OpenAI

pip install rdk openai --extra-index-url https://pypi.fury.io/021labs/

from openai import OpenAI
from rdk import observe, shutdown

@observe(name="openai-chat")
def chat(message: str) -> str:
    client = OpenAI()
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": message}]
    )
    return response.choices[0].message.content

result = chat("Write a haiku about programming")
print(result)

shutdown()

import asyncio
from openai import AsyncOpenAI
from rdk import observe, shutdown

@observe(name="async-openai")
async def async_chat(message: str) -> str:
    client = AsyncOpenAI()
    response = await client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": message}]
    )
    return response.choices[0].message.content

result = asyncio.run(async_chat("Hello!"))
shutdown()

import json
from openai import OpenAI
from rdk import observe, shutdown

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_stock_price",
            "description": "Get current stock price",
            "parameters": {
                "type": "object",
                "properties": {
                    "symbol": {"type": "string", "description": "Stock symbol"}
                },
                "required": ["symbol"]
            }
        }
    }
]

def get_stock_price(symbol: str) -> str:
    # Mock implementation
    prices = {"AAPL": 150.00, "GOOGL": 140.00, "MSFT": 380.00}
    return json.dumps({"symbol": symbol, "price": prices.get(symbol, 0)})

@observe(name="stock-agent")
def stock_agent(question: str) -> str:
    client = OpenAI()
    messages = [{"role": "user", "content": question}]

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
        tools=tools
    )

    # Handle tool calls
    while response.choices[0].message.tool_calls:
        tool_calls = response.choices[0].message.tool_calls
        messages.append(response.choices[0].message)

        for tc in tool_calls:
            args = json.loads(tc.function.arguments)
            result = get_stock_price(args["symbol"])
            messages.append({
                "role": "tool",
                "tool_call_id": tc.id,
                "content": result
            })

        response = client.chat.completions.create(
            model="gpt-4o",
            messages=messages,
            tools=tools
        )

    return response.choices[0].message.content

result = stock_agent("What's Apple's stock price?")
shutdown()