This is a small utility to generate JSON schemas for python functions. With power of type annotations, it is possible to generate a schema for a function without describing it twice.
At this moment, extracting schema from a function is useful for OpenAI Assistant Toll Calling, OpenAI API function-call, and Anthropic Claude Toll calling feature. And it can be used for other purposes for example to generate documentation in the future.
pip install function-schemafrom typing import Annotated, Optional
import enum
def get_weather(
city: Annotated[str, "The city to get the weather for"],
unit: Annotated[
Optional[str],
"The unit to return the temperature in",
enum.Enum("Unit", "celcius fahrenheit")
] = "celcius",
) -> str:
"""Returns the weather for the given city."""
return f"Weather for {city} is 20°C"Function description is taken from the docstring.
Type hinting with typing.Annotated for annotate additional information about the parameters and return type.
- type can be
typing.Union,typing.Optional. (T | Nonefor python 3.10+) - string value of
Annotatedis used as a description - enum value of
Annotatedis used as an enum schema
import json
from function_schema import get_function_schema
schema = get_function_schema(get_weather)
print(json.dumps(schema, indent=2))Will output:
{
"name": "get_weather",
"description": "Returns the weather for the given city.",
"parameters": {
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "The city to get the weather for"
},
"unit": {
"type": "string",
"description": "The unit to return the temperature in",
"enum": [
"celcius",
"fahrenheit"
],
"default": "celcius"
}
},
}
"required": [
"city"
]
}for claude, you should pass 2nd argument as SchemaFormat.claude or claude:
from function_schema import get_function_schema
schema = get_function_schema(get_weather, "claude")Please refer to the Claude tool use documentation for more information.
You can use this schema to make a function call in OpenAI API:
import openai
openai.api_key = "sk-..."
# Create an assistant with the function
assistant = client.beta.assistants.create(
instructions="You are a weather bot. Use the provided functions to answer questions.",
model="gpt-4-turbo-preview",
tools=[{
"type": "function",
"function": get_function_schema(get_weather),
}]
)
run = client.beta.messages.create(
assistant_id=assistant.id,
messages=[
{"role": "user", "content": "What's the weather like in Seoul?"}
]
)
# or with chat completion
result = openai.chat.completion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": "What's the weather like in Seoul?"}
],
tools=[get_function_schema(get_weather)],
tool_call="auto",
)In claude api,
import anthropic
client = anthropic.Client()
response = client.beta.tools.messages.create(
model="claude-3-opus-20240229",
max_tokens=4096,
tools=[get_function_schema(get_weather, "claude")],
messages=[
{"role": "user", "content": "What's the weather like in Seoul?"}
]
)function_schema mymodule.py my_functionMIT License
