openai_tools_stream.py

import json

from rich import print

from log10.load import OpenAI


client = OpenAI()


# Example dummy function hard coded to return the same weather
# In production, this could be your backend API or an external API
def get_current_weather(location, unit="fahrenheit"):
    """Get the current weather in a given location"""
    if "tokyo" in location.lower():
        return json.dumps({"location": "Tokyo", "temperature": "10", "unit": unit})
    elif "san francisco" in location.lower():
        return json.dumps({"location": "San Francisco", "temperature": "72", "unit": unit})
    elif "paris" in location.lower():
        return json.dumps({"location": "Paris", "temperature": "22", "unit": unit})
    else:
        return json.dumps({"location": location, "temperature": "unknown"})


def run_conversation():
    # Step 1: send the conversation and available functions to the model
    messages = [
        {
            "role": "user",
            "content": "What's the weather like in San Francisco, Tokyo, and Paris?",
        }
    ]
    tools = [
        {
            "type": "function",
            "function": {
                "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 = client.chat.completions.create(
        model="gpt-3.5-turbo-0125",
        messages=messages,
        tools=tools,
        tool_choice="auto",  # auto is default, but we'll be explicit
        stream=True,
    )
    tool_calls = []
    for chunk in response:
        if chunk.choices[0].delta:
            if tc := chunk.choices[0].delta.tool_calls:
                if tc[0].id:
                    tool_calls.append(tc[0])
                else:
                    tool_calls[-1].function.arguments += tc[0].function.arguments
    print([{"function": t.function.name, "arguments": t.function.arguments} for t in tool_calls])
    return


print(run_conversation())