mirror of
https://github.com/BerriAI/litellm.git
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1ea046cc61
* test: update tests to new deployment model * test: update model name * test: skip cohere rbac issue test * test: update test - replace gpt-4o model
704 lines
25 KiB
Python
704 lines
25 KiB
Python
# # this tests if the router is initialized correctly
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# import asyncio
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# import os
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# import sys
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# import time
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# import traceback
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# import pytest
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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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# from collections import defaultdict
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# from concurrent.futures import ThreadPoolExecutor
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# from dotenv import load_dotenv
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# import litellm
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# from litellm import Router
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# load_dotenv()
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# # every time we load the router we should have 4 clients:
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# # Async
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# # Sync
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# # Async + Stream
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# # Sync + Stream
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# def test_init_clients():
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# litellm.set_verbose = True
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# import logging
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# from litellm._logging import verbose_router_logger
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# verbose_router_logger.setLevel(logging.DEBUG)
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# try:
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# print("testing init 4 clients with diff timeouts")
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# model_list = [
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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-3",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": os.getenv("AZURE_API_BASE"),
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# "timeout": 0.01,
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# "stream_timeout": 0.000_001,
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# "max_retries": 7,
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# },
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# },
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# ]
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# router = Router(model_list=model_list, set_verbose=True)
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# for elem in router.model_list:
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# model_id = elem["model_info"]["id"]
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# assert router.cache.get_cache(f"{model_id}_client") is not None
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# assert router.cache.get_cache(f"{model_id}_async_client") is not None
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# assert router.cache.get_cache(f"{model_id}_stream_client") is not None
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# assert router.cache.get_cache(f"{model_id}_stream_async_client") is not None
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# # check if timeout for stream/non stream clients is set correctly
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# async_client = router.cache.get_cache(f"{model_id}_async_client")
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# stream_async_client = router.cache.get_cache(
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# f"{model_id}_stream_async_client"
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# )
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# assert async_client.timeout == 0.01
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# assert stream_async_client.timeout == 0.000_001
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# print(vars(async_client))
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# print()
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# print(async_client._base_url)
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# assert (
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# async_client._base_url
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# == "https://openai-gpt-4-test-v-1.openai.azure.com/openai/"
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# )
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# assert (
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# stream_async_client._base_url
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# == "https://openai-gpt-4-test-v-1.openai.azure.com/openai/"
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# )
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# print("PASSED !")
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# except Exception as e:
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# traceback.print_exc()
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# pytest.fail(f"Error occurred: {e}")
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# # test_init_clients()
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# def test_init_clients_basic():
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# litellm.set_verbose = True
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# try:
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# print("Test basic client init")
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# model_list = [
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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-3",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": os.getenv("AZURE_API_BASE"),
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# },
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# },
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# ]
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# router = Router(model_list=model_list)
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# for elem in router.model_list:
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# model_id = elem["model_info"]["id"]
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# assert router.cache.get_cache(f"{model_id}_client") is not None
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# assert router.cache.get_cache(f"{model_id}_async_client") is not None
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# assert router.cache.get_cache(f"{model_id}_stream_client") is not None
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# assert router.cache.get_cache(f"{model_id}_stream_async_client") is not None
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# print("PASSED !")
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# # see if we can init clients without timeout or max retries set
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# except Exception as e:
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# traceback.print_exc()
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# pytest.fail(f"Error occurred: {e}")
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# # test_init_clients_basic()
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# def test_init_clients_basic_azure_cloudflare():
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# # init azure + cloudflare
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# # init OpenAI gpt-3.5
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# # init OpenAI text-embedding
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# # init OpenAI comptaible - Mistral/mistral-medium
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# # init OpenAI compatible - xinference/bge
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# litellm.set_verbose = True
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# try:
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# print("Test basic client init")
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# model_list = [
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# {
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# "model_name": "azure-cloudflare",
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# "litellm_params": {
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# "model": "azure/chatgpt-v-3",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": "https://gateway.ai.cloudflare.com/v1/0399b10e77ac6668c80404a5ff49eb37/litellm-test/azure-openai/openai-gpt-4-test-v-1",
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# },
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# },
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# {
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# "model_name": "gpt-openai",
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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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# {
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# "model_name": "text-embedding-ada-002",
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# "litellm_params": {
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# "model": "text-embedding-ada-002",
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# "api_key": os.getenv("OPENAI_API_KEY"),
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# },
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# },
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# {
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# "model_name": "mistral",
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# "litellm_params": {
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# "model": "mistral/mistral-tiny",
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# "api_key": os.getenv("MISTRAL_API_KEY"),
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# },
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# },
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# {
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# "model_name": "bge-base-en",
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# "litellm_params": {
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# "model": "xinference/bge-base-en",
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# "api_base": "http://127.0.0.1:9997/v1",
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# "api_key": os.getenv("OPENAI_API_KEY"),
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# },
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# },
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# ]
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# router = Router(model_list=model_list)
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# for elem in router.model_list:
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# model_id = elem["model_info"]["id"]
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# assert router.cache.get_cache(f"{model_id}_client") is not None
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# assert router.cache.get_cache(f"{model_id}_async_client") is not None
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# assert router.cache.get_cache(f"{model_id}_stream_client") is not None
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# assert router.cache.get_cache(f"{model_id}_stream_async_client") is not None
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# print("PASSED !")
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# # see if we can init clients without timeout or max retries set
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# except Exception as e:
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# traceback.print_exc()
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# pytest.fail(f"Error occurred: {e}")
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# # test_init_clients_basic_azure_cloudflare()
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# def test_timeouts_router():
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# """
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# Test the timeouts of the router with multiple clients. This HASas to raise a timeout error
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# """
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# import openai
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# litellm.set_verbose = True
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# try:
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# print("testing init 4 clients with diff timeouts")
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# model_list = [
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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-3",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": os.getenv("AZURE_API_BASE"),
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# "timeout": 0.000001,
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# "stream_timeout": 0.000_001,
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# },
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# },
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# ]
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# router = Router(model_list=model_list, num_retries=0)
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# print("PASSED !")
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# async def test():
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# try:
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# await router.acompletion(
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# model="gpt-3.5-turbo",
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# messages=[
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# {"role": "user", "content": "hello, write a 20 pg essay"}
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# ],
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# )
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# except Exception as e:
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# raise e
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# asyncio.run(test())
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# except openai.APITimeoutError as e:
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# print(
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# "Passed: Raised correct exception. Got openai.APITimeoutError\nGood Job", e
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# )
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# print(type(e))
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# pass
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# except Exception as e:
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# pytest.fail(
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# f"Did not raise error `openai.APITimeoutError`. Instead raised error type: {type(e)}, Error: {e}"
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# )
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# # test_timeouts_router()
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# def test_stream_timeouts_router():
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# """
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# Test the stream timeouts router. See if it selected the correct client with stream timeout
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# """
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# import openai
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# litellm.set_verbose = True
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# try:
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# print("testing init 4 clients with diff timeouts")
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# model_list = [
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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-3",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "api_version": os.getenv("AZURE_API_VERSION"),
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# "api_base": os.getenv("AZURE_API_BASE"),
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# "timeout": 200, # regular calls will not timeout, stream calls will
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# "stream_timeout": 10,
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# },
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# },
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# ]
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# router = Router(model_list=model_list)
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# print("PASSED !")
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# data = {
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# "model": "gpt-3.5-turbo",
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# "messages": [{"role": "user", "content": "hello, write a 20 pg essay"}],
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# "stream": True,
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# }
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# selected_client = router._get_client(
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# deployment=router.model_list[0],
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# kwargs=data,
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# client_type=None,
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# )
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# print("Select client timeout", selected_client.timeout)
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# assert selected_client.timeout == 10
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# # make actual call
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# response = router.completion(**data)
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# for chunk in response:
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# print(f"chunk: {chunk}")
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# except openai.APITimeoutError as e:
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# print(
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# "Passed: Raised correct exception. Got openai.APITimeoutError\nGood Job", e
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# )
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# print(type(e))
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# pass
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# except Exception as e:
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# pytest.fail(
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# f"Did not raise error `openai.APITimeoutError`. Instead raised error type: {type(e)}, Error: {e}"
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# )
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# # test_stream_timeouts_router()
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# def test_xinference_embedding():
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# # [Test Init Xinference] this tests if we init xinference on the router correctly
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# # [Test Exception Mapping] tests that xinference is an openai comptiable provider
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# print("Testing init xinference")
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# print(
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# "this tests if we create an OpenAI client for Xinference, with the correct API BASE"
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# )
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# model_list = [
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# {
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# "model_name": "xinference",
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# "litellm_params": {
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# "model": "xinference/bge-base-en",
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# "api_base": "os.environ/XINFERENCE_API_BASE",
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# },
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# }
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# ]
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# router = Router(model_list=model_list)
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# print(router.model_list)
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# print(router.model_list[0])
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# assert (
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# router.model_list[0]["litellm_params"]["api_base"] == "http://0.0.0.0:9997"
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# ) # set in env
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# openai_client = router._get_client(
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# deployment=router.model_list[0],
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# kwargs={"input": ["hello"], "model": "xinference"},
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# )
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# assert openai_client._base_url == "http://0.0.0.0:9997"
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# assert "xinference" in litellm.openai_compatible_providers
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# print("passed")
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# # test_xinference_embedding()
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# def test_router_init_gpt_4_vision_enhancements():
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# try:
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# # tests base_url set when any base_url with /openai/deployments passed to router
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# print("Testing Azure GPT_Vision enhancements")
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# model_list = [
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# {
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# "model_name": "gpt-4-vision-enhancements",
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# "litellm_params": {
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# "model": "azure/gpt-4-vision",
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# "api_key": os.getenv("AZURE_API_KEY"),
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# "base_url": "https://gpt-4-vision-resource.openai.azure.com/openai/deployments/gpt-4-vision/extensions/",
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# "dataSources": [
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# {
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# "type": "AzureComputerVision",
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# "parameters": {
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# "endpoint": "os.environ/AZURE_VISION_ENHANCE_ENDPOINT",
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# "key": "os.environ/AZURE_VISION_ENHANCE_KEY",
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# },
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# }
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# ],
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# },
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# }
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# ]
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# router = Router(model_list=model_list)
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# print(router.model_list)
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# print(router.model_list[0])
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# assert (
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# router.model_list[0]["litellm_params"]["base_url"]
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# == "https://gpt-4-vision-resource.openai.azure.com/openai/deployments/gpt-4-vision/extensions/"
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# ) # set in env
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# assert (
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# router.model_list[0]["litellm_params"]["dataSources"][0]["parameters"][
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# "endpoint"
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# ]
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# == os.environ["AZURE_VISION_ENHANCE_ENDPOINT"]
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# )
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# assert (
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# router.model_list[0]["litellm_params"]["dataSources"][0]["parameters"][
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# "key"
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# ]
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# == os.environ["AZURE_VISION_ENHANCE_KEY"]
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# )
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# azure_client = router._get_client(
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# deployment=router.model_list[0],
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# kwargs={"stream": True, "model": "gpt-4-vision-enhancements"},
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# client_type="async",
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# )
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# assert (
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# azure_client._base_url
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# == "https://gpt-4-vision-resource.openai.azure.com/openai/deployments/gpt-4-vision/extensions/"
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# )
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# print("passed")
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# @pytest.mark.parametrize("sync_mode", [True, False])
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# @pytest.mark.asyncio
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# async def test_openai_with_organization(sync_mode):
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# try:
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# print("Testing OpenAI with organization")
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# model_list = [
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# {
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# "model_name": "openai-bad-org",
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# "litellm_params": {
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# "model": "gpt-3.5-turbo",
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# "organization": "org-ikDc4ex8NB",
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# },
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# },
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# {
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# "model_name": "openai-good-org",
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# "litellm_params": {"model": "gpt-3.5-turbo"},
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# },
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# ]
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# router = Router(model_list=model_list)
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# print(router.model_list)
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# print(router.model_list[0])
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# if sync_mode:
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# openai_client = router._get_client(
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# deployment=router.model_list[0],
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# kwargs={"input": ["hello"], "model": "openai-bad-org"},
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# )
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# print(vars(openai_client))
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# assert openai_client.organization == "org-ikDc4ex8NB"
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# # bad org raises error
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# try:
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# response = router.completion(
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# model="openai-bad-org",
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# messages=[{"role": "user", "content": "this is a test"}],
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# )
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# pytest.fail(
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# "Request should have failed - This organization does not exist"
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# )
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# except Exception as e:
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# print("Got exception: " + str(e))
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# assert "header should match organization for API key" in str(
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# e
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# ) or "No such organization" in str(e)
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# # good org works
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# response = router.completion(
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# model="openai-good-org",
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# messages=[{"role": "user", "content": "this is a test"}],
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# max_tokens=5,
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# )
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# else:
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# openai_client = router._get_client(
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# deployment=router.model_list[0],
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# kwargs={"input": ["hello"], "model": "openai-bad-org"},
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# client_type="async",
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# )
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# print(vars(openai_client))
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# assert openai_client.organization == "org-ikDc4ex8NB"
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# # bad org raises error
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# try:
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# response = await router.acompletion(
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# model="openai-bad-org",
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# messages=[{"role": "user", "content": "this is a test"}],
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# )
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# pytest.fail(
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# "Request should have failed - This organization does not exist"
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# )
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# except Exception as e:
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# print("Got exception: " + str(e))
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# assert "header should match organization for API key" in str(
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# e
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# ) or "No such organization" in str(e)
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# # good org works
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# response = await router.acompletion(
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# model="openai-good-org",
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# messages=[{"role": "user", "content": "this is a test"}],
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# max_tokens=5,
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|
# )
|
|
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
# def test_init_clients_azure_command_r_plus():
|
|
# # This tests that the router uses the OpenAI client for Azure/Command-R+
|
|
# # For azure/command-r-plus we need to use openai.OpenAI because of how the Azure provider requires requests being sent
|
|
# litellm.set_verbose = True
|
|
# import logging
|
|
|
|
# from litellm._logging import verbose_router_logger
|
|
|
|
# verbose_router_logger.setLevel(logging.DEBUG)
|
|
# try:
|
|
# print("testing init 4 clients with diff timeouts")
|
|
# model_list = [
|
|
# {
|
|
# "model_name": "gpt-3.5-turbo",
|
|
# "litellm_params": {
|
|
# "model": "azure/command-r-plus",
|
|
# "api_key": os.getenv("AZURE_COHERE_API_KEY"),
|
|
# "api_base": os.getenv("AZURE_COHERE_API_BASE"),
|
|
# "timeout": 0.01,
|
|
# "stream_timeout": 0.000_001,
|
|
# "max_retries": 7,
|
|
# },
|
|
# },
|
|
# ]
|
|
# router = Router(model_list=model_list, set_verbose=True)
|
|
# for elem in router.model_list:
|
|
# model_id = elem["model_info"]["id"]
|
|
# async_client = router.cache.get_cache(f"{model_id}_async_client")
|
|
# stream_async_client = router.cache.get_cache(
|
|
# f"{model_id}_stream_async_client"
|
|
# )
|
|
# # Assert the Async Clients used are OpenAI clients and not Azure
|
|
# # For using Azure/Command-R-Plus and Azure/Mistral the clients NEED to be OpenAI clients used
|
|
# # this is weirdness introduced on Azure's side
|
|
|
|
# assert "openai.AsyncOpenAI" in str(async_client)
|
|
# assert "openai.AsyncOpenAI" in str(stream_async_client)
|
|
# print("PASSED !")
|
|
|
|
# except Exception as e:
|
|
# traceback.print_exc()
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
# @pytest.mark.asyncio
|
|
# async def test_aaaaatext_completion_with_organization():
|
|
# try:
|
|
# print("Testing Text OpenAI with organization")
|
|
# model_list = [
|
|
# {
|
|
# "model_name": "openai-bad-org",
|
|
# "litellm_params": {
|
|
# "model": "text-completion-openai/gpt-3.5-turbo-instruct",
|
|
# "api_key": os.getenv("OPENAI_API_KEY", None),
|
|
# "organization": "org-ikDc4ex8NB",
|
|
# },
|
|
# },
|
|
# {
|
|
# "model_name": "openai-good-org",
|
|
# "litellm_params": {
|
|
# "model": "text-completion-openai/gpt-3.5-turbo-instruct",
|
|
# "api_key": os.getenv("OPENAI_API_KEY", None),
|
|
# "organization": os.getenv("OPENAI_ORGANIZATION", None),
|
|
# },
|
|
# },
|
|
# ]
|
|
|
|
# router = Router(model_list=model_list)
|
|
|
|
# print(router.model_list)
|
|
# print(router.model_list[0])
|
|
|
|
# openai_client = router._get_client(
|
|
# deployment=router.model_list[0],
|
|
# kwargs={"input": ["hello"], "model": "openai-bad-org"},
|
|
# )
|
|
# print(vars(openai_client))
|
|
|
|
# assert openai_client.organization == "org-ikDc4ex8NB"
|
|
|
|
# # bad org raises error
|
|
|
|
# try:
|
|
# response = await router.atext_completion(
|
|
# model="openai-bad-org",
|
|
# prompt="this is a test",
|
|
# )
|
|
# pytest.fail("Request should have failed - This organization does not exist")
|
|
# except Exception as e:
|
|
# print("Got exception: " + str(e))
|
|
# assert "header should match organization for API key" in str(
|
|
# e
|
|
# ) or "No such organization" in str(e)
|
|
|
|
# # good org works
|
|
# response = await router.atext_completion(
|
|
# model="openai-good-org",
|
|
# prompt="this is a test",
|
|
# max_tokens=5,
|
|
# )
|
|
# print("working response: ", response)
|
|
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
# def test_init_clients_async_mode():
|
|
# litellm.set_verbose = True
|
|
# import logging
|
|
|
|
# from litellm._logging import verbose_router_logger
|
|
# from litellm.types.router import RouterGeneralSettings
|
|
|
|
# verbose_router_logger.setLevel(logging.DEBUG)
|
|
# try:
|
|
# print("testing init 4 clients with diff timeouts")
|
|
# model_list = [
|
|
# {
|
|
# "model_name": "gpt-3.5-turbo",
|
|
# "litellm_params": {
|
|
# "model": "azure/chatgpt-v-3",
|
|
# "api_key": os.getenv("AZURE_API_KEY"),
|
|
# "api_version": os.getenv("AZURE_API_VERSION"),
|
|
# "api_base": os.getenv("AZURE_API_BASE"),
|
|
# "timeout": 0.01,
|
|
# "stream_timeout": 0.000_001,
|
|
# "max_retries": 7,
|
|
# },
|
|
# },
|
|
# ]
|
|
# router = Router(
|
|
# model_list=model_list,
|
|
# set_verbose=True,
|
|
# router_general_settings=RouterGeneralSettings(async_only_mode=True),
|
|
# )
|
|
# for elem in router.model_list:
|
|
# model_id = elem["model_info"]["id"]
|
|
|
|
# # sync clients not initialized in async_only_mode=True
|
|
# assert router.cache.get_cache(f"{model_id}_client") is None
|
|
# assert router.cache.get_cache(f"{model_id}_stream_client") is None
|
|
|
|
# # only async clients initialized in async_only_mode=True
|
|
# assert router.cache.get_cache(f"{model_id}_async_client") is not None
|
|
# assert router.cache.get_cache(f"{model_id}_stream_async_client") is not None
|
|
# except Exception as e:
|
|
# pytest.fail(f"Error occurred: {e}")
|
|
|
|
|
|
# @pytest.mark.parametrize(
|
|
# "environment,expected_models",
|
|
# [
|
|
# ("development", ["gpt-3.5-turbo"]),
|
|
# ("production", ["gpt-4", "gpt-3.5-turbo", "gpt-4o"]),
|
|
# ],
|
|
# )
|
|
# def test_init_router_with_supported_environments(environment, expected_models):
|
|
# """
|
|
# Tests that the correct models are setup on router when LITELLM_ENVIRONMENT is set
|
|
# """
|
|
# os.environ["LITELLM_ENVIRONMENT"] = environment
|
|
# model_list = [
|
|
# {
|
|
# "model_name": "gpt-3.5-turbo",
|
|
# "litellm_params": {
|
|
# "model": "azure/chatgpt-v-3",
|
|
# "api_key": os.getenv("AZURE_API_KEY"),
|
|
# "api_version": os.getenv("AZURE_API_VERSION"),
|
|
# "api_base": os.getenv("AZURE_API_BASE"),
|
|
# "timeout": 0.01,
|
|
# "stream_timeout": 0.000_001,
|
|
# "max_retries": 7,
|
|
# },
|
|
# "model_info": {"supported_environments": ["development", "production"]},
|
|
# },
|
|
# {
|
|
# "model_name": "gpt-4",
|
|
# "litellm_params": {
|
|
# "model": "openai/gpt-4",
|
|
# "api_key": os.getenv("OPENAI_API_KEY"),
|
|
# "timeout": 0.01,
|
|
# "stream_timeout": 0.000_001,
|
|
# "max_retries": 7,
|
|
# },
|
|
# "model_info": {"supported_environments": ["production"]},
|
|
# },
|
|
# {
|
|
# "model_name": "gpt-4o",
|
|
# "litellm_params": {
|
|
# "model": "openai/gpt-4o",
|
|
# "api_key": os.getenv("OPENAI_API_KEY"),
|
|
# "timeout": 0.01,
|
|
# "stream_timeout": 0.000_001,
|
|
# "max_retries": 7,
|
|
# },
|
|
# "model_info": {"supported_environments": ["production"]},
|
|
# },
|
|
# ]
|
|
# router = Router(model_list=model_list, set_verbose=True)
|
|
# _model_list = router.get_model_names()
|
|
|
|
# print("model_list: ", _model_list)
|
|
# print("expected_models: ", expected_models)
|
|
|
|
# assert set(_model_list) == set(expected_models)
|
|
|
|
# os.environ.pop("LITELLM_ENVIRONMENT")
|