import sys, os import traceback from dotenv import load_dotenv import copy load_dotenv() sys.path.insert( 0, os.path.abspath("../..") ) # Adds the parent directory to the system path import asyncio from litellm import Router async def call_acompletion(semaphore, router: Router, input_data): async with semaphore: # Replace 'input_data' with appropriate parameters for acompletion response = await router.acompletion(**input_data) # Handle the response as needed return response async def main(): # Initialize the Router model_list= [{ "model_name": "gpt-3.5-turbo", "litellm_params": { "model": "gpt-3.5-turbo", "api_key": os.getenv("OPENAI_API_KEY"), }, }, { "model_name": "gpt-3.5-turbo", "litellm_params": { "model": "azure/chatgpt-v-2", "api_key": os.getenv("AZURE_API_KEY"), "api_base": os.getenv("AZURE_API_BASE"), "api_version": os.getenv("AZURE_API_VERSION") }, }, { "model_name": "gpt-3.5-turbo", "litellm_params": { "model": "azure/chatgpt-functioncalling", "api_key": os.getenv("AZURE_API_KEY"), "api_base": os.getenv("AZURE_API_BASE"), "api_version": os.getenv("AZURE_API_VERSION") }, }] router = Router(model_list=model_list, num_retries=3) # Create a semaphore with a capacity of 100 semaphore = asyncio.Semaphore(100) # List to hold all task references tasks = [] # Launch 1000 tasks for _ in range(100): task = asyncio.create_task(call_acompletion(semaphore, router, {"model": "gpt-3.5-turbo", "messages": [{"role":"user", "content": "Hey, how's it going?"}]})) tasks.append(task) # Wait for all tasks to complete responses = await asyncio.gather(*tasks) # Process responses as needed print(f"NUMBER OF COMPLETED TASKS: {len(responses)}") # Run the main function asyncio.run(main())