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Jason Liu
73 lines
2.2 KiB
Markdown
73 lines
2.2 KiB
Markdown
# Welcome to OpenAI Function Call
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We try to provides a powerful and efficient approach to output parsing when interacting with OpenAI's Function Call API. One that is framework agnostic and minimizes any dependencies. It leverages the data validation capabilities of the Pydantic library to handle output parsing in a more structured and reliable manner. If you have any feedback, leave an issue or hit me up on [twitter](https://twitter.com/jxnlco).
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## Installation
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```python
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pip install openai_function_call
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```
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## Usage
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This module simplifies the interaction with the OpenAI API, enabling a more structured outputs. Below are examples showcasing the use of function calls and schemas with OpenAI and Pydantic. In later modoules we'll go over a wide array of more creative uses.
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### Example 1: Function Calls
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```python
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import openai
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from openai_function_call import openai_function
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@openai_function
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def sum(a:int, b:int) -> int:
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"""Sum description adds a + b"""
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return a + b
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completion = openai.ChatCompletion.create(
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model="gpt-3.5-turbo-0613",
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temperature=0,
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functions=[sum.openai_schema],
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function_call={"name": sum.openai_schema["name"]},
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messages=[
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{
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"role": "system",
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"content": "You must use the `sum` function instead of adding yourself.",
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},
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{
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"role": "user",
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"content": "What is 6+3",
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},
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],
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)
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result = sum.from_response(completion)
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print(result) # 9
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```
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### Example 2: Schema Extraction
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```python
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import openai
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from openai_function_call import OpenAISchema
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from pydantic import Field
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class UserDetails(OpenAISchema):
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"""Details of a user"""
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name: str = Field(..., description="users's full name")
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age: int
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completion = openai.ChatCompletion.create(
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model="gpt-3.5-turbo-0613",
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functions=[UserDetails.openai_schema],
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function_call={"name": UserDetails.openai_schema["name"]},
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messages=[
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{"role": "system", "content": "Extract user details from my requests"},
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{"role": "user", "content": "My name is John Doe and I'm 30 years old."},
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],
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)
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user_details = UserDetails.from_response(completion)
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print(user_details) # name="John Doe", age=30
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```
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