funcOAI 0.0.3

A package that helps users easily create functions to feed to GPT function calling API

FunctionalOAI

FunctionalOAI is a Python module // library designed to help you make the use of the GPT function calling API much easier.

Ideas

If you have any features or ideas that could be added to this project, you could open an issue.

Installation

• Through pip

pip3 install funcOAI

• Through setup.py

python3 setup.py install

Usage

# importing the main class
from functionalOAI import FunAI

client = FunAI()

@client.attach
def my_function(*args, **kwargs):
    # provide gpt with something

# you could also use attachFunctions
client.attachFunctions([my_function, func1, func2])

# or even this cursed one
client.functions = my_function

# to see all functions
print(client.functions)

• After creating you're functions then you could use openai python module to create a chat with chatgpt and you could provide it with client.functions e.g ...

from functionalOAI import FunAI

client = FunAI()

@client.attach
def get_current_weather(location: str, unit: str = "fahrenheit"):
    """Get the current weather in a given location"""
    weather_info = {
        "location": location,
        "temperature": "72",
        "unit": unit,
        "forecast": ["sunny", "windy"],
    }
    return json.dumps(weather_info)

def run_conversation():
    messages = [{"role": "user", "content": "What's the weather like in Boston?"}]

    ## function info
    functions = client.functions

    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo-0613",
        messages=messages,
        functions=functions,
        function_call="auto",
    )
    response_message = response["choices"][0]["message"]

    if response_message.get("function_call"):
        available_functions = {
            "get_current_weather": get_current_weather,
        }
        function_name = response_message["function_call"]["name"]
        fuction_to_call = available_functions[function_name]
        function_args = json.loads(response_message["function_call"]["arguments"])
        function_response = fuction_to_call(
            location=function_args.get("location"),
            unit=function_args.get("unit"),
        )

        messages.append(response_message)
        messages.append(
            {
                "role": "function",
                "name": function_name,
                "content": function_response,
            }
        )

        second_response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo-0613",
            messages=messages,
        )
        return second_response


print(run_conversation())

This is an edited example of the official OpenAI API example

NOTICE!!

To make this module work correctly with all of you're functions there are set of rules you have to go by when defining the functions

• Providing type annotations for all the arguments e.g ...

def foo(arg1: int, arg2: str, arg3: list):

• Providing a docstring that follows PEP-257 One liner docstrings (you could do it as you like as long as its a function desciption without parameters and returns)

def add(x: int, y: int):
    """return the sum of x and y"""
    return x + y

WARNING

• This module is not fully complete as it still lacks some extra functionality
• There is no error handling as for now, so obeying the rules of function defining is necessary

TODO

• create a special type for the functions list, to make it more flexable and accessable, and much more efficient (handeling duplicates etc ...)
• create a multi-line docstring parser that gets a description for the function and a description for each of the arguments
• handle all possible errors in creating the body of the function, and create backup plans in case something was missing in the function definition

Contribute

You could contribute through

• Opening issues
• Forking the repo
• Creating Pull requests
• etc...