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My_SQL_Connection.py

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+### In this file we will store all the codes related to connection to my sql server.
+
+import mysql.connector
+import pandas as pd
+###======================================================================database details-=======================================================
+def database_details(host,user,password):
+    connection = mysql.connector.connect(
+        host = host,
+        user = user,
+        password = password,
+        buffered = True
+        )
+    cursor = connection.cursor()
+    databases = ("Show databases")
+    cursor.execute(databases)
+    db = []
+    for (databases) in cursor:
+        db.append(databases[0])
+
+    cursor.close()
+    connection.close()
+    return db, len(db)
+
+#### =========================================================================retrieving the tables==========================================================
+def tables_in_this_DB(host,user,password,db_name):
+    db_config = {
+        'host':host,
+        'user': user,
+        'password': password,
+        'database': db_name,
+    }
+    connection = mysql.connector.connect(**db_config)
+    cursor = connection.cursor()
+    query1 = "SHOW TABLES"
+    cursor.execute(query1)
+    tables = cursor.fetchall()
+
+    cursor.close()
+    connection.close()
+    return tables, len(tables)
+
+#### ==================================================Printing the tables=======================================================================
+def printing_tables(host,user,password,db_name):
+    db_config = {
+        'host':host,
+        'user': user,
+        'password': password,
+        'database': db_name,
+    }
+    connection = mysql.connector.connect(**db_config)
+    cursor = connection.cursor()
+    cursor.execute("SHOW TABLES")
+    table_names = [table[0] for table in cursor.fetchall()]
+
+    tables_data = {}
+
+    for table_name in table_names:
+        query = f"SELECT * FROM {table_name}"
+        cursor.execute(query)
+        rows = cursor.fetchall()
+
+        col_names = [desc[0] for desc in cursor.description]
+        df = pd.DataFrame(rows, columns=col_names)
+
+        tables_data[table_name] = df
+    cursor.close()
+    connection.close()
+    return tables_data
+
+
+
+def create_table_command(host,user,password,db_name):
+    db_config = {
+        'host': host,
+        'user': user,
+        'password': password,
+        'database': db_name,
+    }
+
+    connection = mysql.connector.connect(**db_config)
+    cursor = connection.cursor()
+    query = "SHOW TABLES"
+    cursor.execute(query)
+    table_names = [table[0] for table in cursor.fetchall()]
+
+    create_table_statements = {}
+    for table_name in table_names:
+        query = f"SHOW CREATE TABLE {table_name}"
+        cursor.execute(query)
+        create_table_data = cursor.fetchone()
+
+        if create_table_data:
+            # The CREATE TABLE statement is in the second element of the tuple
+            create_table_statement = create_table_data[1]
+            create_table_statement = create_table_statement.split("ENGINE=")[0].strip()
+            create_table_statements[table_name] = create_table_statement
+
+    cursor.close()
+    connection.close()
+
+    return create_table_statements

app.py

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+import streamlit as st
+
+from My_SQL_Connection import database_details, tables_in_this_DB, printing_tables, create_table_command
+from streamlit_option_menu import option_menu
+from model_functions import LOAD_GEMMA
+import torch
+
+
+user_name = 'arya'
+
+
+
+if 'localhost' not in st.session_state:
+    st.session_state.localhost = ''
+    st.session_state.user = ''
+    st.session_state.password = ''
+    st.session_state.table_commands = """ """
+
+with st.sidebar:
+    selected = option_menu("Querio Lingua", ["Log In", 'main functionalities','Chat with AI'],
+                           icons=['house', 'gear', 'robot'], menu_icon="cast", default_index=1)
+
+if selected == 'Log In':
+    st.title(f'welcome to our web application :green[{user_name}]')
+    st.subheader('welcome to our MY SQL Database Explorer ~ ')
+
+    st.write('First Check how many databases you have in your server ~')
+    st.session_state.localhost = st.text_input("what is your host, (localhost if in local) or give the url", 'localhost',help='host')
+    st.session_state.user = st.text_input("what is your user name (usually root)", 'root')
+    st.session_state.password = st.text_input('Password', type='password')
+
+elif selected == 'main functionalities':
+    st.title(f'welcome to our web application :green[{user_name}]')
+    st.subheader('welcome to our MY SQL Database Explorer ~ ')
+    if st.button('All your databases ~ '):
+        db, l = database_details(st.session_state.localhost, st.session_state.user, st.session_state.password)
+        st.table(db)
+
+    st.subheader('Now we will see details of any database~ ')
+
+    st.session_state.db_name = st.text_input('Which Database you want')
+
+    if st.button('All tables present in that particular database'):
+        if not st.session_state.db_name:
+            st.warning('Input database name first')
+        else:
+            tables, l = tables_in_this_DB(st.session_state.localhost, st.session_state.user, st.session_state.password, st.session_state.db_name)
+            st.write(f'There is only {l} tables present in this database')
+            st.write(tables)
+
+    st.subheader('check out tables~ ')
+
+    if st.button('Print the tables~'):
+        tables_data = printing_tables(st.session_state.localhost, st.session_state.user, st.session_state.password, st.session_state.db_name)
+        for table_name, table_data in tables_data.items():
+            st.write(f"Table: {table_name}")
+            st.table(table_data)
+
+    st.subheader('Retrieve the CREATE TABLE Statements')
+
+    if st.button('Generate statements'):
+        statements = create_table_command(st.session_state.localhost, st.session_state.user, st.session_state.password, st.session_state.db_name)
+        for table_name, table_statements in statements.items():
+            st.write(f'{table_name}')
+            st.session_state.table_commands = table_statements
+            st.code(table_statements)
+
+
+elif selected == 'Chat with AI':
+    #st.set_page_config(page_title='🧠MemoryBot🤖', layout='wide')
+    # Initialize session states
+    if "generated" not in st.session_state:
+        st.session_state["generated"] = []
+    if "past" not in st.session_state:
+        st.session_state["past"] = []
+    if "input" not in st.session_state:
+        st.session_state["input"] = ""
+    if "stored_session" not in st.session_state:
+        st.session_state["stored_session"] = []
+
+    def get_text():
+        """
+        Get the user input text.
+
+        Returns:
+            (str): The text entered by the user
+        """
+        input_text = st.text_input("You: ", st.session_state["input"], key="input",
+                                placeholder="Your AI assistant here! Ask me anything ...", 
+                                label_visibility='hidden')
+        return input_text
+    
+    def new_chat():
+        """
+        Clears session state and starts a new chat.
+        """
+        save = []
+        for i in range(len(st.session_state['generated'])-1, -1, -1):
+            save.append("User:" + st.session_state["past"][i])
+            save.append("Bot:" + st.session_state["generated"][i])        
+        st.session_state["stored_session"].append(save)
+        st.session_state["generated"] = []
+        st.session_state["past"] = []
+        st.session_state["input"] = ""
+    
+    with st.sidebar.expander("🛠️ ", expanded=False):
+        MODEL = st.selectbox(label='Model', options=['GEMMA-2B FINE TUNED'])
+        
+
+    st.title("🤖 Chat Bot with 🧠")
+    st.subheader(" Powered by 🚀 GEMMA")
+
+
+    st.sidebar.button("New Chat", on_click = new_chat, type='primary')
+    user_input = get_text()
+
+    if user_input:
+        tokenizer,model = LOAD_GEMMA()
+        device = torch.device("cpu")
+        alpeca_prompt = f"""Below are sql tables schemas paired with instruction that describes a task. Using valid SQLite, write a response that appropriately completes the request for the provided tables.
+         ### Instruction: {user_input}. ### Input: {st.session_state.table_commands}
+                            ### Response:
+                            """
+        with st.status('Generating Result',expanded=False) as status:
+            inputs = tokenizer([alpeca_prompt], return_tensors="pt").to(device)
+            outputs = model.generate(**inputs, max_new_tokens=30)
+            output = tokenizer.decode(outputs[0], skip_special_tokens=False)
+            st.session_state.past.append(user_input)  
+            st.session_state.generated.append(output)
+            print(output)
+            status.update(label="Result Generated!", state="complete", expanded=False)
+
+    download_str = []
+    # Display the conversation history using an expander, and allow the user to download it
+    with st.expander("Conversation", expanded=True):
+        for i in range(len(st.session_state['generated'])-1, -1, -1):
+            st.info(st.session_state["past"][i],icon="🧐")
+            st.success(st.session_state["generated"][i], icon="🤖")
+            download_str.append(st.session_state["past"][i])
+            download_str.append(st.session_state["generated"][i]) 
+
+        # Can throw error - requires fix
+        download_str = '\n'.join(download_str)
+        if download_str:
+            st.download_button('Download',download_str)
+
+    # Display stored conversation sessions in the sidebar
+    for i, sublist in enumerate(st.session_state.stored_session):
+            with st.sidebar.expander(label= f"Conversation-Session:{i}"):
+                st.write(sublist)
+
+    # Allow the user to clear all stored conversation sessions
+    if st.session_state.stored_session:   
+        if st.sidebar.button("Clear-all"):
+            del st.session_state.stored_session 

model_functions.py

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+from transformers import AutoModelForCausalLM,AutoTokenizer
+import streamlit as st
+
+@st.cache_resource(show_spinner='Loading the Gemma model. Be patient🙏')
+def LOAD_GEMMA():
+  model_id = "aryachakraborty/GEMMA-2B-NL-SQL"
+  tokenizer = AutoTokenizer.from_pretrained(model_id)
+  model = AutoModelForCausalLM.from_pretrained(model_id,
+                                               low_cpu_mem_usage = True
+                                                ).cpu()
+  return tokenizer,model
+
+
+def LOAD_MISTRAL():
+  model_id=''
+  tokenizer = AutoTokenizer.from_pretrained(model_id)
+  model = AutoModelForCausalLM.from_pretrained(model_id,
+                                               low_cpu_usage=True,
+                                               ).cpu()

requirements.txt

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+bitsandbytes==0.42.0
+peft==0.8.2
+trl==0.7.10
+accelerate==0.27.1
+datasets==2.17.0
+transformers==4.38.0
+streamlit
+streamlit_option_menu
+torch
+mysql.connector
+pandas