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182 lines
No EOL
8 KiB
Python
182 lines
No EOL
8 KiB
Python
import sys, os
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import os, io
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# this file is to test litellm/proxy
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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 pytest
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import litellm
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from litellm import embedding, completion, completion_cost, Timeout
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from litellm import RateLimitError
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import importlib, inspect
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# test /chat/completion request to the proxy
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from fastapi.testclient import TestClient
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from fastapi import FastAPI
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from litellm.proxy.proxy_server import router, save_worker_config, initialize # Replace with the actual module where your FastAPI router is defined
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filepath = os.path.dirname(os.path.abspath(__file__))
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config_fp = f"{filepath}/test_configs/test_custom_logger.yaml"
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python_file_path = f"{filepath}/test_configs/custom_callbacks.py"
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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)
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app = FastAPI()
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app.include_router(router) # Include your router in the test app
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@app.on_event("startup")
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async def wrapper_startup_event():
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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)
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# Here you create a fixture that will be used by your tests
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# Make sure the fixture returns TestClient(app)
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@pytest.fixture(autouse=True)
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def client():
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with TestClient(app) as client:
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yield client
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# Your bearer token
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token = os.getenv("PROXY_MASTER_KEY")
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headers = {
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"Authorization": f"Bearer {token}"
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}
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def test_chat_completion(client):
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try:
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# Your test data
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print("initialized proxy")
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# import the initialized custom logger
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print(litellm.callbacks)
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assert len(litellm.callbacks) == 1 # assert litellm is initialized with 1 callback
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my_custom_logger = litellm.callbacks[0]
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assert my_custom_logger.async_success == False
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test_data = {
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"model": "Azure OpenAI GPT-4 Canada",
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"messages": [
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{
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"role": "user",
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"content": "hi"
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},
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],
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"max_tokens": 10,
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}
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response = client.post("/chat/completions", json=test_data, headers=headers)
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print("made request", response.status_code, response.text)
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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
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assert my_custom_logger.async_completion_kwargs["model"] == "chatgpt-v-2" # checks if kwargs passed to async_log_success_event are correct
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print("\n\n Custom Logger Async Completion args", my_custom_logger.async_completion_kwargs)
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litellm_params = my_custom_logger.async_completion_kwargs.get("litellm_params")
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config_model_info = litellm_params.get("model_info")
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proxy_server_request_object = litellm_params.get("proxy_server_request")
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assert config_model_info == {'mode': 'chat', 'input_cost_per_token': 0.0002}
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assert proxy_server_request_object == {'url': 'http://testserver/chat/completions', 'method': 'POST', 'headers': {'host': 'testserver', 'accept': '*/*', 'accept-encoding': 'gzip, deflate', 'connection': 'keep-alive', 'user-agent': 'testclient', 'authorization': 'Bearer None', 'content-length': '105', 'content-type': 'application/json'}, 'body': {'model': 'Azure OpenAI GPT-4 Canada', 'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 10}}
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result = response.json()
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print(f"Received response: {result}")
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print("\nPassed /chat/completions with Custom Logger!")
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except Exception as e:
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pytest.fail("LiteLLM Proxy test failed. Exception", e)
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def test_chat_completion_stream(client):
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try:
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# Your test data
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import json
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print("initialized proxy")
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# import the initialized custom logger
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print(litellm.callbacks)
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assert len(litellm.callbacks) == 1 # assert litellm is initialized with 1 callback
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my_custom_logger = litellm.callbacks[0]
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assert my_custom_logger.streaming_response_obj == None # no streaming response obj is set pre call
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test_data = {
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"model": "Azure OpenAI GPT-4 Canada",
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"messages": [
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{
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"role": "user",
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"content": "write 1 line poem about LiteLLM"
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},
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],
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"max_tokens": 40,
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"stream": True # streaming call
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}
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response = client.post("/chat/completions", json=test_data, headers=headers)
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print("made request", response.status_code, response.text)
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complete_response = ""
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for line in response.iter_lines():
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if line:
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# Process the streaming data line here
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print("\n\n Line", line)
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print(line)
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line = str(line)
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json_data = line.replace('data: ', '')
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# Parse the JSON string
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data = json.loads(json_data)
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print("\n\n decode_data", data)
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# Access the content of choices[0]['message']['content']
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content = data['choices'][0]['delta']['content'] or ""
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# Process the content as needed
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print("Content:", content)
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complete_response+= content
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print("\n\nHERE is the complete streaming response string", complete_response)
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print("\n\nHERE IS the streaming Response from callback\n\n")
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print(my_custom_logger.streaming_response_obj)
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streamed_response = my_custom_logger.streaming_response_obj
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assert complete_response == streamed_response["choices"][0]["message"]["content"]
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except Exception as e:
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pytest.fail("LiteLLM Proxy test failed. Exception", e)
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def test_embedding(client):
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try:
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# Your test data
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print("initialized proxy")
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# import the initialized custom logger
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print(litellm.callbacks)
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assert len(litellm.callbacks) == 1 # assert litellm is initialized with 1 callback
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my_custom_logger = litellm.callbacks[0]
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assert my_custom_logger.async_success_embedding == False
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test_data = {
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"model": "azure-embedding-model",
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"input": ["hello"]
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}
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response = client.post("/embeddings", json=test_data, headers=headers)
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print("made request", response.status_code, response.text)
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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
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assert my_custom_logger.async_embedding_kwargs["model"] == "azure-embedding-model" # checks if kwargs passed to async_log_success_event are correct
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kwargs = my_custom_logger.async_embedding_kwargs
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litellm_params = kwargs.get("litellm_params")
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proxy_server_request = litellm_params.get("proxy_server_request")
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model_info = litellm_params.get("model_info")
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assert proxy_server_request == {'url': 'http://testserver/embeddings', 'method': 'POST', 'headers': {'host': 'testserver', 'accept': '*/*', 'accept-encoding': 'gzip, deflate', 'connection': 'keep-alive', 'user-agent': 'testclient', 'authorization': 'Bearer None', 'content-length': '54', 'content-type': 'application/json'}, 'body': {'model': 'azure-embedding-model', 'input': ['hello']}}
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assert model_info == {'input_cost_per_token': 0.002, 'mode': 'embedding'}
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result = response.json()
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print(f"Received response: {result}")
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except Exception as e:
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pytest.fail("LiteLLM Proxy test failed. Exception", e) |