mirror of
https://github.com/BerriAI/litellm.git
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69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
import sys, os
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import traceback
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from dotenv import load_dotenv
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import copy
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load_dotenv()
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import asyncio
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from litellm import Router, Timeout
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async def call_acompletion(semaphore, router: Router, input_data):
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async with semaphore:
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try:
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# Use asyncio.wait_for to set a timeout for the task
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response = await router.acompletion(**input_data)
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# Handle the response as needed
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return response
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except Timeout:
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print(f"Task timed out: {input_data}")
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return None # You may choose to return something else or raise an exception
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async def main():
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# Initialize the Router
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model_list= [{
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "gpt-3.5-turbo",
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"api_key": os.getenv("OPENAI_API_KEY"),
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},
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}, {
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "azure/chatgpt-v-2",
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"api_key": os.getenv("AZURE_API_KEY"),
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"api_base": os.getenv("AZURE_API_BASE"),
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"api_version": os.getenv("AZURE_API_VERSION")
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},
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}, {
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "azure/chatgpt-functioncalling",
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"api_key": os.getenv("AZURE_API_KEY"),
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"api_base": os.getenv("AZURE_API_BASE"),
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"api_version": os.getenv("AZURE_API_VERSION")
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},
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}]
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router = Router(model_list=model_list, num_retries=3, timeout=10)
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# Create a semaphore with a capacity of 100
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semaphore = asyncio.Semaphore(100)
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# List to hold all task references
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tasks = []
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# Launch 1000 tasks
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for _ in range(1000):
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task = asyncio.create_task(call_acompletion(semaphore, router, {"model": "gpt-3.5-turbo", "messages": [{"role":"user", "content": "Hey, how's it going?"}]}))
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tasks.append(task)
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# Wait for all tasks to complete
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responses = await asyncio.gather(*tasks)
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# Process responses as needed
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print(f"NUMBER OF COMPLETED TASKS: {len(responses)}")
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# Run the main function
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asyncio.run(main())
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