# OpenAI functions
The `openai-functions` Python project simplifies the usage of OpenAI's ChatGPT [function calling](https://platform.openai.com/docs/guides/gpt/function-calling) feature. It abstracts away the complexity of parsing function signatures and docstrings by providing developers with a clean and intuitive interface.
 [](https://coveralls.io/github/rizerphe/openai-functions?branch=main) [](https://opensource.org/licenses/MIT) [](https://badge.fury.io/py/openai-functions) [](https://openai-functions.readthedocs.io/en/latest/?badge=latest)
## Installation
You can install `openai-functions` from PyPI using pip:
```
pip install openai-functions
```
## Usage
1. Import the necessary modules and provide your API key:
```python
import enum
import openai
from openai_functions import Conversation
openai.api_key = "<YOUR_API_KEY>"
```
2. Create a `Conversation` instance:
```python
conversation = Conversation()
```
3. Define your functions using the `@conversation.add_function` decorator:
```python
class Unit(enum.Enum):
FAHRENHEIT = "fahrenheit"
CELSIUS = "celsius"
@conversation.add_function()
def get_current_weather(location: str, unit: Unit = Unit.FAHRENHEIT) -> dict:
"""Get the current weather in a given location.
Args:
location (str): The city and state, e.g., San Francisco, CA
unit (Unit): The unit to use, e.g., fahrenheit or celsius
"""
return {
"location": location,
"temperature": "72",
"unit": unit.value,
"forecast": ["sunny", "windy"],
}
```
4. Ask the AI a question:
```python
response = conversation.ask("What's the weather in San Francisco?")
# Should return something like:
# The current weather in San Francisco is 72 degrees Fahrenheit and it is sunny and windy.
```
You can read more about how to use `Conversation` [here](https://openai-functions.readthedocs.io/en/latest/conversation.html).
## More barebones use - just schema generation and result parsing:
```python
from openai_functions import FunctionWrapper
wrapper = FunctionWrapper(get_current_weather)
schema = wrapper.schema
result = wrapper({"location": "San Francisco, CA"})
```
Or you could use [skills](https://openai-functions.readthedocs.io/en/latest/skills.html).
## Another use case: data extraction
1. Import the necessary modules and provide your API key:
```python
from dataclasses import dataclass
import openai
from openai_functions import nlp
openai.api_key = "<YOUR_API_KEY>"
```
3. Define your data container using the `@nlp` decorator:
```python
@nlp
@dataclass
class Person:
"""Extract personal info"""
name: str
age: int
```
4. Ask the AI for the extracted data:
```python
person = Person.from_natural_language("I'm Jack and I'm 20 years old.")
```
You can read more about `@nlp` [here](https://openai-functions.readthedocs.io/en/latest/nlp_interface.html).
Note: mypy does not parse class decorators ([#3135](https://github.com/python/mypy/issues/3135)), so you might have trouble getting type checking when using it like this. Consider using something like `nlp(Person).from_natural_language` to get proper type support.
## How it Works
`openai-functions` takes care of the following tasks:
- Parsing the function signatures (with type annotations) and docstrings.
- Sending the conversation and function descriptions to the OpenAI model.
- Deciding whether to call a function based on the model's response.
- Calling the appropriate function with the provided arguments.
- Updating the conversation with the function response.
- Repeating the process until the model generates a user-facing message.
This abstraction allows developers to focus on defining their functions and adding user messages without worrying about the details of function calling.
## Note
Please note that `openai-functions` is an unofficial project not maintained by OpenAI. Use it at your discretion.
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