{"question":"Which product has the highest gross merchandise value?","generated_query":"SELECT ROUND(SUM(CASE WHEN cancellation_status = 'TRUE' THEN 1 ELSE 0 END) \/ COUNT(*) * 100, 2) AS cancellation_percentage FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE);","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which product has the highest gross merchandise value?","role":"user"},{"content":"SELECT ROUND(SUM(CASE WHEN cancellation_status = 'TRUE' THEN 1 ELSE 0 END) \/ COUNT(*) * 100, 2) AS cancellation_percentage FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE);","role":"assistant"}]}
{"question":"What is the average cancellation rate for each city in the last quarter?","generated_query":"SELECT source, SUM(COALESCE(shipping_expense, 0)) AS total_shipping_expense FROM order_values GROUP BY source ORDER BY total_shipping_expense DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average cancellation rate for each city in the last quarter?","role":"user"},{"content":"SELECT source, SUM(COALESCE(shipping_expense, 0)) AS total_shipping_expense FROM order_values GROUP BY source ORDER BY total_shipping_expense DESC;","role":"assistant"}]}
{"question":"What is the total shipping expense for each source?","generated_query":"SELECT AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE order_date_time_utc >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND customer_id IN (SELECT customer_id FROM customer_demographics WHERE age_group = '18-24');","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total shipping expense for each source?","role":"user"},{"content":"SELECT AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE order_date_time_utc >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND customer_id IN (SELECT customer_id FROM customer_demographics WHERE age_group = '18-24');","role":"assistant"}]}
{"question":"What is the total sales by source for the last year?","generated_query":"SELECT LOWER(product_title) AS product, SUM(COALESCE(net_sales_before_tax, 0)) AS sales FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) AND product_title IS NOT NULL GROUP BY LOWER(product_title) ORDER BY sales DESC LIMIT 3;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales by source for the last year?","role":"user"},{"content":"SELECT LOWER(product_title) AS product, SUM(COALESCE(net_sales_before_tax, 0)) AS sales FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) AND product_title IS NOT NULL GROUP BY LOWER(product_title) ORDER BY sales DESC LIMIT 3;","role":"assistant"}]}
{"question":"What is the total sales amount for the last quarter?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, ROUND(SUM(CASE WHEN cancellation_status = 'TRUE' THEN 1 ELSE 0 END) \/ COUNT(order_id) * 100, 2) AS cancellation_rate FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales amount for the last quarter?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, ROUND(SUM(CASE WHEN cancellation_status = 'TRUE' THEN 1 ELSE 0 END) \/ COUNT(order_id) * 100, 2) AS cancellation_rate FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"Which are the top 5 states by sales in the last quarter?","generated_query":"SELECT LOWER(billing_address_city) AS city, AVG(COALESCE(gross_merchandise_value, 0)) AS avg_order_value FROM order_values GROUP BY LOWER(billing_address_city) ORDER BY avg_order_value DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which are the top 5 states by sales in the last quarter?","role":"user"},{"content":"SELECT LOWER(billing_address_city) AS city, AVG(COALESCE(gross_merchandise_value, 0)) AS avg_order_value FROM order_values GROUP BY LOWER(billing_address_city) ORDER BY avg_order_value DESC LIMIT 1;","role":"assistant"}]}
{"question":"What is the average order value for each product?","generated_query":"SELECT AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE customer_id IN (SELECT customer_id FROM order_values WHERE order_date_time_utc >= DATE_TRUNC('year', ADD_MONTHS(CURRENT_DATE, -1)) AND order_day_of_week IN ('Saturday', 'Sunday'));","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value for each product?","role":"user"},{"content":"SELECT AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE customer_id IN (SELECT customer_id FROM order_values WHERE order_date_time_utc >= DATE_TRUNC('year', ADD_MONTHS(CURRENT_DATE, -1)) AND order_day_of_week IN ('Saturday', 'Sunday'));","role":"assistant"}]}
{"question":"What is the trend of sales for the last 3 months by product category","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, LOWER(product_category) AS product_category, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month, LOWER(product_category) ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the trend of sales for the last 3 months by product category","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, LOWER(product_category) AS product_category, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month, LOWER(product_category) ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"What is the total sales amount for orders with a product title containing 'Gaming Laptop'?","generated_query":"SELECT SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_sales FROM order_values WHERE product_category = 'Fashion';","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales amount for orders with a product title containing 'Gaming Laptop'?","role":"user"},{"content":"SELECT SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_sales FROM order_values WHERE product_category = 'Fashion';","role":"assistant"}]}
{"question":"What is the total sales by day of week","generated_query":"SELECT source, AVG(COALESCE(shipping_expense, 0)) AS avg_shipping_expense FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) GROUP BY source ORDER BY avg_shipping_expense DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales by day of week","role":"user"},{"content":"SELECT source, AVG(COALESCE(shipping_expense, 0)) AS avg_shipping_expense FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) GROUP BY source ORDER BY avg_shipping_expense DESC;","role":"assistant"}]}
{"question":"What is the total refund amount by product category?","generated_query":"SELECT product_category, SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY product_category ORDER BY total_sales DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total refund amount by product category?","role":"user"},{"content":"SELECT product_category, SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY product_category ORDER BY total_sales DESC LIMIT 1;","role":"assistant"}]}
{"question":"What is the total sales amount for orders placed in the last 3 months?","generated_query":"SELECT source, SUM(COALESCE(item_shipping_charge, 0)) AS total_shipping_expense FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY source ORDER BY total_shipping_expense DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales amount for orders placed in the last 3 months?","role":"user"},{"content":"SELECT source, SUM(COALESCE(item_shipping_charge, 0)) AS total_shipping_expense FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY source ORDER BY total_shipping_expense DESC;","role":"assistant"}]}
{"question":"What is the total sales for the last 6 months?","generated_query":"SELECT product_title, SUM(COALESCE(gross_profit, 0)) AS total_gross_profit FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY product_title ORDER BY total_gross_profit DESC LIMIT 2;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales for the last 6 months?","role":"user"},{"content":"SELECT product_title, SUM(COALESCE(gross_profit, 0)) AS total_gross_profit FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY product_title ORDER BY total_gross_profit DESC LIMIT 2;","role":"assistant"}]}
{"question":"What is the average profit margin by product category?","generated_query":"SELECT sku_id, SUM(COALESCE(gross_sales_price_before_tax, 0)) AS total_gross_sales FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY sku_id ORDER BY total_gross_sales DESC LIMIT 3;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average profit margin by product category?","role":"user"},{"content":"SELECT sku_id, SUM(COALESCE(gross_sales_price_before_tax, 0)) AS total_gross_sales FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY sku_id ORDER BY total_gross_sales DESC LIMIT 3;","role":"assistant"}]}
{"question":"What is the total additional fees for the last month?","generated_query":"SELECT SUM(COALESCE(item_additional_fees, 0)) AS total_additional_fees FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE);","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total additional fees for the last month?","role":"user"},{"content":"SELECT SUM(COALESCE(item_additional_fees, 0)) AS total_additional_fees FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE);","role":"assistant"}]}
{"question":"Show me the trend of orders from Shopify for this year","generated_query":"SELECT order_day_of_month, AVG(net_sales_before_tax) AS avg_order_value FROM order_values WHERE order_month = 4 AND order_year = 2024 GROUP BY order_day_of_month ORDER BY avg_order_value DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Show me the trend of orders from Shopify for this year","role":"user"},{"content":"SELECT order_day_of_month, AVG(net_sales_before_tax) AS avg_order_value FROM order_values WHERE order_month = 4 AND order_year = 2024 GROUP BY order_day_of_month ORDER BY avg_order_value DESC;","role":"assistant"}]}
{"question":"What is the percentage of orders that were fulfilled in the last 3 months?","generated_query":"SELECT SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) - 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the percentage of orders that were fulfilled in the last 3 months?","role":"user"},{"content":"SELECT SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) - 1;","role":"assistant"}]}
{"question":"Which are the top 5 products by profit in the last 6 months?","generated_query":"SELECT LOWER(product_title) AS product_title, SUM(COALESCE(gross_profit, 0)) AS total_profit FROM order_values WHERE order_date >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND order_date < DATE_TRUNC('month', CURRENT_DATE) GROUP BY LOWER(product_title) ORDER BY total_profit DESC LIMIT 5;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which are the top 5 products by profit in the last 6 months?","role":"user"},{"content":"SELECT LOWER(product_title) AS product_title, SUM(COALESCE(gross_profit, 0)) AS total_profit FROM order_values WHERE order_date >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND order_date < DATE_TRUNC('month', CURRENT_DATE) GROUP BY LOWER(product_title) ORDER BY total_profit DESC LIMIT 5;","role":"assistant"}]}
{"question":"Which are the top 3 products by sales in 2022?","generated_query":"SELECT product_title, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = 2022 GROUP BY product_title ORDER BY total_sales DESC LIMIT 3;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which are the top 3 products by sales in 2022?","role":"user"},{"content":"SELECT product_title, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = 2022 GROUP BY product_title ORDER BY total_sales DESC LIMIT 3;","role":"assistant"}]}
{"question":"Which are the top 3 products by sales in Q3 2022?","generated_query":"SELECT product_title, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = 2022 AND order_quarter = 3 GROUP BY product_title ORDER BY total_sales DESC LIMIT 3;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which are the top 3 products by sales in Q3 2022?","role":"user"},{"content":"SELECT product_title, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = 2022 AND order_quarter = 3 GROUP BY product_title ORDER BY total_sales DESC LIMIT 3;","role":"assistant"}]}
{"question":"What is the revenue trend by quarter for the last 3 years?","generated_query":"SELECT sku_id, SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_revenue FROM order_values WHERE order_date >= DATE_TRUNC('quarter', CURRENT_DATE) AND order_date < DATE_TRUNC('quarter', ADD_MONTHS(CURRENT_DATE, 3)) GROUP BY sku_id ORDER BY total_revenue DESC LIMIT 1","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the revenue trend by quarter for the last 3 years?","role":"user"},{"content":"SELECT sku_id, SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_revenue FROM order_values WHERE order_date >= DATE_TRUNC('quarter', CURRENT_DATE) AND order_date < DATE_TRUNC('quarter', ADD_MONTHS(CURRENT_DATE, 3)) GROUP BY sku_id ORDER BY total_revenue DESC LIMIT 1","role":"assistant"}]}
{"question":"What is the average gross profit margin for the last 3 months?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_date >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average gross profit margin for the last 3 months?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_date >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"What is the average order value in the last 12 months?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(total_returns_before_tax, 0)) \/ SUM(COALESCE(gross_sales_price_after_tax, 0)) AS return_rate FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value in the last 12 months?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(total_returns_before_tax, 0)) \/ SUM(COALESCE(gross_sales_price_after_tax, 0)) AS return_rate FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month","role":"assistant"}]}
{"question":"What is the percentage of orders with refunds in the last quarter?","generated_query":"SELECT product_category, SUM(COALESCE(gross_merchandise_value, 0)) AS total_sales FROM order_values GROUP BY product_category ORDER BY total_sales DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the percentage of orders with refunds in the last quarter?","role":"user"},{"content":"SELECT product_category, SUM(COALESCE(gross_merchandise_value, 0)) AS total_sales FROM order_values GROUP BY product_category ORDER BY total_sales DESC LIMIT 1;","role":"assistant"}]}
{"question":"What is the average order value for customers in the 18-24 age group in the last 6 months?","generated_query":"SELECT LOWER(product_category) AS product_category, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(DATE_TRUNC('quarter', CURRENT_DATE)) AND order_quarter = QUARTER(DATE_TRUNC('quarter', CURRENT_DATE)) GROUP BY LOWER(product_category) ORDER BY total_sales DESC LIMIT 5;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value for customers in the 18-24 age group in the last 6 months?","role":"user"},{"content":"SELECT LOWER(product_category) AS product_category, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(DATE_TRUNC('quarter', CURRENT_DATE)) AND order_quarter = QUARTER(DATE_TRUNC('quarter', CURRENT_DATE)) GROUP BY LOWER(product_category) ORDER BY total_sales DESC LIMIT 5;","role":"assistant"}]}
{"question":"What is the trend of AOV for Shopify in the last 3 months","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE source = 'Shopify' AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the trend of AOV for Shopify in the last 3 months","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE source = 'Shopify' AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"What is the average order value by product id for the last month?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(gross_merchandise_value, 0)) AS gross_merchandise_value FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value by product id for the last month?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(gross_merchandise_value, 0)) AS gross_merchandise_value FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"Which are the top 2 products by sales in the last month","generated_query":"SELECT LOWER(product_title) AS product, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) GROUP BY product_title ORDER BY total_sales DESC LIMIT 2;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which are the top 2 products by sales in the last month","role":"user"},{"content":"SELECT LOWER(product_title) AS product, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) GROUP BY product_title ORDER BY total_sales DESC LIMIT 2;","role":"assistant"}]}
{"question":"What is the average order frequency per customer in the last year?","generated_query":"SELECT LOWER(product_category) AS category, SUM(COALESCE(total_returns_before_tax, 0)) \/ SUM(COALESCE(net_sales_before_tax, 0)) AS return_rate FROM order_values WHERE order_quarter = QUARTER(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) AND product_category IS NOT NULL GROUP BY LOWER(product_category) ORDER BY return_rate DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order frequency per customer in the last year?","role":"user"},{"content":"SELECT LOWER(product_category) AS category, SUM(COALESCE(total_returns_before_tax, 0)) \/ SUM(COALESCE(net_sales_before_tax, 0)) AS return_rate FROM order_values WHERE order_quarter = QUARTER(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) AND product_category IS NOT NULL GROUP BY LOWER(product_category) ORDER BY return_rate DESC;","role":"assistant"}]}
{"question":"Show me the sales performance by hour of the day for the last quarter","generated_query":"SELECT product_title, SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY product_title ORDER BY total_sales DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Show me the sales performance by hour of the day for the last quarter","role":"user"},{"content":"SELECT product_title, SUM(COALESCE(gross_sales_price_after_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY product_title ORDER BY total_sales DESC LIMIT 1;","role":"assistant"}]}
{"question":"What is the average order value by source?","generated_query":"SELECT source, AVG(COALESCE(gross_sales_price_before_tax, 0)) AS average_order_value FROM order_values GROUP BY source ORDER BY average_order_value DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value by source?","role":"user"},{"content":"SELECT source, AVG(COALESCE(gross_sales_price_before_tax, 0)) AS average_order_value FROM order_values GROUP BY source ORDER BY average_order_value DESC;","role":"assistant"}]}
{"question":"Show me the trend of cancellations for Shopify in the last 2 months","generated_query":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) AND billing_address_city IS NOT NULL GROUP BY LOWER(billing_address_city) ORDER BY total_sales DESC LIMIT 5;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Show me the trend of cancellations for Shopify in the last 2 months","role":"user"},{"content":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -6)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) AND billing_address_city IS NOT NULL GROUP BY LOWER(billing_address_city) ORDER BY total_sales DESC LIMIT 5;","role":"assistant"}]}
{"question":"What is the total refund amount for each source?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(gross_profit, 0)) AS gross_profit FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total refund amount for each source?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, SUM(COALESCE(gross_profit, 0)) AS gross_profit FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"What is the average order value trend for the last 3 months?","generated_query":"SELECT LOWER(source) AS channel, SUM(COALESCE(gross_sales_price_after_tax, 0)) \/ COUNT(DISTINCT customer_id) AS customer_lifetime_value FROM order_values GROUP BY LOWER(source) ORDER BY customer_lifetime_value DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value trend for the last 3 months?","role":"user"},{"content":"SELECT LOWER(source) AS channel, SUM(COALESCE(gross_sales_price_after_tax, 0)) \/ COUNT(DISTINCT customer_id) AS customer_lifetime_value FROM order_values GROUP BY LOWER(source) ORDER BY customer_lifetime_value DESC;","role":"assistant"}]}
{"question":"What is the total sales for each quarter?","generated_query":"SELECT AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE customer_id IN (SELECT customer_id FROM order_values WHERE order_date_time_utc >= DATE_TRUNC('year', ADD_MONTHS(CURRENT_DATE, -1)) GROUP BY customer_id HAVING COUNT(order_id) > 5);","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total sales for each quarter?","role":"user"},{"content":"SELECT AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE customer_id IN (SELECT customer_id FROM order_values WHERE order_date_time_utc >= DATE_TRUNC('year', ADD_MONTHS(CURRENT_DATE, -1)) GROUP BY customer_id HAVING COUNT(order_id) > 5);","role":"assistant"}]}
{"question":"What is the total gross sales by source for the last quarter?","generated_query":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE billing_address_city IS NOT NULL GROUP BY LOWER(billing_address_city) ORDER BY total_sales DESC LIMIT 3;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total gross sales by source for the last quarter?","role":"user"},{"content":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE billing_address_city IS NOT NULL GROUP BY LOWER(billing_address_city) ORDER BY total_sales DESC LIMIT 3;","role":"assistant"}]}
{"question":"What is the average order value by product category for the last month?","generated_query":"SELECT product_category, AVG(COALESCE(net_sales_before_tax, 0)) AS avg_order_value FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) GROUP BY product_category ORDER BY avg_order_value DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value by product category for the last month?","role":"user"},{"content":"SELECT product_category, AVG(COALESCE(net_sales_before_tax, 0)) AS avg_order_value FROM order_values WHERE order_month = MONTH(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) GROUP BY product_category ORDER BY avg_order_value DESC;","role":"assistant"}]}
{"question":"What is the total tax amount for orders placed in the last month?","generated_query":"SELECT LOWER(product_title) AS product, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY LOWER(product_title) ORDER BY total_sales DESC LIMIT 5;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total tax amount for orders placed in the last month?","role":"user"},{"content":"SELECT LOWER(product_title) AS product, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY LOWER(product_title) ORDER BY total_sales DESC LIMIT 5;","role":"assistant"}]}
{"question":"What is the average shipping expense for Shopify orders in 2023?","generated_query":"SELECT ROUND(SUM(CASE WHEN payment_status = 'paid' THEN 1 ELSE 0 END) \/ COUNT(*) * 100, 2) AS paid_orders_percentage FROM order_values WHERE order_date >= DATE_TRUNC('month', CURRENT_DATE) - INTERVAL 1 MONTH AND order_date < DATE_TRUNC('month', CURRENT_DATE);","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average shipping expense for Shopify orders in 2023?","role":"user"},{"content":"SELECT ROUND(SUM(CASE WHEN payment_status = 'paid' THEN 1 ELSE 0 END) \/ COUNT(*) * 100, 2) AS paid_orders_percentage FROM order_values WHERE order_date >= DATE_TRUNC('month', CURRENT_DATE) - INTERVAL 1 MONTH AND order_date < DATE_TRUNC('month', CURRENT_DATE);","role":"assistant"}]}
{"question":"Which are the top 5 products by gross profit for the last month?","generated_query":"SELECT ROUND(AVG(COALESCE(net_sales_before_tax, 0)), 2) AS average_order_value FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) - 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which are the top 5 products by gross profit for the last month?","role":"user"},{"content":"SELECT ROUND(AVG(COALESCE(net_sales_before_tax, 0)), 2) AS average_order_value FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) - 1;","role":"assistant"}]}
{"question":"What is the trend of gross profit for the last 12 months?","generated_query":"SELECT SUM(COALESCE(gross_merchandise_value, 0)) AS total_sales FROM order_values WHERE order_date >= DATE_TRUNC('month', CURRENT_DATE) - INTERVAL 3 MONTH AND order_date < DATE_TRUNC('month', CURRENT_DATE);","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the trend of gross profit for the last 12 months?","role":"user"},{"content":"SELECT SUM(COALESCE(gross_merchandise_value, 0)) AS total_sales FROM order_values WHERE order_date >= DATE_TRUNC('month', CURRENT_DATE) - INTERVAL 3 MONTH AND order_date < DATE_TRUNC('month', CURRENT_DATE);","role":"assistant"}]}
{"question":"What is the average order value for each month in the last year?","generated_query":"SELECT LOWER(product_title) AS product, (gross_profit \/ net_sales_before_tax) * 100 AS profit_margin FROM order_values WHERE order_quarter = 4 AND order_year = 2023 GROUP BY LOWER(product_title), gross_profit, net_sales_before_tax ORDER BY profit_margin DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value for each month in the last year?","role":"user"},{"content":"SELECT LOWER(product_title) AS product, (gross_profit \/ net_sales_before_tax) * 100 AS profit_margin FROM order_values WHERE order_quarter = 4 AND order_year = 2023 GROUP BY LOWER(product_title), gross_profit, net_sales_before_tax ORDER BY profit_margin DESC LIMIT 1;","role":"assistant"}]}
{"question":"What is the percentage of returns for new customers in June 2023?","generated_query":"SELECT LOWER(product_category) AS category, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_quarter = QUARTER(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) GROUP BY LOWER(product_category) ORDER BY total_sales DESC;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the percentage of returns for new customers in June 2023?","role":"user"},{"content":"SELECT LOWER(product_category) AS category, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_quarter = QUARTER(CURRENT_DATE) AND order_year = YEAR(CURRENT_DATE) GROUP BY LOWER(product_category) ORDER BY total_sales DESC;","role":"assistant"}]}
{"question":"Which SKU has the highest return rate in the last quarter?","generated_query":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_quarter = 4 AND order_year = 2023 GROUP BY LOWER(billing_address_city) ORDER BY total_sales DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which SKU has the highest return rate in the last quarter?","role":"user"},{"content":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(net_sales_before_tax, 0)) AS total_sales FROM order_values WHERE order_quarter = 4 AND order_year = 2023 GROUP BY LOWER(billing_address_city) ORDER BY total_sales DESC LIMIT 1;","role":"assistant"}]}
{"question":"Which category has the highest return rate in the last 3 months?","generated_query":"SELECT product_category, AVG(COALESCE(gross_merchandise_value, 0)) AS avg_order_value FROM order_values GROUP BY product_category ORDER BY avg_order_value DESC LIMIT 1;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"Which category has the highest return rate in the last 3 months?","role":"user"},{"content":"SELECT product_category, AVG(COALESCE(gross_merchandise_value, 0)) AS avg_order_value FROM order_values GROUP BY product_category ORDER BY avg_order_value DESC LIMIT 1;","role":"assistant"}]}
{"question":"What is the trend of sales by product category in the last 9 months?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the trend of sales by product category in the last 9 months?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, AVG(COALESCE(gross_sales_price_after_tax, 0)) AS avg_order_value FROM order_values WHERE TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"What is the average order value by customer type (new or returning)?","generated_query":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(profit_cm1, 0)) \/ SUM(COALESCE(net_sales_before_tax, 0)) * 100 AS cm1_margin FROM order_values WHERE order_quarter = EXTRACT(QUARTER FROM CURRENT_DATE) AND order_year = EXTRACT(YEAR FROM CURRENT_DATE) GROUP BY LOWER(billing_address_city) ORDER BY cm1_margin DESC LIMIT 3;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average order value by customer type (new or returning)?","role":"user"},{"content":"SELECT LOWER(billing_address_city) AS city, SUM(COALESCE(profit_cm1, 0)) \/ SUM(COALESCE(net_sales_before_tax, 0)) * 100 AS cm1_margin FROM order_values WHERE order_quarter = EXTRACT(QUARTER FROM CURRENT_DATE) AND order_year = EXTRACT(YEAR FROM CURRENT_DATE) GROUP BY LOWER(billing_address_city) ORDER BY cm1_margin DESC LIMIT 3;","role":"assistant"}]}
{"question":"What is the total duties collected for the last year?","generated_query":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, COUNT(DISTINCT order_id) AS total_returns FROM order_values WHERE refund_status = 'TRUE' AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the total duties collected for the last year?","role":"user"},{"content":"SELECT CONCAT(order_year, '-', LPAD(order_month, 2, '0')) AS order_date, COUNT(DISTINCT order_id) AS total_returns FROM order_values WHERE refund_status = 'TRUE' AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -12)) AND TO_DATE(CONCAT(order_year, '-', LPAD(order_month, 2, '0')), 'yyyy-MM') < DATE_TRUNC('month', CURRENT_DATE) GROUP BY order_year, order_month ORDER BY order_year, order_month;","role":"assistant"}]}
{"question":"What is the average shipping expense per order in the last quarter?","generated_query":"SELECT sku_id, SUM(ordered_quantity) AS total_sold FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY sku_id ORDER BY total_sold DESC LIMIT 5;","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"What is the average shipping expense per order in the last quarter?","role":"user"},{"content":"SELECT sku_id, SUM(ordered_quantity) AS total_sold FROM order_values WHERE order_year = YEAR(CURRENT_DATE) AND order_quarter = QUARTER(CURRENT_DATE) GROUP BY sku_id ORDER BY total_sold DESC LIMIT 5;","role":"assistant"}]}
{"question":"How many orders were cancelled within the last 3 months?","generated_query":"SELECT COUNT(order_id) FROM order_values WHERE cancellation_status = 'TRUE' AND order_date >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND order_date < DATE_TRUNC('month', CURRENT_DATE);","messages":[{"content":"\nYou are a SQL expert in Mysql. As a SQL expert, your job is to answer data related questions from the business team accurately by writing SQL queries. Refer to the provided database schema for tables and columns. Do not correct spelling mistakes in the schema.\n\nPlease generate only read\/SELECT queries for data safety. If a question cannot be answered using a SELECT operation, it should not be addressed.\nRefer the sample queries to see how date filters and calculations are done. Pay high attention on sample queries that seem most relevant to user question.\n\nFormat your responses as JSON, including the SQL query and the following associated fields. Use this format:\n\ngenerated_query:[{\"sql_query\": \"Your SQL Query Here\", \"logic\": \"Explain briefly the logic you used\", \"response\": \"A friendly and conversational response to give more context to the user.\", \"chart\": {\"type\": \"The type of chart\", \"x_axis\": [\"Array of variables in the x-axis of the chart\"], \"y_axis\": [\"Array of variables in the y-axis of the chart\"]} }]\n\n## Database Schema:\n{\n    \"order_values\": \"This table contains comprehensive order information including pricing, tax, discounts, returns, shipping, and product details. Each row represents a unique line item within an order and includes timestamps, statuses, and financials associated with the order.\",\n}\nCOLUMNS = {\n    \"order_values\": {\n        \"order_line_item_id\": {\n            \"description\": \"Unique identifier for each line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"source\": {\n            \"description\": \"Source of the order (e.g., platform or channel)\",\n            \"values_sample\": [\"shopify\"],\n        },\n        \"order_id\": {\n            \"description\": \"Unique identifier for each order\",\n            \"values_sample\": [\"shopify_5667598663969\"],\n        },\n        \"ordered_quantity\": {\n            \"description\": \"Quantity of each item ordered\",\n            \"values_sample\": [1],\n        },\n        \"gross_sales_price_after_tax\": {\n            \"description\": \"Gross sales price after tax is applied\",\n            \"values_sample\": [150.00],\n        },\n        \"tax_percent\": {\n            \"description\": \"Tax percentage applied to the order\",\n            \"values_sample\": [18.0],\n        },\n        \"total_price_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [20.00],\n        },\n        \"gross_sales_price_before_tax\": {\n            \"description\": \"Gross sales price before tax is applied\",\n            \"values_sample\": [127.12],\n        },\n        \"total_discount_after_tax\": {\n            \"description\": \"Total discount amount after tax is applied\",\n            \"values_sample\": [10.00],\n        },\n        \"total_discount_tax\": {\n            \"description\": \"Total tax amount on the discount applied\",\n            \"values_sample\": [1.80],\n        },\n        \"total_discount_before_tax\": {\n            \"description\": \"Total discount amount before tax is applied\",\n            \"values_sample\": [8.20],\n        },\n        \"total_cancellation_returns_before_tax\": {\n            \"description\": \"Total cancellation returns amount before tax\",\n            \"values_sample\": [20.00],\n        },\n        \"total_rto_returns_before_tax\": {\n            \"description\": \"Total RTO (Return to Origin) returns amount before tax\",\n            \"values_sample\": [15.00],\n        },\n        \"total_returns_refund_before_tax\": {\n            \"description\": \"Total refund amount before tax due to returns\",\n            \"values_sample\": [30.00],\n        },\n        \"total_returns_before_tax\": {\n            \"description\": \"Total returns amount before tax, including all types of returns\",\n            \"values_sample\": [25.00],\n        },\n        \"total_return_tax\": {\n            \"description\": \"Total tax amount on returns\",\n            \"values_sample\": [4.50],\n        },\n        \"net_sales_before_tax\": {\n            \"description\": \"Net sales amount before tax is applied\",\n            \"values_sample\": [100.00],\n        },\n        \"item_shipping_charge\": {\n            \"description\": \"Shipping charge for the item\",\n            \"values_sample\": [5.00],\n        },\n        \"item_duties\": {\n            \"description\": \"Duties charged for the item\",\n            \"values_sample\": [3.00],\n        },\n        \"item_additional_fees\": {\n            \"description\": \"Additional fees associated with the item\",\n            \"values_sample\": [2.00],\n        },\n        \"total_tax\": {\n            \"description\": \"Total tax amount applied to the order\",\n            \"values_sample\": [18.00],\n        },\n        \"total_sales_after_tax\": {\n            \"description\": \"Total sales amount after tax is applied\",\n            \"values_sample\": [120.00],\n        },\n        \"gross_merchandise_value\": {\n            \"description\": \"Gross merchandise value of the item\",\n            \"values_sample\": [150.00],\n        },\n        \"sku_id\": {\n            \"description\": \"Unique identifier for each SKU (Stock Keeping Unit)\",\n            \"values_sample\": [\"shopify_8848983261473_47478863036705\"],\n        },\n        \"sku_code\": {\n            \"description\": \"Code assigned to each SKU\",\n            \"values_sample\": [\"BSL-D-SIP-0001\"],\n        },\n        \"product_category\": {\n            \"description\": \"Category of the product\",\n            \"values_sample\": [\"Insulated Sipper\"],\n        },\n        \"product_id\": {\n            \"description\": \"Unique identifier for each product\",\n            \"values_sample\": [\"shopify_8848983261473\"],\n        },\n        \"product_title\": {\n            \"description\": \"Title of the product\",\n            \"values_sample\": [\"Kids Sipper (430 ml)\"],\n        },\n        \"product_price\": {\n            \"description\": \"Price of the product\",\n            \"values_sample\": [999],\n        },\n        \"customer_id\": {\n            \"description\": \"Unique identifier for each customer\",\n            \"values_sample\": [\"shopify_7694075199777\"],\n        },\n        \"first_ordered_at\": {\n            \"description\": \"Timestamp of the customer's first order\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_refund_line_item_id\": {\n            \"description\": \"Unique identifier for each refunded line item in an order\",\n            \"values_sample\": [\"shopify_5667598663969_14461737632033\"],\n        },\n        \"order_date_time_utc\": {\n            \"description\": \"Order date and time in UTC\",\n            \"values_sample\": [\"2024-02-14 16:00:13.000000\"],\n        },\n        \"order_date_time\": {\n            \"description\": \"Local date and time of the order\",\n            \"values_sample\": [\"2024-02-14 11:00:13.000000\"],\n        },\n        \"order_date\": {\n            \"description\": \"Date of the order\",\n            \"values_sample\": [\"2024-02-14\"],\n        },\n        \"order_year\": {\n            \"description\": \"Year of the order\",\n            \"values_sample\": [2024],\n        },\n        \"order_quarter\": {\n            \"description\": \"Quarter of the year when the order was placed\",\n            \"values_sample\": [1],\n        },\n        \"order_month\": {\n            \"description\": \"Month of the order\",\n            \"values_sample\": [2],\n        },\n        \"order_day_of_month\": {\n            \"description\": \"Day of the month of the order\",\n            \"values_sample\": [14],\n        },\n        \"order_week\": {\n            \"description\": \"Week of the year when the order was placed\",\n            \"values_sample\": [7],\n        },\n        \"order_day_of_week\": {\n            \"description\": \"Day of the week of the order\",\n            \"values_sample\": [4],  # Assuming Sunday is 0\n        },\n        \"order_hour\": {\n            \"description\": \"Hour of the day when the order was placed\",\n            \"values_sample\": [16],\n        },\n        \"order_minute\": {\n            \"description\": \"Minute of the hour when the order was placed\",\n            \"values_sample\": [0],\n        },\n        \"order_time\": {\n            \"description\": \"Time of the order\",\n            \"values_sample\": [\"16:00\"],\n        },\n        \"refund_status\": {\n            \"description\": \"Refund status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"rto_status\": {\n            \"description\": \"Return to Origin (RTO) status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"cancellation_status\": {\n            \"description\": \"Cancellation status of the order\",\n            \"values_sample\": [\"false\"],\n        },\n        \"order_status\": {\n            \"description\": \"Current status of the order\",\n            \"values_sample\": [\"completed\"],\n        },\n        \"payment_status\": {\n            \"description\": \"Payment status of the order\",\n            \"values_sample\": [\"paid\"],\n        },\n        \"return_reason\": {\n            \"description\": \"Reason for return, if applicable\",\n            \"values_sample\": [\"damaged item\"],\n        },\n        \"billing_address_city\": {\n            \"description\": \"City of the billing address\",\n            \"values_sample\": [\"Surat\"],\n        },\n        \"billing_address_state\": {\n            \"description\": \"State of the billing address\",\n            \"values_sample\": [\"Gujarat\"],\n        },\n        \"billing_address_country\": {\n            \"description\": \"Country of the billing address\",\n            \"values_sample\": [\"India\"],\n        },\n        \"gift_wrap_expense\": {\n            \"description\": \"Expense incurred for gift wrapping\",\n            \"values_sample\": [5.00],\n        },\n        \"packaging_expense\": {\n            \"description\": \"Expense incurred for packaging\",\n            \"values_sample\": [3.00],\n        },\n        \"handling_expense\": {\n            \"description\": \"Expense incurred for handling\",\n            \"values_sample\": [2.00],\n        },\n        \"shipping_expense\": {\n            \"description\": \"Expense incurred for shipping\",\n            \"values_sample\": [10.00],\n        },\n        \"marketplace_expense\": {\n            \"description\": \"Marketplace fees associated with the order\",\n            \"values_sample\": [8.00],\n        },\n        \"payment_gateway_expense\": {\n            \"description\": \"Fees charged by the payment gateway\",\n            \"values_sample\": [4.00],\n        },\n        \"other_adjustments\": {\n            \"description\": \"Other adjustments related to the order\",\n            \"values_sample\": [2.50],\n        },\n        \"estimated_expense\": {\n            \"description\": \"Estimated total expense for the order\",\n            \"values_sample\": [20.00],\n        },\n        \"sku_cost\": {\n            \"description\": \"Cost of the SKU\",\n            \"values_sample\": [75.00],\n        },\n        \"gross_profit\": {\n            \"description\": \"Gross profit for the order\",\n            \"values_sample\": [50.00],\n        },\n        \"cm1_expense\": {\n            \"description\": \"CM1 (Contribution Margin 1) expense\",\n            \"values_sample\": [10.00],\n        },\n        \"profit_cm1\": {\n            \"description\": \"CM1 profit for the order\",\n            \"values_sample\": [40.00],\n        },\n        \"_synced_at\": {\n            \"description\": \"Timestamp when the data was last synced\",\n            \"values_sample\": [\"2024-02-14 16:30:00.000000\"],\n        },\n    },\n}\n\n## Guidelines that are necessary to follow for making correct SQL queries:\n1. Whenever working with any text fields, always cast both column and value to lowercase before performing any operations on them.\n2. Chart Type, X-axis and Y-axis will be \"null\" when the question asks for a single value instead of a trend or split.\n3. Ensure numeric typecasting for numerators in division operations.\n4. Use lowercase for string matching to maintain consistency. Note: Do type casting to varchar only if needed (mainly in case of Mssql DB type).\n5. Apply the same operation in both GROUP BY and SELECT clauses when referencing the same field.\n6. Create aliases for fields in SELECT on which operations are applied.\n7. Always prefix field names with table or alias names in joins.\n8. Treat numeric fields as measures and text, enums, and time fields as dimensions in aggregation queries.\n9. Please do not refer the database name in column or table names.\n10. Prevent zero division errors by validating the denominator in division operations.\n11. Exclude null values in aggregations of numeric fields.\n12. Use LOWER in GROUP BY only if the same column in SELECT is also in LOWER.\n13. Please consider the granularity level of the table and do appropriate aggregations.\ne.g.: If order_data table has Order ID - SKU ID columns, and question is asked at order level, group rows by Order ID. Write queries accordingly.\n14. In case time period is not mentioned, use last 12 calendar months data only for calculations, unless lifetime value like questions are asked.\n15. Consider order by ABS value wherever seems logical.\n16. Round the calculations to 2 decimal points at appropriate places, like AVG and Percentages.\n17. Please type-cast the date columns appropriately before making any date based comparisons (only if needed). E.g. for IBM I DB2 ``` to_date(cast(date_column as char(8)),'YYYYMMDD') < current date' ```\n\n## Additional guidelines specific for IBM I DB2:\n18. In case of IBM I DB2 queries do not end with semi-colon ';'\n19. In case of IBM I DB2 syntax to get top x rows is 'FETCH TOP x ROWS ONLY'.\n20. Column names in IBM I DB2 are in upper case and should match in chart dict.\n\n## Response:\n","role":"system"},{"content":"How many orders were cancelled within the last 3 months?","role":"user"},{"content":"SELECT COUNT(order_id) FROM order_values WHERE cancellation_status = 'TRUE' AND order_date >= DATE_TRUNC('month', ADD_MONTHS(CURRENT_DATE, -3)) AND order_date < DATE_TRUNC('month', CURRENT_DATE);","role":"assistant"}]}