Skip to main content

Helper functions to generate OpenAI GPT function calling requests.

Project description

OpenAI Function Calling

GitHub Actions Build Status PyPi Package Version

Helper functions to generate JSON schema dicts for OpenAI ChatGPT function calling requests. See the official Function Calling reference for more information.

Installation

Install from PyPi with:

pip install openai-function-calling

The openai-function-calling package does come with the openai package. It must be installed separately with pip install openai

Usage

Auto-Infer the Function Definition (Beta)

Automatically infer your function name, description, and parameters given a reference to the function. A Function instance is returned which can be converted to JSON schema with .to_json_schema() and then passed to the OpenAI chat completion API:

from typing import Any, Callable
from openai_function_calling import FunctionInferrer
import openai
import json

# Define example functions.

def get_current_weather(location: str, unit: str = "fahrenheit") -> str:
    """Get the current weather and return a summary."""
    return f"It is currently sunny in {location} and 75 degrees {unit}."


def get_tomorrows_weather(location: str, unit: str = "fahrenheit") -> str:
    """Get the weather for tomorrow and return a summary."""
    return f"Tomorrow it will be rainy in {location} and 60 degrees {unit}."

# Infer the function definitions.
get_current_weather_function = FunctionInferrer.infer_from_function_reference(
    get_current_weather
)

get_tomorrows_weather_function = FunctionInferrer.infer_from_function_reference(
    get_tomorrows_weather
)

# Get the function to call from ChatGPT (you would normally have more than one).
response = openai.ChatCompletion.create(
    model="gpt-3.5-turbo-0613",
    messages=[
        {
            "role": "user",
            "content": "What will the weather be like in Boston, MA today?",
        }
    ],
    functions=[
        # Convert the functions to JSON schema.
        get_current_weather_function.to_json_schema(),
        get_tomorrows_weather_function.to_json_schema(),
    ],
)

Define Functions with Objects

Define your function definitions using typed classes Function and Parameter which automatically convert to JSON schema with .to_json_schema methods. See an example below:

from openai_function_calling import Function, FunctionDict, Parameter, JsonSchemaType


def get_current_weather(location: str, unit: str) -> str:
    """Do some stuff in here."""


# Define the function.
get_current_weather_function = Function(
    "get_current_weather",
    "Get the current weather",
    [
        Parameter(
            name="location",
            type=JsonSchemaType.STRING,
            description="The city and state, e.g. San Francisco, CA",
        ),
        Parameter(
            name="unit",
            type=JsonSchemaType.STRING,
            description="The temperature unit to use.",
            enum=["celsius", "fahrenheit"],
        ),
    ],
)

# Convert to a JSON schema dict to send to OpenAI.
get_current_weather_function_schema = get_current_weather_function.to_json_schema()

Convert Functions to OpenAI Compatible JSON

from openai import OpenAI
from openai.types.chat import (
    ChatCompletion,
    ChatCompletionUserMessageParam,
)
from openai_function_calling.tool_helpers import ToolHelpers


# Define our functions.
def get_current_weather(location: str, unit: str) -> str:
    """Get the current weather and return a summary."""
    return f"It is currently sunny in {location} and 75 degrees {unit}."


def get_tomorrows_weather(location: str, unit: str) -> str:
    """Get tomorrow's weather and return a summary."""
    return f"It will be rainy tomorrow in {location} and around 65 degrees {unit}."


openai_client = OpenAI()

# Send the query and our function context to OpenAI.
response: ChatCompletion = openai_client.chat.completions.create(
    model="gpt-3.5-turbo-1106",
    messages=[
        ChatCompletionUserMessageParam(
            role="user", content="What's the weather in Boston MA?"
        ),
    ],
    tools=ToolHelpers.infer_from_function_refs(
        [get_current_weather, get_tomorrows_weather]
    ),
    tool_choice="auto",
)

Examples

To run the examples, set the environment variable OPENAI_API_KEY to your OpenAI API key. For example:

export OPENAI_API_KEY=SOME_KEY_VALUE

# or when running an example

OPENAI_API_KEY=SOME_KEY_VALUE python examples/weather_functions.py

Make sure to also follow all instructions in the Installation section.

See complete examples in the ./examples folder.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

openai_function_calling-2.2.0.tar.gz (8.6 kB view details)

Uploaded Source

Built Distribution

openai_function_calling-2.2.0-py3-none-any.whl (10.0 kB view details)

Uploaded Python 3

File details

Details for the file openai_function_calling-2.2.0.tar.gz.

File metadata

File hashes

Hashes for openai_function_calling-2.2.0.tar.gz
Algorithm Hash digest
SHA256 dd4a79499d44ce67181b9d7ea2cce01871877d8ad39a24bff099c3bca167363c
MD5 3420d1c2c1f4a77406c109309dfdcca0
BLAKE2b-256 d2e6a5b30169838e7e4925e91a99e936b3f0d962c058ec203285665ea90c36dc

See more details on using hashes here.

File details

Details for the file openai_function_calling-2.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for openai_function_calling-2.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 7c15e5325a0ba4c0bcdd23fa3aa7954e69c11b8a4424493e3b1f05d88d01e846
MD5 25b3f9c07caa27bef69a30db5d698cf3
BLAKE2b-256 384810b84329b76b45ad8fcbc3f6ecc2075d0275bdc97cfbf737894dc466541f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page