litellm/proxy/tests/bursty_load_test_completion.py

import time, asyncio
from openai import AsyncOpenAI
import uuid
import traceback


litellm_client = AsyncOpenAI(api_key="test", base_url="http://0.0.0.0:8000")


async def litellm_completion():
    # Your existing code for litellm_completion goes here
    try:
        response = await litellm_client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "user", "content": f"This is a test: {uuid.uuid4()}" * 180}
            ],  # this is about 4k tokens per request
        )
        return response

    except Exception as e:
        # If there's an exception, log the error message
        with open("error_log.txt", "a") as error_log:
            error_log.write(f"Error during completion: {str(e)}\n")
        pass


async def main():
    start = time.time()
    n = 60  # Send 60 concurrent requests, each with 4k tokens = 240k Tokens
    tasks = [litellm_completion() for _ in range(n)]

    chat_completions = await asyncio.gather(*tasks)

    successful_completions = [c for c in chat_completions if c is not None]

    # Write errors to error_log.txt
    with open("error_log.txt", "a") as error_log:
        for completion in chat_completions:
            if isinstance(completion, str):
                error_log.write(completion + "\n")

    print(n, time.time() - start, len(successful_completions))


if __name__ == "__main__":
    # Blank out contents of error_log.txt
    open("error_log.txt", "w").close()

    asyncio.run(main())