import sys, os import traceback from dotenv import load_dotenv load_dotenv() import os, io # this file is to test litellm/proxy sys.path.insert( 0, os.path.abspath("../..") ) # Adds the parent directory to the system path import pytest import litellm from litellm import embedding, completion, completion_cost, Timeout from litellm import RateLimitError import importlib, inspect # test /chat/completion request to the proxy from fastapi.testclient import TestClient from fastapi import FastAPI from litellm.proxy.proxy_server import router, save_worker_config, initialize # Replace with the actual module where your FastAPI router is defined filepath = os.path.dirname(os.path.abspath(__file__)) config_fp = f"{filepath}/test_configs/test_custom_logger.yaml" python_file_path = f"{filepath}/test_configs/custom_callbacks.py" save_worker_config(config=config_fp, model=None, alias=None, api_base=None, api_version=None, debug=False, temperature=None, max_tokens=None, request_timeout=600, max_budget=None, telemetry=False, drop_params=True, add_function_to_prompt=False, headers=None, save=False, use_queue=False) app = FastAPI() app.include_router(router) # Include your router in the test app @app.on_event("startup") async def wrapper_startup_event(): initialize(config=config_fp, model=None, alias=None, api_base=None, api_version=None, debug=True, temperature=None, max_tokens=None, request_timeout=600, max_budget=None, telemetry=False, drop_params=True, add_function_to_prompt=False, headers=None, save=False, use_queue=False) # Here you create a fixture that will be used by your tests # Make sure the fixture returns TestClient(app) @pytest.fixture(autouse=True) def client(): with TestClient(app) as client: yield client # Your bearer token token = os.getenv("PROXY_MASTER_KEY") headers = { "Authorization": f"Bearer {token}" } def test_chat_completion(client): try: # Your test data print("initialized proxy") # import the initialized custom logger print(litellm.callbacks) assert len(litellm.callbacks) == 1 # assert litellm is initialized with 1 callback my_custom_logger = litellm.callbacks[0] assert my_custom_logger.async_success == False test_data = { "model": "Azure OpenAI GPT-4 Canada", "messages": [ { "role": "user", "content": "hi" }, ], "max_tokens": 10, } response = client.post("/chat/completions", json=test_data, headers=headers) print("made request", response.status_code, response.text) assert my_custom_logger.async_success == True # checks if the status of async_success is True, only the async_log_success_event can set this to true assert my_custom_logger.async_completion_kwargs["model"] == "chatgpt-v-2" # checks if kwargs passed to async_log_success_event are correct result = response.json() print(f"Received response: {result}") except Exception as e: pytest.fail("LiteLLM Proxy test failed. Exception", e) def test_embedding(client): try: # Your test data print("initialized proxy") # import the initialized custom logger print(litellm.callbacks) assert len(litellm.callbacks) == 1 # assert litellm is initialized with 1 callback my_custom_logger = litellm.callbacks[0] assert my_custom_logger.async_success_embedding == False test_data = { "model": "azure-embedding-model", "input": ["hello"] } response = client.post("/embeddings", json=test_data, headers=headers) print("made request", response.status_code, response.text) assert my_custom_logger.async_success_embedding == True # checks if the status of async_success is True, only the async_log_success_event can set this to true assert my_custom_logger.async_embedding_kwargs["model"] == "azure-embedding-model" # checks if kwargs passed to async_log_success_event are correct result = response.json() print(f"Received response: {result}") except Exception as e: pytest.fail("LiteLLM Proxy test failed. Exception", e)