forked from phoenix/litellm-mirror
refactor: move all testing to top-level of repo
Closes https://github.com/BerriAI/litellm/issues/486
This commit is contained in:
Krrish Dholakia
parent
5403c5828c
commit
3560f0ef2c
213 changed files with 74 additions and 217 deletions
698
tests/local_testing/test_router_init.py
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698
tests/local_testing/test_router_init.py
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@ -0,0 +1,698 @@
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# 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-2",
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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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) # openai python adds the extra /
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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-2",
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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-2",
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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-2",
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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-2",
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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 "No such organization: org-ikDc4ex8NB" 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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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 "No such organization: org-ikDc4ex8NB" in str(e)
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||||
|
||||
# good org works
|
||||
response = await router.acompletion(
|
||||
model="openai-good-org",
|
||||
messages=[{"role": "user", "content": "this is a test"}],
|
||||
max_tokens=5,
|
||||
)
|
||||
|
||||
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_text_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 "No such organization: org-ikDc4ex8NB" 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-2",
|
||||
"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-2",
|
||||
"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")
|
||||
Loading…
Add table
Add a link
Reference in a new issue