Helper functions to generate JSON schema dicts for OpenAI ChatGPT function calling requests. See the official Function Calling reference for more information.
Install from PyPi with:
pip install openai-function-callingThe openai-function-calling package does come with the openai package. It must be installed separately with pip install openai
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 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()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",
)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.pyMake sure to also follow all instructions in the Installation section.
See complete examples in the ./examples folder.