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  tags: []
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  tags: []
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  ---
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+ # Sabiá-3 (Qwen-2) tokenizer v2
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+ This new version improves the chat template by handling custom system prompts and including the new `tool` role.
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+ ## Simple usage
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+ ```python
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+ messages = [
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+ {"role": "system", "content": "Você é um assistante inteligente."},
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+ {"role": "user", "content": "Olá!"},
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+ {"role": "assistant", "content": "Olá! Como posso ajudar você hoje?"},
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+ {"role": "user", "content": "Qual é a capital do Brasil?"},
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+ ]
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+
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+ print(tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True))
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+ ```
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+ Will result in the following string:
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+
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+ ```
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+ Você é um assistante inteligente. USUÁRIO: Olá! ASSISTENTE: Olá! Como posso ajudar você hoje?<|endoftext|>USUÁRIO: Qual é a capital do Brasil? ASSISTENTE:
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+ ```
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+
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+ ## Tools
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+
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+ ```python
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+ messages = [
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+ {"role": "system", "content": """You are a helpful customer support assistant. Use the supplied tools to assist the user.
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+ Uso de funções: Opcional
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+
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+ Lista de funções disponíveis:
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+
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+ <functions>
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+ [{"type": "function", "function": {"name": "get_delivery_date", "description": "Get the delivery date for a customer's order. Call this whenever you need to know the delivery date, for example when a customer asks 'Where is my package'", "parameters": {"type": "object", "properties": {"order_id": {"type": "string", "description": "The customer's order ID."}}, "required": ["order_id"], "additionalProperties": false}}}]
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+ </functions>
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+
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+ Formato esperado de resposta quando houver utilização de funções:
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+ <multiplefunctions>
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+ <functioncall> {"name": "function_name", "arguments": {"arg_1": "value_1", "arg_2": "value_2", ...}} </functioncall>
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+ <functioncall> {"name": "function_name", "arguments": {"arg_1": "value_1", "arg_2": "value_2", ...}} </functioncall>
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+ ...
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+ </multiplefunctions>
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+
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+ Aspectos importantes:
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+ - Chamadas de funções DEVEM seguir o formato especificado
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+ - Parâmetros necessários DEVEM ser especificados"""},
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+ {"role": "user", "content": "Hi, can you tell me the delivery date for my order?"},
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+ {"role": "assistant", "content": "Hi there! I can help with that. Can you please provide your order ID?"},
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+ {"role": "user", "content": "i think it is order_12345"},
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+ {
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+ "role": "assistant",
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+ "tool_calls": [
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+ {
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+ "id": "call_62136354",
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+ "type": "function",
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+ "function": {
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+ "arguments": "{'order_id': 'order_12345'}",
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+ "name": "get_delivery_date"
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+ }
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+ }
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+ ]
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+ },
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+ {
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+ "role": "tool",
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+ "content": json.dumps({
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+ "order_id": "order_12345",
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+ "delivery_date": "00-00-2000"
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+ }),
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+ "tool_call_id": "call_62136354"
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+ }
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+ ]
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+ ```
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+ The resulting string will be:
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+
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+ ```
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+ You are a helpful customer support assistant. Use the supplied tools to assist the user.
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+ Uso de funções: Opcional
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+
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+ Lista de funções disponíveis:
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+
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+ <functions>
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+ [{"type": "function", "function": {"name": "get_delivery_date", "description": "Get the delivery date for a customer's order. Call this whenever you need to know the delivery date, for example when a customer asks 'Where is my package'", "parameters": {"type": "object", "properties": {"order_id": {"type": "string", "description": "The customer's order ID."}}, "required": ["order_id"], "additionalProperties": false}}}]
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+ </functions>
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+
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+ Formato esperado de resposta quando houver utilização de funções:
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+ <multiplefunctions>
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+ <functioncall> {"name": "function_name", "arguments": {"arg_1": "value_1", "arg_2": "value_2", ...}} </functioncall>
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+ <functioncall> {"name": "function_name", "arguments": {"arg_1": "value_1", "arg_2": "value_2", ...}} </functioncall>
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+ ...
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+ </multiplefunctions>
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+
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+ Aspectos importantes:
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+ - Chamadas de funções DEVEM seguir o formato especificado
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+ - Parâmetros necessários DEVEM ser especificados USUÁRIO: Hi, can you tell me the delivery date for my order? ASSISTENTE: Hi there! I can help with that. Can you please provide your order ID?<|endoftext|>USUÁRIO: i think it is order_12345 ASSISTENTE: <multiplefunctions>
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+ <functioncall> {"name": "get_delivery_date", "arguments": {'order_id': 'order_12345'}} </functioncall>
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+ </multiplefunctions><|endoftext|>FUNCTION_RESPONSE: {"order_id": "order_12345", "delivery_date": "00-00-2000"} ASSISTENTE:
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+ ```