Function Calling

LiteLLM only supports: OpenAI gpt-4-0613 and gpt-3.5-turbo-0613 for function calling

Quick Start

This is exactly how OpenAI supports function calling for gpt-4-0613 and gpt-3.5-turbo-0613

import os, litellm
from litellm import completion

os.environ['OPENAI_API_KEY'] = ""

messages = [
    {"role": "user", "content": "What is the weather like in Boston?"}
]

# python function that will get executed
def get_current_weather(location):
  if location == "Boston, MA":
    return "The weather is 12F"

# JSON Schema to pass to OpenAI
functions = [
    {
      "name": "get_current_weather",
      "description": "Get the current weather in a given location",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. San Francisco, CA"
          },
          "unit": {
            "type": "string",
            "enum": ["celsius", "fahrenheit"]
          }
        },
        "required": ["location"]
      }
    }
  ]

response = completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
print(response)

litellm.function_to_dict - Convert Functions to dictionary for OpenAI function calling

function_to_dict allows you to pass a function docstring and produce a dictionary usable for OpenAI function calling

Using function_to_dict

1. Define your function get_current_weather
2. Add a docstring to your function get_current_weather
3. Pass the function to litellm.utils.function_to_dict to get the dictionary for OpenAI function calling

# function with docstring
def get_current_weather(location: str, unit: str):
        """Get the current weather in a given location

        Parameters
        ----------
        location : str
            The city and state, e.g. San Francisco, CA
        unit : {'celsius', 'fahrenheit'}
            Temperature unit

        Returns
        -------
        str
            a sentence indicating the weather
        """
        if location == "Boston, MA":
            return "The weather is 12F"

# use litellm.utils.function_to_dict to convert function to dict
function_json = litellm.utils.function_to_dict(get_current_weather)
print(function_json)

Output from function_to_dict

{
    'name': 'get_current_weather', 
    'description': 'Get the current weather in a given location', 
    'parameters': {
        'type': 'object', 
        'properties': {
            'location': {'type': 'string', 'description': 'The city and state, e.g. San Francisco, CA'}, 
            'unit': {'type': 'string', 'description': 'Temperature unit', 'enum': "['fahrenheit', 'celsius']"}
        }, 
        'required': ['location', 'unit']
    }
}

Using function_to_dict with Function calling

import os, litellm
from litellm import completion

os.environ['OPENAI_API_KEY'] = ""

messages = [
    {"role": "user", "content": "What is the weather like in Boston?"}
]

def get_current_weather(location):
  if location == "Boston, MA":
    return "The weather is 12F"

functions = litellm.utils.function_to_dict(get_current_weather)

response = completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
print(response)

Function calling for Non-OpenAI LLMs

For Non OpenAI LLMs - LiteLLM raises an exception if you try using it for function calling

Adding Function to prompt

For Non OpenAI LLMs LiteLLM allows you to add the function to the prompt set: litellm.add_function_to_prompt = True

Usage

import os, litellm
from litellm import completion

# IMPORTANT - Set this to TRUE to add the function to the prompt for Non OpenAI LLMs
litellm.add_function_to_prompt = True # set add_function_to_prompt for Non OpenAI LLMs

os.environ['OPENAI_API_KEY'] = ""

messages = [
    {"role": "user", "content": "What is the weather like in Boston?"}
]

def get_current_weather(location):
  if location == "Boston, MA":
    return "The weather is 12F"

functions = [
    {
      "name": "get_current_weather",
      "description": "Get the current weather in a given location",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. San Francisco, CA"
          },
          "unit": {
            "type": "string",
            "enum": ["celsius", "fahrenheit"]
          }
        },
        "required": ["location"]
      }
    }
  ]

response = completion(model="claude-2", messages=messages, functions=functions)
print(response)