Spaces:
Configuration error
Configuration error
import os | |
import sys | |
import traceback | |
from unittest import mock | |
from dotenv import load_dotenv | |
import litellm.proxy | |
import litellm.proxy.proxy_server | |
load_dotenv() | |
import io | |
import json | |
import os | |
# this file is to test litellm/proxy | |
sys.path.insert( | |
0, os.path.abspath("../..") | |
) # Adds the parent directory to the system path | |
import asyncio | |
import logging | |
import pytest | |
import litellm | |
from litellm import RateLimitError, Timeout, completion, completion_cost, embedding | |
# Configure logging | |
logging.basicConfig( | |
level=logging.DEBUG, # Set the desired logging level | |
format="%(asctime)s - %(levelname)s - %(message)s", | |
) | |
from unittest.mock import AsyncMock, patch | |
from fastapi import FastAPI | |
# test /chat/completion request to the proxy | |
from fastapi.testclient import TestClient | |
from litellm.integrations.custom_logger import CustomLogger | |
from litellm.proxy.proxy_server import ( # Replace with the actual module where your FastAPI router is defined | |
app, | |
initialize, | |
save_worker_config, | |
) | |
from litellm.proxy.utils import ProxyLogging | |
# Your bearer token | |
token = "sk-1234" | |
headers = {"Authorization": f"Bearer {token}"} | |
example_completion_result = { | |
"choices": [ | |
{ | |
"message": { | |
"content": "Whispers of the wind carry dreams to me.", | |
"role": "assistant", | |
} | |
} | |
], | |
} | |
example_embedding_result = { | |
"object": "list", | |
"data": [ | |
{ | |
"object": "embedding", | |
"index": 0, | |
"embedding": [ | |
-0.006929283495992422, | |
-0.005336422007530928, | |
-4.547132266452536e-05, | |
-0.024047505110502243, | |
-0.006929283495992422, | |
-0.005336422007530928, | |
-4.547132266452536e-05, | |
-0.024047505110502243, | |
-0.006929283495992422, | |
-0.005336422007530928, | |
-4.547132266452536e-05, | |
-0.024047505110502243, | |
], | |
} | |
], | |
"model": "text-embedding-3-small", | |
"usage": {"prompt_tokens": 5, "total_tokens": 5}, | |
} | |
example_image_generation_result = { | |
"created": 1589478378, | |
"data": [{"url": "https://..."}, {"url": "https://..."}], | |
} | |
def mock_patch_acompletion(): | |
return mock.patch( | |
"litellm.proxy.proxy_server.llm_router.acompletion", | |
return_value=example_completion_result, | |
) | |
def mock_patch_aembedding(): | |
return mock.patch( | |
"litellm.proxy.proxy_server.llm_router.aembedding", | |
return_value=example_embedding_result, | |
) | |
def mock_patch_aimage_generation(): | |
return mock.patch( | |
"litellm.proxy.proxy_server.llm_router.aimage_generation", | |
return_value=example_image_generation_result, | |
) | |
def fake_env_vars(monkeypatch): | |
# Set some fake environment variables | |
monkeypatch.setenv("OPENAI_API_KEY", "fake_openai_api_key") | |
monkeypatch.setenv("OPENAI_API_BASE", "http://fake-openai-api-base") | |
monkeypatch.setenv("AZURE_API_BASE", "http://fake-azure-api-base") | |
monkeypatch.setenv("AZURE_OPENAI_API_KEY", "fake_azure_openai_api_key") | |
monkeypatch.setenv("AZURE_SWEDEN_API_BASE", "http://fake-azure-sweden-api-base") | |
monkeypatch.setenv("REDIS_HOST", "localhost") | |
def client_no_auth(fake_env_vars): | |
# Assuming litellm.proxy.proxy_server is an object | |
from litellm.proxy.proxy_server import cleanup_router_config_variables | |
cleanup_router_config_variables() | |
filepath = os.path.dirname(os.path.abspath(__file__)) | |
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml" | |
# initialize can get run in parallel, it sets specific variables for the fast api app, sinc eit gets run in parallel different tests use the wrong variables | |
asyncio.run(initialize(config=config_fp, debug=True)) | |
return TestClient(app) | |
def test_chat_completion(mock_acompletion, client_no_auth): | |
global headers | |
try: | |
# Your test data | |
test_data = { | |
"model": "gpt-3.5-turbo", | |
"messages": [ | |
{"role": "user", "content": "hi"}, | |
], | |
"max_tokens": 10, | |
} | |
print("testing proxy server with chat completions") | |
response = client_no_auth.post("/v1/chat/completions", json=test_data) | |
mock_acompletion.assert_called_once_with( | |
model="gpt-3.5-turbo", | |
messages=[ | |
{"role": "user", "content": "hi"}, | |
], | |
max_tokens=10, | |
litellm_call_id=mock.ANY, | |
litellm_logging_obj=mock.ANY, | |
request_timeout=mock.ANY, | |
specific_deployment=True, | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
print(f"response - {response.text}") | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"Received response: {result}") | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
def test_get_settings_request_timeout(client_no_auth): | |
""" | |
When no timeout is set, it should use the litellm.request_timeout value | |
""" | |
# Set a known value for litellm.request_timeout | |
import litellm | |
# Make a GET request to /settings | |
response = client_no_auth.get("/settings") | |
# Check if the request was successful | |
assert response.status_code == 200 | |
# Parse the JSON response | |
settings = response.json() | |
print("settings", settings) | |
assert settings["litellm.request_timeout"] == litellm.request_timeout | |
def test_add_headers_to_request(litellm_key_header_name): | |
from fastapi import Request | |
from starlette.datastructures import URL | |
import json | |
from litellm.proxy.litellm_pre_call_utils import ( | |
clean_headers, | |
LiteLLMProxyRequestSetup, | |
) | |
headers = { | |
"Authorization": "Bearer 1234", | |
"X-Custom-Header": "Custom-Value", | |
"X-Stainless-Header": "Stainless-Value", | |
} | |
request = Request(scope={"type": "http"}) | |
request._url = URL(url="/chat/completions") | |
request._body = json.dumps({"model": "gpt-3.5-turbo"}).encode("utf-8") | |
request_headers = clean_headers(headers, litellm_key_header_name) | |
forwarded_headers = LiteLLMProxyRequestSetup._get_forwardable_headers( | |
request_headers | |
) | |
assert forwarded_headers == {"X-Custom-Header": "Custom-Value"} | |
def test_chat_completion_forward_headers( | |
mock_acompletion, client_no_auth, litellm_key_header_name, forward_headers | |
): | |
global headers | |
try: | |
if forward_headers: | |
gs = getattr(litellm.proxy.proxy_server, "general_settings") | |
gs["forward_client_headers_to_llm_api"] = True | |
setattr(litellm.proxy.proxy_server, "general_settings", gs) | |
if litellm_key_header_name is not None: | |
gs = getattr(litellm.proxy.proxy_server, "general_settings") | |
gs["litellm_key_header_name"] = litellm_key_header_name | |
setattr(litellm.proxy.proxy_server, "general_settings", gs) | |
# Your test data | |
test_data = { | |
"model": "gpt-3.5-turbo", | |
"messages": [ | |
{"role": "user", "content": "hi"}, | |
], | |
"max_tokens": 10, | |
} | |
headers_to_forward = { | |
"X-Custom-Header": "Custom-Value", | |
"X-Another-Header": "Another-Value", | |
} | |
if litellm_key_header_name is not None: | |
headers_to_not_forward = {litellm_key_header_name: "Bearer 1234"} | |
else: | |
headers_to_not_forward = {"Authorization": "Bearer 1234"} | |
received_headers = {**headers_to_forward, **headers_to_not_forward} | |
print("testing proxy server with chat completions") | |
response = client_no_auth.post( | |
"/v1/chat/completions", json=test_data, headers=received_headers | |
) | |
if not forward_headers: | |
assert "headers" not in mock_acompletion.call_args.kwargs | |
else: | |
assert mock_acompletion.call_args.kwargs["headers"] == { | |
"x-custom-header": "Custom-Value", | |
"x-another-header": "Another-Value", | |
} | |
print(f"response - {response.text}") | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"Received response: {result}") | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
async def test_team_disable_guardrails(mock_acompletion, client_no_auth): | |
""" | |
If team not allowed to turn on/off guardrails | |
Raise 403 forbidden error, if request is made by team on `/key/generate` or `/chat/completions`. | |
""" | |
import asyncio | |
import json | |
import time | |
from fastapi import HTTPException, Request | |
from starlette.datastructures import URL | |
from litellm.proxy._types import ( | |
LiteLLM_TeamTable, | |
LiteLLM_TeamTableCachedObj, | |
ProxyException, | |
UserAPIKeyAuth, | |
) | |
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth | |
from litellm.proxy.proxy_server import hash_token, user_api_key_cache | |
_team_id = "1234" | |
user_key = "sk-12345678" | |
valid_token = UserAPIKeyAuth( | |
team_id=_team_id, | |
team_blocked=True, | |
token=hash_token(user_key), | |
last_refreshed_at=time.time(), | |
) | |
await asyncio.sleep(1) | |
team_obj = LiteLLM_TeamTableCachedObj( | |
team_id=_team_id, | |
blocked=False, | |
last_refreshed_at=time.time(), | |
metadata={"guardrails": {"modify_guardrails": False}}, | |
) | |
user_api_key_cache.set_cache(key=hash_token(user_key), value=valid_token) | |
user_api_key_cache.set_cache(key="team_id:{}".format(_team_id), value=team_obj) | |
setattr(litellm.proxy.proxy_server, "user_api_key_cache", user_api_key_cache) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
setattr(litellm.proxy.proxy_server, "prisma_client", "hello-world") | |
request = Request(scope={"type": "http"}) | |
request._url = URL(url="/chat/completions") | |
body = {"metadata": {"guardrails": {"hide_secrets": False}}} | |
json_bytes = json.dumps(body).encode("utf-8") | |
request._body = json_bytes | |
try: | |
await user_api_key_auth(request=request, api_key="Bearer " + user_key) | |
pytest.fail("Expected to raise 403 forbidden error.") | |
except ProxyException as e: | |
assert e.code == str(403) | |
from test_custom_callback_input import CompletionCustomHandler | |
def test_custom_logger_failure_handler(mock_acompletion, client_no_auth): | |
from litellm.proxy._types import UserAPIKeyAuth | |
from litellm.proxy.proxy_server import hash_token, user_api_key_cache | |
rpm_limit = 0 | |
mock_api_key = "sk-my-test-key" | |
cache_value = UserAPIKeyAuth(token=hash_token(mock_api_key), rpm_limit=rpm_limit) | |
user_api_key_cache.set_cache(key=hash_token(mock_api_key), value=cache_value) | |
mock_logger = CustomLogger() | |
mock_logger_unit_tests = CompletionCustomHandler() | |
proxy_logging_obj: ProxyLogging = getattr( | |
litellm.proxy.proxy_server, "proxy_logging_obj" | |
) | |
litellm.callbacks = [mock_logger, mock_logger_unit_tests] | |
proxy_logging_obj._init_litellm_callbacks(llm_router=None) | |
setattr(litellm.proxy.proxy_server, "user_api_key_cache", user_api_key_cache) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
setattr(litellm.proxy.proxy_server, "prisma_client", "FAKE-VAR") | |
setattr(litellm.proxy.proxy_server, "proxy_logging_obj", proxy_logging_obj) | |
with patch.object( | |
mock_logger, "async_log_failure_event", new=AsyncMock() | |
) as mock_failed_alert: | |
# Your test data | |
test_data = { | |
"model": "gpt-3.5-turbo", | |
"messages": [ | |
{"role": "user", "content": "hi"}, | |
], | |
"max_tokens": 10, | |
} | |
print("testing proxy server with chat completions") | |
response = client_no_auth.post( | |
"/v1/chat/completions", | |
json=test_data, | |
headers={"Authorization": "Bearer {}".format(mock_api_key)}, | |
) | |
assert response.status_code == 429 | |
# confirm async_log_failure_event is called | |
mock_failed_alert.assert_called() | |
assert len(mock_logger_unit_tests.errors) == 0 | |
def test_engines_model_chat_completions(mock_acompletion, client_no_auth): | |
global headers | |
try: | |
# Your test data | |
test_data = { | |
"model": "gpt-3.5-turbo", | |
"messages": [ | |
{"role": "user", "content": "hi"}, | |
], | |
"max_tokens": 10, | |
} | |
print("testing proxy server with chat completions") | |
response = client_no_auth.post( | |
"/engines/gpt-3.5-turbo/chat/completions", json=test_data | |
) | |
mock_acompletion.assert_called_once_with( | |
model="gpt-3.5-turbo", | |
messages=[ | |
{"role": "user", "content": "hi"}, | |
], | |
max_tokens=10, | |
litellm_call_id=mock.ANY, | |
litellm_logging_obj=mock.ANY, | |
request_timeout=mock.ANY, | |
specific_deployment=True, | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
print(f"response - {response.text}") | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"Received response: {result}") | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
def test_chat_completion_azure(mock_acompletion, client_no_auth): | |
global headers | |
try: | |
# Your test data | |
test_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
"max_tokens": 10, | |
} | |
print("testing proxy server with Azure Request /chat/completions") | |
response = client_no_auth.post("/v1/chat/completions", json=test_data) | |
mock_acompletion.assert_called_once_with( | |
model="azure/chatgpt-v-3", | |
messages=[ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
max_tokens=10, | |
litellm_call_id=mock.ANY, | |
litellm_logging_obj=mock.ANY, | |
request_timeout=mock.ANY, | |
specific_deployment=True, | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"Received response: {result}") | |
assert len(result["choices"][0]["message"]["content"]) > 0 | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
# Run the test | |
# test_chat_completion_azure() | |
def test_openai_deployments_model_chat_completions_azure( | |
mock_acompletion, client_no_auth | |
): | |
global headers | |
try: | |
# Your test data | |
test_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
"max_tokens": 10, | |
} | |
url = "/openai/deployments/azure/chatgpt-v-3/chat/completions" | |
print(f"testing proxy server with Azure Request {url}") | |
response = client_no_auth.post(url, json=test_data) | |
mock_acompletion.assert_called_once_with( | |
model="azure/chatgpt-v-3", | |
messages=[ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
max_tokens=10, | |
litellm_call_id=mock.ANY, | |
litellm_logging_obj=mock.ANY, | |
request_timeout=mock.ANY, | |
specific_deployment=True, | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"Received response: {result}") | |
assert len(result["choices"][0]["message"]["content"]) > 0 | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
# Run the test | |
# test_openai_deployments_model_chat_completions_azure() | |
### EMBEDDING | |
def test_embedding(mock_aembedding, client_no_auth): | |
global headers | |
from litellm.proxy.proxy_server import user_custom_auth | |
try: | |
test_data = { | |
"model": "azure/azure-embedding-model", | |
"input": ["good morning from litellm"], | |
} | |
response = client_no_auth.post("/v1/embeddings", json=test_data) | |
mock_aembedding.assert_called_once_with( | |
model="azure/azure-embedding-model", | |
input=["good morning from litellm"], | |
specific_deployment=True, | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
assert response.status_code == 200 | |
result = response.json() | |
print(len(result["data"][0]["embedding"])) | |
assert len(result["data"][0]["embedding"]) > 10 # this usually has len==1536 so | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
def test_bedrock_embedding(mock_aembedding, client_no_auth): | |
global headers | |
from litellm.proxy.proxy_server import user_custom_auth | |
try: | |
test_data = { | |
"model": "amazon-embeddings", | |
"input": ["good morning from litellm"], | |
} | |
response = client_no_auth.post("/v1/embeddings", json=test_data) | |
mock_aembedding.assert_called_once_with( | |
model="amazon-embeddings", | |
input=["good morning from litellm"], | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
assert response.status_code == 200 | |
result = response.json() | |
print(len(result["data"][0]["embedding"])) | |
assert len(result["data"][0]["embedding"]) > 10 # this usually has len==1536 so | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
def test_sagemaker_embedding(client_no_auth): | |
global headers | |
from litellm.proxy.proxy_server import user_custom_auth | |
try: | |
test_data = { | |
"model": "GPT-J 6B - Sagemaker Text Embedding (Internal)", | |
"input": ["good morning from litellm"], | |
} | |
response = client_no_auth.post("/v1/embeddings", json=test_data) | |
assert response.status_code == 200 | |
result = response.json() | |
print(len(result["data"][0]["embedding"])) | |
assert len(result["data"][0]["embedding"]) > 10 # this usually has len==1536 so | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
# Run the test | |
# test_embedding() | |
#### IMAGE GENERATION | |
def test_img_gen(mock_aimage_generation, client_no_auth): | |
global headers | |
from litellm.proxy.proxy_server import user_custom_auth | |
try: | |
test_data = { | |
"model": "dall-e-3", | |
"prompt": "A cute baby sea otter", | |
"n": 1, | |
"size": "1024x1024", | |
} | |
response = client_no_auth.post("/v1/images/generations", json=test_data) | |
mock_aimage_generation.assert_called_once_with( | |
model="dall-e-3", | |
prompt="A cute baby sea otter", | |
n=1, | |
size="1024x1024", | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
assert response.status_code == 200 | |
result = response.json() | |
print(len(result["data"][0]["url"])) | |
assert len(result["data"][0]["url"]) > 10 | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
#### ADDITIONAL | |
def test_add_new_model(client_no_auth): | |
global headers | |
try: | |
test_data = { | |
"model_name": "test_openai_models", | |
"litellm_params": { | |
"model": "gpt-3.5-turbo", | |
}, | |
"model_info": {"description": "this is a test openai model"}, | |
} | |
client_no_auth.post("/model/new", json=test_data, headers=headers) | |
response = client_no_auth.get("/model/info", headers=headers) | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"response: {result}") | |
model_info = None | |
for m in result["data"]: | |
if m["model_name"] == "test_openai_models": | |
model_info = m["model_info"] | |
assert model_info["description"] == "this is a test openai model" | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}") | |
def test_health(client_no_auth): | |
global headers | |
import logging | |
import time | |
from litellm._logging import verbose_logger, verbose_proxy_logger | |
verbose_proxy_logger.setLevel(logging.DEBUG) | |
try: | |
response = client_no_auth.get("/health") | |
assert response.status_code == 200 | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
# test_add_new_model() | |
from litellm.integrations.custom_logger import CustomLogger | |
class MyCustomHandler(CustomLogger): | |
def log_pre_api_call(self, model, messages, kwargs): | |
print(f"Pre-API Call") | |
def log_success_event(self, kwargs, response_obj, start_time, end_time): | |
print(f"On Success") | |
assert kwargs["user"] == "proxy-user" | |
assert kwargs["model"] == "gpt-3.5-turbo" | |
assert kwargs["max_tokens"] == 10 | |
customHandler = MyCustomHandler() | |
def test_chat_completion_optional_params(mock_acompletion, client_no_auth): | |
# [PROXY: PROD TEST] - DO NOT DELETE | |
# This tests if all the /chat/completion params are passed to litellm | |
try: | |
# Your test data | |
litellm.set_verbose = True | |
test_data = { | |
"model": "gpt-3.5-turbo", | |
"messages": [ | |
{"role": "user", "content": "hi"}, | |
], | |
"max_tokens": 10, | |
"user": "proxy-user", | |
} | |
litellm.callbacks = [customHandler] | |
print("testing proxy server: optional params") | |
response = client_no_auth.post("/v1/chat/completions", json=test_data) | |
mock_acompletion.assert_called_once_with( | |
model="gpt-3.5-turbo", | |
messages=[ | |
{"role": "user", "content": "hi"}, | |
], | |
max_tokens=10, | |
user="proxy-user", | |
litellm_call_id=mock.ANY, | |
litellm_logging_obj=mock.ANY, | |
request_timeout=mock.ANY, | |
specific_deployment=True, | |
metadata=mock.ANY, | |
proxy_server_request=mock.ANY, | |
) | |
assert response.status_code == 200 | |
result = response.json() | |
print(f"Received response: {result}") | |
except Exception as e: | |
pytest.fail("LiteLLM Proxy test failed. Exception", e) | |
# Run the test | |
# test_chat_completion_optional_params() | |
# Test Reading config.yaml file | |
from litellm.proxy.proxy_server import ProxyConfig | |
def test_load_router_config(mock_cache, fake_env_vars): | |
mock_cache.return_value.cache.__dict__ = {"redis_client": None} | |
mock_cache.return_value.supported_call_types = [ | |
"completion", | |
"acompletion", | |
"embedding", | |
"aembedding", | |
"atranscription", | |
"transcription", | |
] | |
try: | |
import asyncio | |
print("testing reading config") | |
# this is a basic config.yaml with only a model | |
filepath = os.path.dirname(os.path.abspath(__file__)) | |
proxy_config = ProxyConfig() | |
result = asyncio.run( | |
proxy_config.load_config( | |
router=None, | |
config_file_path=f"{filepath}/example_config_yaml/simple_config.yaml", | |
) | |
) | |
print(result) | |
assert len(result[1]) == 1 | |
# this is a load balancing config yaml | |
result = asyncio.run( | |
proxy_config.load_config( | |
router=None, | |
config_file_path=f"{filepath}/example_config_yaml/azure_config.yaml", | |
) | |
) | |
print(result) | |
assert len(result[1]) == 2 | |
# config with general settings - custom callbacks | |
result = asyncio.run( | |
proxy_config.load_config( | |
router=None, | |
config_file_path=f"{filepath}/example_config_yaml/azure_config.yaml", | |
) | |
) | |
print(result) | |
assert len(result[1]) == 2 | |
# tests for litellm.cache set from config | |
print("testing reading proxy config for cache") | |
litellm.cache = None | |
asyncio.run( | |
proxy_config.load_config( | |
router=None, | |
config_file_path=f"{filepath}/example_config_yaml/cache_no_params.yaml", | |
) | |
) | |
assert litellm.cache is not None | |
assert "redis_client" in vars( | |
litellm.cache.cache | |
) # it should default to redis on proxy | |
assert litellm.cache.supported_call_types == [ | |
"completion", | |
"acompletion", | |
"embedding", | |
"aembedding", | |
"atranscription", | |
"transcription", | |
] # init with all call types | |
litellm.disable_cache() | |
print("testing reading proxy config for cache with params") | |
mock_cache.return_value.supported_call_types = [ | |
"embedding", | |
"aembedding", | |
] | |
asyncio.run( | |
proxy_config.load_config( | |
router=None, | |
config_file_path=f"{filepath}/example_config_yaml/cache_with_params.yaml", | |
) | |
) | |
assert litellm.cache is not None | |
print(litellm.cache) | |
print(litellm.cache.supported_call_types) | |
print(vars(litellm.cache.cache)) | |
assert "redis_client" in vars( | |
litellm.cache.cache | |
) # it should default to redis on proxy | |
assert litellm.cache.supported_call_types == [ | |
"embedding", | |
"aembedding", | |
] # init with all call types | |
except Exception as e: | |
pytest.fail( | |
f"Proxy: Got exception reading config: {str(e)}\n{traceback.format_exc()}" | |
) | |
# test_load_router_config() | |
async def test_team_update_redis(): | |
""" | |
Tests if team update, updates the redis cache if set | |
""" | |
from litellm.caching.caching import DualCache, RedisCache | |
from litellm.proxy._types import LiteLLM_TeamTableCachedObj | |
from litellm.proxy.auth.auth_checks import _cache_team_object | |
proxy_logging_obj: ProxyLogging = getattr( | |
litellm.proxy.proxy_server, "proxy_logging_obj" | |
) | |
redis_cache = RedisCache() | |
with patch.object( | |
redis_cache, | |
"async_set_cache", | |
new=AsyncMock(), | |
) as mock_client: | |
await _cache_team_object( | |
team_id="1234", | |
team_table=LiteLLM_TeamTableCachedObj(team_id="1234"), | |
user_api_key_cache=DualCache(redis_cache=redis_cache), | |
proxy_logging_obj=proxy_logging_obj, | |
) | |
mock_client.assert_called() | |
async def test_get_team_redis(client_no_auth): | |
""" | |
Tests if get_team_object gets value from redis cache, if set | |
""" | |
from litellm.caching.caching import DualCache, RedisCache | |
from litellm.proxy.auth.auth_checks import get_team_object | |
proxy_logging_obj: ProxyLogging = getattr( | |
litellm.proxy.proxy_server, "proxy_logging_obj" | |
) | |
redis_cache = RedisCache() | |
with patch.object( | |
redis_cache, | |
"async_get_cache", | |
new=AsyncMock(), | |
) as mock_client: | |
try: | |
await get_team_object( | |
team_id="1234", | |
user_api_key_cache=DualCache(redis_cache=redis_cache), | |
parent_otel_span=None, | |
proxy_logging_obj=proxy_logging_obj, | |
prisma_client=AsyncMock(), | |
) | |
except Exception as e: | |
pass | |
mock_client.assert_called_once() | |
import random | |
import uuid | |
from unittest.mock import AsyncMock, MagicMock, PropertyMock, patch | |
from litellm.proxy._types import ( | |
LitellmUserRoles, | |
NewUserRequest, | |
TeamMemberAddRequest, | |
UserAPIKeyAuth, | |
) | |
from litellm.proxy.management_endpoints.internal_user_endpoints import new_user | |
from litellm.proxy.management_endpoints.team_endpoints import team_member_add | |
from test_key_generate_prisma import prisma_client | |
async def test_create_user_default_budget(prisma_client, user_role): | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
setattr(litellm, "max_internal_user_budget", 10) | |
setattr(litellm, "internal_user_budget_duration", "5m") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
user = f"ishaan {uuid.uuid4().hex}" | |
request = NewUserRequest( | |
user_id=user, user_role=user_role | |
) # create a key with no budget | |
with patch.object( | |
litellm.proxy.proxy_server.prisma_client, "insert_data", new=AsyncMock() | |
) as mock_client: | |
await new_user( | |
request, | |
) | |
mock_client.assert_called() | |
print(f"mock_client.call_args: {mock_client.call_args}") | |
print("mock_client.call_args.kwargs: {}".format(mock_client.call_args.kwargs)) | |
if user_role == LitellmUserRoles.INTERNAL_USER.value: | |
assert ( | |
mock_client.call_args.kwargs["data"]["max_budget"] | |
== litellm.max_internal_user_budget | |
) | |
assert ( | |
mock_client.call_args.kwargs["data"]["budget_duration"] | |
== litellm.internal_user_budget_duration | |
) | |
else: | |
assert mock_client.call_args.kwargs["data"]["max_budget"] is None | |
assert mock_client.call_args.kwargs["data"]["budget_duration"] is None | |
async def test_create_team_member_add(prisma_client, new_member_method): | |
import time | |
from fastapi import Request | |
from litellm.proxy._types import LiteLLM_TeamTableCachedObj, LiteLLM_UserTable | |
from litellm.proxy.proxy_server import hash_token, user_api_key_cache | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
setattr(litellm, "max_internal_user_budget", 10) | |
setattr(litellm, "internal_user_budget_duration", "5m") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
user = f"ishaan {uuid.uuid4().hex}" | |
_team_id = "litellm-test-client-id-new" | |
team_obj = LiteLLM_TeamTableCachedObj( | |
team_id=_team_id, | |
blocked=False, | |
last_refreshed_at=time.time(), | |
metadata={"guardrails": {"modify_guardrails": False}}, | |
) | |
# user_api_key_cache.set_cache(key=hash_token(user_key), value=valid_token) | |
user_api_key_cache.set_cache(key="team_id:{}".format(_team_id), value=team_obj) | |
setattr(litellm.proxy.proxy_server, "user_api_key_cache", user_api_key_cache) | |
if new_member_method == "user_id": | |
data = { | |
"team_id": _team_id, | |
"member": [{"role": "user", "user_id": user}], | |
} | |
elif new_member_method == "user_email": | |
data = { | |
"team_id": _team_id, | |
"member": [{"role": "user", "user_email": user}], | |
} | |
team_member_add_request = TeamMemberAddRequest(**data) | |
with patch( | |
"litellm.proxy.proxy_server.prisma_client.db.litellm_usertable", | |
new_callable=AsyncMock, | |
) as mock_litellm_usertable, patch( | |
"litellm.proxy.auth.auth_checks._get_team_object_from_user_api_key_cache", | |
new=AsyncMock(return_value=team_obj), | |
) as mock_team_obj: | |
mock_client = AsyncMock( | |
return_value=LiteLLM_UserTable( | |
user_id="1234", max_budget=100, user_email="1234" | |
) | |
) | |
mock_litellm_usertable.upsert = mock_client | |
mock_litellm_usertable.find_many = AsyncMock(return_value=None) | |
team_mock_client = AsyncMock() | |
original_val = getattr( | |
litellm.proxy.proxy_server.prisma_client.db, "litellm_teamtable" | |
) | |
litellm.proxy.proxy_server.prisma_client.db.litellm_teamtable = team_mock_client | |
team_mock_client.update = AsyncMock( | |
return_value=LiteLLM_TeamTableCachedObj(team_id="1234") | |
) | |
await team_member_add( | |
data=team_member_add_request, | |
user_api_key_dict=UserAPIKeyAuth(user_role="proxy_admin"), | |
) | |
mock_client.assert_called() | |
print(f"mock_client.call_args: {mock_client.call_args}") | |
print("mock_client.call_args.kwargs: {}".format(mock_client.call_args.kwargs)) | |
assert ( | |
mock_client.call_args.kwargs["data"]["create"]["max_budget"] | |
== litellm.max_internal_user_budget | |
) | |
assert ( | |
mock_client.call_args.kwargs["data"]["create"]["budget_duration"] | |
== litellm.internal_user_budget_duration | |
) | |
litellm.proxy.proxy_server.prisma_client.db.litellm_teamtable = original_val | |
async def test_create_team_member_add_team_admin_user_api_key_auth( | |
prisma_client, team_member_role, team_route | |
): | |
import time | |
from fastapi import Request | |
from litellm.proxy._types import LiteLLM_TeamTableCachedObj, Member | |
from litellm.proxy.proxy_server import ( | |
ProxyException, | |
hash_token, | |
user_api_key_auth, | |
user_api_key_cache, | |
) | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
setattr(litellm, "max_internal_user_budget", 10) | |
setattr(litellm, "internal_user_budget_duration", "5m") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
user = f"ishaan {uuid.uuid4().hex}" | |
_team_id = "litellm-test-client-id-new" | |
user_key = "sk-12345678" | |
valid_token = UserAPIKeyAuth( | |
team_id=_team_id, | |
token=hash_token(user_key), | |
team_member=Member(role=team_member_role, user_id=user), | |
last_refreshed_at=time.time(), | |
) | |
user_api_key_cache.set_cache(key=hash_token(user_key), value=valid_token) | |
team_obj = LiteLLM_TeamTableCachedObj( | |
team_id=_team_id, | |
blocked=False, | |
last_refreshed_at=time.time(), | |
metadata={"guardrails": {"modify_guardrails": False}}, | |
) | |
user_api_key_cache.set_cache(key="team_id:{}".format(_team_id), value=team_obj) | |
setattr(litellm.proxy.proxy_server, "user_api_key_cache", user_api_key_cache) | |
## TEST IF TEAM ADMIN ALLOWED TO CALL /MEMBER_ADD ENDPOINT | |
import json | |
from starlette.datastructures import URL | |
request = Request(scope={"type": "http"}) | |
request._url = URL(url=team_route) | |
body = {} | |
json_bytes = json.dumps(body).encode("utf-8") | |
request._body = json_bytes | |
## ALLOWED BY USER_API_KEY_AUTH | |
await user_api_key_auth(request=request, api_key="Bearer " + user_key) | |
async def test_create_team_member_add_team_admin( | |
prisma_client, new_member_method, user_role | |
): | |
""" | |
Relevant issue - https://github.com/BerriAI/litellm/issues/5300 | |
Allow team admins to: | |
- Add and remove team members | |
- raise error if team member not an existing 'internal_user' | |
""" | |
import time | |
from fastapi import Request | |
from litellm.proxy._types import ( | |
LiteLLM_TeamTableCachedObj, | |
LiteLLM_UserTable, | |
Member, | |
) | |
from litellm.proxy.proxy_server import ( | |
HTTPException, | |
ProxyException, | |
hash_token, | |
user_api_key_auth, | |
user_api_key_cache, | |
) | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
setattr(litellm, "max_internal_user_budget", 10) | |
setattr(litellm, "internal_user_budget_duration", "5m") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
user = f"ishaan {uuid.uuid4().hex}" | |
_team_id = "litellm-test-client-id-new" | |
user_key = "sk-12345678" | |
team_admin = f"krrish {uuid.uuid4().hex}" | |
valid_token = UserAPIKeyAuth( | |
team_id=_team_id, | |
user_id=team_admin, | |
token=hash_token(user_key), | |
last_refreshed_at=time.time(), | |
) | |
user_api_key_cache.set_cache(key=hash_token(user_key), value=valid_token) | |
team_obj = LiteLLM_TeamTableCachedObj( | |
team_id=_team_id, | |
blocked=False, | |
last_refreshed_at=time.time(), | |
members_with_roles=[Member(role=user_role, user_id=team_admin)], | |
metadata={"guardrails": {"modify_guardrails": False}}, | |
) | |
user_api_key_cache.set_cache(key="team_id:{}".format(_team_id), value=team_obj) | |
setattr(litellm.proxy.proxy_server, "user_api_key_cache", user_api_key_cache) | |
if new_member_method == "user_id": | |
data = { | |
"team_id": _team_id, | |
"member": [{"role": "user", "user_id": user}], | |
} | |
elif new_member_method == "user_email": | |
data = { | |
"team_id": _team_id, | |
"member": [{"role": "user", "user_email": user}], | |
} | |
team_member_add_request = TeamMemberAddRequest(**data) | |
with patch( | |
"litellm.proxy.proxy_server.prisma_client.db.litellm_usertable", | |
new_callable=AsyncMock, | |
) as mock_litellm_usertable, patch( | |
"litellm.proxy.auth.auth_checks._get_team_object_from_user_api_key_cache", | |
new=AsyncMock(return_value=team_obj), | |
) as mock_team_obj: | |
mock_client = AsyncMock( | |
return_value=LiteLLM_UserTable( | |
user_id="1234", max_budget=100, user_email="1234" | |
) | |
) | |
mock_litellm_usertable.upsert = mock_client | |
mock_litellm_usertable.find_many = AsyncMock(return_value=None) | |
team_mock_client = AsyncMock() | |
original_val = getattr( | |
litellm.proxy.proxy_server.prisma_client.db, "litellm_teamtable" | |
) | |
litellm.proxy.proxy_server.prisma_client.db.litellm_teamtable = team_mock_client | |
team_mock_client.update = AsyncMock( | |
return_value=LiteLLM_TeamTableCachedObj(team_id="1234") | |
) | |
try: | |
await team_member_add( | |
data=team_member_add_request, | |
user_api_key_dict=valid_token, | |
) | |
except HTTPException as e: | |
if user_role == "user": | |
assert e.status_code == 403 | |
return | |
else: | |
raise e | |
mock_client.assert_called() | |
print(f"mock_client.call_args: {mock_client.call_args}") | |
print("mock_client.call_args.kwargs: {}".format(mock_client.call_args.kwargs)) | |
assert ( | |
mock_client.call_args.kwargs["data"]["create"]["max_budget"] | |
== litellm.max_internal_user_budget | |
) | |
assert ( | |
mock_client.call_args.kwargs["data"]["create"]["budget_duration"] | |
== litellm.internal_user_budget_duration | |
) | |
litellm.proxy.proxy_server.prisma_client.db.litellm_teamtable = original_val | |
async def test_user_info_team_list(prisma_client): | |
"""Assert user_info for admin calls team_list function""" | |
from litellm.proxy._types import LiteLLM_UserTable | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
from litellm.proxy.management_endpoints.internal_user_endpoints import user_info | |
with patch( | |
"litellm.proxy.management_endpoints.team_endpoints.list_team", | |
new_callable=AsyncMock, | |
) as mock_client: | |
prisma_client.get_data = AsyncMock( | |
return_value=LiteLLM_UserTable( | |
user_role="proxy_admin", | |
user_id="default_user_id", | |
max_budget=None, | |
user_email="", | |
) | |
) | |
try: | |
await user_info( | |
request=MagicMock(), | |
user_id=None, | |
user_api_key_dict=UserAPIKeyAuth( | |
api_key="sk-1234", user_id="default_user_id" | |
), | |
) | |
except Exception: | |
pass | |
mock_client.assert_called() | |
async def test_add_callback_via_key(prisma_client): | |
""" | |
Test if callback specified in key, is used. | |
""" | |
global headers | |
import json | |
from fastapi import HTTPException, Request, Response | |
from starlette.datastructures import URL | |
from litellm.proxy.proxy_server import chat_completion | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
litellm.set_verbose = True | |
try: | |
# Your test data | |
test_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
} | |
request = Request(scope={"type": "http", "method": "POST", "headers": {}}) | |
request._url = URL(url="/chat/completions") | |
json_bytes = json.dumps(test_data).encode("utf-8") | |
request._body = json_bytes | |
with patch.object( | |
litellm.litellm_core_utils.litellm_logging, | |
"LangFuseLogger", | |
new=MagicMock(), | |
) as mock_client: | |
resp = await chat_completion( | |
request=request, | |
fastapi_response=Response(), | |
user_api_key_dict=UserAPIKeyAuth( | |
metadata={ | |
"logging": [ | |
{ | |
"callback_name": "langfuse", # 'otel', 'langfuse', 'lunary' | |
"callback_type": "success", # set, if required by integration - future improvement, have logging tools work for success + failure by default | |
"callback_vars": { | |
"langfuse_public_key": "os.environ/LANGFUSE_PUBLIC_KEY", | |
"langfuse_secret_key": "os.environ/LANGFUSE_SECRET_KEY", | |
"langfuse_host": "https://us.cloud.langfuse.com", | |
}, | |
} | |
] | |
} | |
), | |
) | |
print(resp) | |
mock_client.assert_called() | |
mock_client.return_value.log_event.assert_called() | |
args, kwargs = mock_client.return_value.log_event.call_args | |
kwargs = kwargs["kwargs"] | |
assert "user_api_key_metadata" in kwargs["litellm_params"]["metadata"] | |
assert ( | |
"logging" | |
in kwargs["litellm_params"]["metadata"]["user_api_key_metadata"] | |
) | |
checked_keys = False | |
for item in kwargs["litellm_params"]["metadata"]["user_api_key_metadata"][ | |
"logging" | |
]: | |
for k, v in item["callback_vars"].items(): | |
print("k={}, v={}".format(k, v)) | |
if "key" in k: | |
assert "os.environ" in v | |
checked_keys = True | |
assert checked_keys | |
except Exception as e: | |
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") | |
async def test_add_callback_via_key_litellm_pre_call_utils( | |
prisma_client, callback_type, expected_success_callbacks, expected_failure_callbacks | |
): | |
import json | |
from fastapi import HTTPException, Request, Response | |
from starlette.datastructures import URL | |
from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
proxy_config = getattr(litellm.proxy.proxy_server, "proxy_config") | |
request = Request(scope={"type": "http", "method": "POST", "headers": {}}) | |
request._url = URL(url="/chat/completions") | |
test_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
} | |
json_bytes = json.dumps(test_data).encode("utf-8") | |
request._body = json_bytes | |
data = { | |
"data": { | |
"model": "azure/chatgpt-v-3", | |
"messages": [{"role": "user", "content": "write 1 sentence poem"}], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
}, | |
"request": request, | |
"user_api_key_dict": UserAPIKeyAuth( | |
token=None, | |
key_name=None, | |
key_alias=None, | |
spend=0.0, | |
max_budget=None, | |
expires=None, | |
models=[], | |
aliases={}, | |
config={}, | |
user_id=None, | |
team_id=None, | |
max_parallel_requests=None, | |
metadata={ | |
"logging": [ | |
{ | |
"callback_name": "langfuse", | |
"callback_type": callback_type, | |
"callback_vars": { | |
"langfuse_public_key": "my-mock-public-key", | |
"langfuse_secret_key": "my-mock-secret-key", | |
"langfuse_host": "https://us.cloud.langfuse.com", | |
}, | |
} | |
] | |
}, | |
tpm_limit=None, | |
rpm_limit=None, | |
budget_duration=None, | |
budget_reset_at=None, | |
allowed_cache_controls=[], | |
permissions={}, | |
model_spend={}, | |
model_max_budget={}, | |
soft_budget_cooldown=False, | |
litellm_budget_table=None, | |
org_id=None, | |
team_spend=None, | |
team_alias=None, | |
team_tpm_limit=None, | |
team_rpm_limit=None, | |
team_max_budget=None, | |
team_models=[], | |
team_blocked=False, | |
soft_budget=None, | |
team_model_aliases=None, | |
team_member_spend=None, | |
team_metadata=None, | |
end_user_id=None, | |
end_user_tpm_limit=None, | |
end_user_rpm_limit=None, | |
end_user_max_budget=None, | |
last_refreshed_at=None, | |
api_key=None, | |
user_role=None, | |
allowed_model_region=None, | |
parent_otel_span=None, | |
), | |
"proxy_config": proxy_config, | |
"general_settings": {}, | |
"version": "0.0.0", | |
} | |
new_data = await add_litellm_data_to_request(**data) | |
print("NEW DATA: {}".format(new_data)) | |
assert "langfuse_public_key" in new_data | |
assert new_data["langfuse_public_key"] == "my-mock-public-key" | |
assert "langfuse_secret_key" in new_data | |
assert new_data["langfuse_secret_key"] == "my-mock-secret-key" | |
if expected_success_callbacks: | |
assert "success_callback" in new_data | |
assert new_data["success_callback"] == expected_success_callbacks | |
if expected_failure_callbacks: | |
assert "failure_callback" in new_data | |
assert new_data["failure_callback"] == expected_failure_callbacks | |
async def test_disable_fallbacks_by_key(disable_fallbacks_set): | |
from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup | |
key_metadata = {"disable_fallbacks": disable_fallbacks_set} | |
existing_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [{"role": "user", "content": "write 1 sentence poem"}], | |
} | |
data = LiteLLMProxyRequestSetup.add_key_level_controls( | |
key_metadata=key_metadata, | |
data=existing_data, | |
_metadata_variable_name="metadata", | |
) | |
assert data["disable_fallbacks"] == disable_fallbacks_set | |
async def test_add_callback_via_key_litellm_pre_call_utils_gcs_bucket( | |
prisma_client, callback_type, expected_success_callbacks, expected_failure_callbacks | |
): | |
import json | |
from fastapi import HTTPException, Request, Response | |
from starlette.datastructures import URL | |
from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
proxy_config = getattr(litellm.proxy.proxy_server, "proxy_config") | |
request = Request(scope={"type": "http", "method": "POST", "headers": {}}) | |
request._url = URL(url="/chat/completions") | |
test_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
} | |
json_bytes = json.dumps(test_data).encode("utf-8") | |
request._body = json_bytes | |
data = { | |
"data": { | |
"model": "azure/chatgpt-v-3", | |
"messages": [{"role": "user", "content": "write 1 sentence poem"}], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
}, | |
"request": request, | |
"user_api_key_dict": UserAPIKeyAuth( | |
token=None, | |
key_name=None, | |
key_alias=None, | |
spend=0.0, | |
max_budget=None, | |
expires=None, | |
models=[], | |
aliases={}, | |
config={}, | |
user_id=None, | |
team_id=None, | |
max_parallel_requests=None, | |
metadata={ | |
"logging": [ | |
{ | |
"callback_name": "gcs_bucket", | |
"callback_type": callback_type, | |
"callback_vars": { | |
"gcs_bucket_name": "key-logging-project1", | |
"gcs_path_service_account": "pathrise-convert-1606954137718-a956eef1a2a8.json", | |
}, | |
} | |
] | |
}, | |
tpm_limit=None, | |
rpm_limit=None, | |
budget_duration=None, | |
budget_reset_at=None, | |
allowed_cache_controls=[], | |
permissions={}, | |
model_spend={}, | |
model_max_budget={}, | |
soft_budget_cooldown=False, | |
litellm_budget_table=None, | |
org_id=None, | |
team_spend=None, | |
team_alias=None, | |
team_tpm_limit=None, | |
team_rpm_limit=None, | |
team_max_budget=None, | |
team_models=[], | |
team_blocked=False, | |
soft_budget=None, | |
team_model_aliases=None, | |
team_member_spend=None, | |
team_metadata=None, | |
end_user_id=None, | |
end_user_tpm_limit=None, | |
end_user_rpm_limit=None, | |
end_user_max_budget=None, | |
last_refreshed_at=None, | |
api_key=None, | |
user_role=None, | |
allowed_model_region=None, | |
parent_otel_span=None, | |
), | |
"proxy_config": proxy_config, | |
"general_settings": {}, | |
"version": "0.0.0", | |
} | |
new_data = await add_litellm_data_to_request(**data) | |
print("NEW DATA: {}".format(new_data)) | |
assert "gcs_bucket_name" in new_data | |
assert new_data["gcs_bucket_name"] == "key-logging-project1" | |
assert "gcs_path_service_account" in new_data | |
assert ( | |
new_data["gcs_path_service_account"] | |
== "pathrise-convert-1606954137718-a956eef1a2a8.json" | |
) | |
if expected_success_callbacks: | |
assert "success_callback" in new_data | |
assert new_data["success_callback"] == expected_success_callbacks | |
if expected_failure_callbacks: | |
assert "failure_callback" in new_data | |
assert new_data["failure_callback"] == expected_failure_callbacks | |
async def test_add_callback_via_key_litellm_pre_call_utils_langsmith( | |
prisma_client, callback_type, expected_success_callbacks, expected_failure_callbacks | |
): | |
import json | |
from fastapi import HTTPException, Request, Response | |
from starlette.datastructures import URL | |
from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
proxy_config = getattr(litellm.proxy.proxy_server, "proxy_config") | |
request = Request(scope={"type": "http", "method": "POST", "headers": {}}) | |
request._url = URL(url="/chat/completions") | |
test_data = { | |
"model": "azure/chatgpt-v-3", | |
"messages": [ | |
{"role": "user", "content": "write 1 sentence poem"}, | |
], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
} | |
json_bytes = json.dumps(test_data).encode("utf-8") | |
request._body = json_bytes | |
data = { | |
"data": { | |
"model": "azure/chatgpt-v-3", | |
"messages": [{"role": "user", "content": "write 1 sentence poem"}], | |
"max_tokens": 10, | |
"mock_response": "Hello world", | |
"api_key": "my-fake-key", | |
}, | |
"request": request, | |
"user_api_key_dict": UserAPIKeyAuth( | |
token=None, | |
key_name=None, | |
key_alias=None, | |
spend=0.0, | |
max_budget=None, | |
expires=None, | |
models=[], | |
aliases={}, | |
config={}, | |
user_id=None, | |
team_id=None, | |
max_parallel_requests=None, | |
metadata={ | |
"logging": [ | |
{ | |
"callback_name": "langsmith", | |
"callback_type": callback_type, | |
"callback_vars": { | |
"langsmith_api_key": "ls-1234", | |
"langsmith_project": "pr-brief-resemblance-72", | |
"langsmith_base_url": "https://api.smith.langchain.com", | |
}, | |
} | |
] | |
}, | |
tpm_limit=None, | |
rpm_limit=None, | |
budget_duration=None, | |
budget_reset_at=None, | |
allowed_cache_controls=[], | |
permissions={}, | |
model_spend={}, | |
model_max_budget={}, | |
soft_budget_cooldown=False, | |
litellm_budget_table=None, | |
org_id=None, | |
team_spend=None, | |
team_alias=None, | |
team_tpm_limit=None, | |
team_rpm_limit=None, | |
team_max_budget=None, | |
team_models=[], | |
team_blocked=False, | |
soft_budget=None, | |
team_model_aliases=None, | |
team_member_spend=None, | |
team_metadata=None, | |
end_user_id=None, | |
end_user_tpm_limit=None, | |
end_user_rpm_limit=None, | |
end_user_max_budget=None, | |
last_refreshed_at=None, | |
api_key=None, | |
user_role=None, | |
allowed_model_region=None, | |
parent_otel_span=None, | |
), | |
"proxy_config": proxy_config, | |
"general_settings": {}, | |
"version": "0.0.0", | |
} | |
new_data = await add_litellm_data_to_request(**data) | |
print("NEW DATA: {}".format(new_data)) | |
assert "langsmith_api_key" in new_data | |
assert new_data["langsmith_api_key"] == "ls-1234" | |
assert "langsmith_project" in new_data | |
assert new_data["langsmith_project"] == "pr-brief-resemblance-72" | |
assert "langsmith_base_url" in new_data | |
assert new_data["langsmith_base_url"] == "https://api.smith.langchain.com" | |
if expected_success_callbacks: | |
assert "success_callback" in new_data | |
assert new_data["success_callback"] == expected_success_callbacks | |
if expected_failure_callbacks: | |
assert "failure_callback" in new_data | |
assert new_data["failure_callback"] == expected_failure_callbacks | |
async def test_gemini_pass_through_endpoint(): | |
from starlette.datastructures import URL | |
from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( | |
Request, | |
Response, | |
gemini_proxy_route, | |
) | |
body = b""" | |
{ | |
"contents": [{ | |
"parts":[{ | |
"text": "The quick brown fox jumps over the lazy dog." | |
}] | |
}] | |
} | |
""" | |
# Construct the scope dictionary | |
scope = { | |
"type": "http", | |
"method": "POST", | |
"path": "/gemini/v1beta/models/gemini-1.5-flash:countTokens", | |
"query_string": b"key=sk-1234", | |
"headers": [ | |
(b"content-type", b"application/json"), | |
], | |
} | |
# Create a new Request object | |
async def async_receive(): | |
return {"type": "http.request", "body": body, "more_body": False} | |
request = Request( | |
scope=scope, | |
receive=async_receive, | |
) | |
resp = await gemini_proxy_route( | |
endpoint="v1beta/models/gemini-1.5-flash:countTokens?key=sk-1234", | |
request=request, | |
fastapi_response=Response(), | |
) | |
print(resp.body) | |
async def test_proxy_model_group_alias_checks(prisma_client, hidden): | |
""" | |
Check if model group alias is returned on | |
`/v1/models` | |
`/v1/model/info` | |
`/v1/model_group/info` | |
""" | |
import json | |
from fastapi import HTTPException, Request, Response | |
from starlette.datastructures import URL | |
from litellm.proxy.proxy_server import model_group_info, model_info_v1, model_list | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
proxy_config = getattr(litellm.proxy.proxy_server, "proxy_config") | |
_model_list = [ | |
{ | |
"model_name": "gpt-3.5-turbo", | |
"litellm_params": {"model": "gpt-3.5-turbo"}, | |
} | |
] | |
model_alias = "gpt-4" | |
router = litellm.Router( | |
model_list=_model_list, | |
model_group_alias={model_alias: {"model": "gpt-3.5-turbo", "hidden": hidden}}, | |
) | |
setattr(litellm.proxy.proxy_server, "llm_router", router) | |
setattr(litellm.proxy.proxy_server, "llm_model_list", _model_list) | |
request = Request(scope={"type": "http", "method": "POST", "headers": {}}) | |
request._url = URL(url="/v1/models") | |
resp = await model_list( | |
user_api_key_dict=UserAPIKeyAuth(models=[]), | |
) | |
if hidden: | |
assert len(resp["data"]) == 1 | |
else: | |
assert len(resp["data"]) == 2 | |
print(resp) | |
resp = await model_info_v1( | |
user_api_key_dict=UserAPIKeyAuth(models=[]), | |
) | |
models = resp["data"] | |
is_model_alias_in_list = False | |
for item in models: | |
if model_alias == item["model_name"]: | |
is_model_alias_in_list = True | |
if hidden: | |
assert is_model_alias_in_list is False | |
else: | |
assert is_model_alias_in_list | |
resp = await model_group_info( | |
user_api_key_dict=UserAPIKeyAuth(models=[]), | |
) | |
print(f"resp: {resp}") | |
models = resp["data"] | |
is_model_alias_in_list = False | |
print(f"model_alias: {model_alias}, models: {models}") | |
for item in models: | |
if model_alias == item.model_group: | |
is_model_alias_in_list = True | |
if hidden: | |
assert is_model_alias_in_list is False | |
else: | |
assert is_model_alias_in_list, f"models: {models}" | |
async def test_proxy_model_group_info_rerank(prisma_client): | |
""" | |
Check if rerank model is returned on the following endpoints | |
`/v1/models` | |
`/v1/model/info` | |
`/v1/model_group/info` | |
""" | |
import json | |
from fastapi import HTTPException, Request, Response | |
from starlette.datastructures import URL | |
from litellm.proxy.proxy_server import model_group_info, model_info_v1, model_list | |
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
await litellm.proxy.proxy_server.prisma_client.connect() | |
proxy_config = getattr(litellm.proxy.proxy_server, "proxy_config") | |
_model_list = [ | |
{ | |
"model_name": "rerank-english-v3.0", | |
"litellm_params": {"model": "cohere/rerank-english-v3.0"}, | |
"model_info": { | |
"mode": "rerank", | |
}, | |
} | |
] | |
router = litellm.Router(model_list=_model_list) | |
setattr(litellm.proxy.proxy_server, "llm_router", router) | |
setattr(litellm.proxy.proxy_server, "llm_model_list", _model_list) | |
request = Request(scope={"type": "http", "method": "POST", "headers": {}}) | |
request._url = URL(url="/v1/models") | |
resp = await model_list( | |
user_api_key_dict=UserAPIKeyAuth(models=[]), | |
) | |
assert len(resp["data"]) == 1 | |
print(resp) | |
resp = await model_info_v1( | |
user_api_key_dict=UserAPIKeyAuth(models=[]), | |
) | |
models = resp["data"] | |
assert models[0]["model_info"]["mode"] == "rerank" | |
resp = await model_group_info( | |
user_api_key_dict=UserAPIKeyAuth(models=[]), | |
) | |
print(resp) | |
models = resp["data"] | |
assert models[0].mode == "rerank" | |
# @pytest.mark.asyncio | |
# async def test_proxy_team_member_add(prisma_client): | |
# """ | |
# Add 10 people to a team. Confirm all 10 are added. | |
# """ | |
# from litellm.proxy.management_endpoints.team_endpoints import ( | |
# team_member_add, | |
# new_team, | |
# ) | |
# from litellm.proxy._types import TeamMemberAddRequest, Member, NewTeamRequest | |
# setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) | |
# setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") | |
# try: | |
# async def test(): | |
# await litellm.proxy.proxy_server.prisma_client.connect() | |
# from litellm.proxy.proxy_server import user_api_key_cache | |
# user_api_key_dict = UserAPIKeyAuth( | |
# user_role=LitellmUserRoles.PROXY_ADMIN, | |
# api_key="sk-1234", | |
# user_id="1234", | |
# ) | |
# new_team() | |
# for _ in range(10): | |
# request = TeamMemberAddRequest( | |
# team_id="1234", | |
# member=Member( | |
# user_id="1234", | |
# user_role=LitellmUserRoles.INTERNAL_USER, | |
# ), | |
# ) | |
# key = await team_member_add( | |
# request, user_api_key_dict=user_api_key_dict | |
# ) | |
# print(key) | |
# user_id = key.user_id | |
# # check /user/info to verify user_role was set correctly | |
# new_user_info = await user_info( | |
# user_id=user_id, user_api_key_dict=user_api_key_dict | |
# ) | |
# new_user_info = new_user_info.user_info | |
# print("new_user_info=", new_user_info) | |
# assert new_user_info["user_role"] == LitellmUserRoles.INTERNAL_USER | |
# assert new_user_info["user_id"] == user_id | |
# generated_key = key.key | |
# bearer_token = "Bearer " + generated_key | |
# assert generated_key not in user_api_key_cache.in_memory_cache.cache_dict | |
# value_from_prisma = await prisma_client.get_data( | |
# token=generated_key, | |
# ) | |
# print("token from prisma", value_from_prisma) | |
# request = Request( | |
# { | |
# "type": "http", | |
# "route": api_route, | |
# "path": api_route.path, | |
# "headers": [("Authorization", bearer_token)], | |
# } | |
# ) | |
# # use generated key to auth in | |
# result = await user_api_key_auth(request=request, api_key=bearer_token) | |
# print("result from user auth with new key", result) | |
# asyncio.run(test()) | |
# except Exception as e: | |
# pytest.fail(f"An exception occurred - {str(e)}") | |
async def test_proxy_server_prisma_setup(): | |
from litellm.proxy.proxy_server import ProxyStartupEvent, proxy_state | |
from litellm.proxy.utils import ProxyLogging | |
from litellm.caching import DualCache | |
user_api_key_cache = DualCache() | |
with patch.object( | |
litellm.proxy.proxy_server, "PrismaClient", new=MagicMock() | |
) as mock_prisma_client: | |
mock_client = mock_prisma_client.return_value # This is the mocked instance | |
mock_client.connect = AsyncMock() # Mock the connect method | |
mock_client.check_view_exists = AsyncMock() # Mock the check_view_exists method | |
mock_client.health_check = AsyncMock() # Mock the health_check method | |
mock_client._set_spend_logs_row_count_in_proxy_state = ( | |
AsyncMock() | |
) # Mock the _set_spend_logs_row_count_in_proxy_state method | |
await ProxyStartupEvent._setup_prisma_client( | |
database_url=os.getenv("DATABASE_URL"), | |
proxy_logging_obj=ProxyLogging(user_api_key_cache=user_api_key_cache), | |
user_api_key_cache=user_api_key_cache, | |
) | |
# Verify our mocked methods were called | |
mock_client.connect.assert_called_once() | |
mock_client.check_view_exists.assert_called_once() | |
# Note: This is REALLY IMPORTANT to check that the health check is called | |
# This is how we ensure the DB is ready before proceeding | |
mock_client.health_check.assert_called_once() | |
# check that the spend logs row count is set in proxy state | |
mock_client._set_spend_logs_row_count_in_proxy_state.assert_called_once() | |
assert proxy_state.get_proxy_state_variable("spend_logs_row_count") is not None | |
async def test_proxy_server_prisma_setup_invalid_db(): | |
""" | |
PROD TEST: Test that proxy server startup fails when it's unable to connect to the database | |
Think 2-3 times before editing / deleting this test, it's important for PROD | |
""" | |
from litellm.proxy.proxy_server import ProxyStartupEvent | |
from litellm.proxy.utils import ProxyLogging | |
from litellm.caching import DualCache | |
user_api_key_cache = DualCache() | |
invalid_db_url = "postgresql://invalid:invalid@localhost:5432/nonexistent" | |
_old_db_url = os.getenv("DATABASE_URL") | |
os.environ["DATABASE_URL"] = invalid_db_url | |
with pytest.raises(Exception) as exc_info: | |
await ProxyStartupEvent._setup_prisma_client( | |
database_url=invalid_db_url, | |
proxy_logging_obj=ProxyLogging(user_api_key_cache=user_api_key_cache), | |
user_api_key_cache=user_api_key_cache, | |
) | |
print("GOT EXCEPTION=", exc_info) | |
assert "httpx.ConnectError" in str(exc_info.value) | |
# # Verify the error message indicates a database connection issue | |
# assert any(x in str(exc_info.value).lower() for x in ["database", "connection", "authentication"]) | |
if _old_db_url: | |
os.environ["DATABASE_URL"] = _old_db_url | |
async def test_get_ui_settings_spend_logs_threshold(): | |
""" | |
Test that get_ui_settings correctly sets DISABLE_EXPENSIVE_DB_QUERIES based on spend_logs_row_count threshold | |
""" | |
from litellm.proxy.management_endpoints.ui_sso import get_ui_settings | |
from litellm.proxy.proxy_server import proxy_state | |
from fastapi import Request | |
from litellm.constants import MAX_SPENDLOG_ROWS_TO_QUERY | |
# Create a mock request | |
mock_request = Request( | |
scope={ | |
"type": "http", | |
"headers": [], | |
"method": "GET", | |
"scheme": "http", | |
"server": ("testserver", 80), | |
"path": "/sso/get/ui_settings", | |
"query_string": b"", | |
} | |
) | |
# Test case 1: When spend_logs_row_count > MAX_SPENDLOG_ROWS_TO_QUERY | |
proxy_state.set_proxy_state_variable( | |
"spend_logs_row_count", MAX_SPENDLOG_ROWS_TO_QUERY + 1 | |
) | |
response = await get_ui_settings(mock_request) | |
print("response from get_ui_settings", json.dumps(response, indent=4)) | |
assert response["DISABLE_EXPENSIVE_DB_QUERIES"] is True | |
assert response["NUM_SPEND_LOGS_ROWS"] == MAX_SPENDLOG_ROWS_TO_QUERY + 1 | |
# Test case 2: When spend_logs_row_count < MAX_SPENDLOG_ROWS_TO_QUERY | |
proxy_state.set_proxy_state_variable( | |
"spend_logs_row_count", MAX_SPENDLOG_ROWS_TO_QUERY - 1 | |
) | |
response = await get_ui_settings(mock_request) | |
print("response from get_ui_settings", json.dumps(response, indent=4)) | |
assert response["DISABLE_EXPENSIVE_DB_QUERIES"] is False | |
assert response["NUM_SPEND_LOGS_ROWS"] == MAX_SPENDLOG_ROWS_TO_QUERY - 1 | |
# Test case 3: Edge case - exactly MAX_SPENDLOG_ROWS_TO_QUERY | |
proxy_state.set_proxy_state_variable( | |
"spend_logs_row_count", MAX_SPENDLOG_ROWS_TO_QUERY | |
) | |
response = await get_ui_settings(mock_request) | |
print("response from get_ui_settings", json.dumps(response, indent=4)) | |
assert response["DISABLE_EXPENSIVE_DB_QUERIES"] is False | |
assert response["NUM_SPEND_LOGS_ROWS"] == MAX_SPENDLOG_ROWS_TO_QUERY | |
# Clean up | |
proxy_state.set_proxy_state_variable("spend_logs_row_count", 0) | |
async def test_run_background_health_check_reflects_llm_model_list(monkeypatch): | |
""" | |
Test that _run_background_health_check reflects changes to llm_model_list in each health check iteration. | |
""" | |
import litellm.proxy.proxy_server as proxy_server | |
import copy | |
test_model_list_1 = [{"model_name": "model-a"}] | |
test_model_list_2 = [{"model_name": "model-b"}] | |
called_model_lists = [] | |
async def fake_perform_health_check(model_list, details): | |
called_model_lists.append(copy.deepcopy(model_list)) | |
return (["healthy"], ["unhealthy"]) | |
monkeypatch.setattr(proxy_server, "health_check_interval", 1) | |
monkeypatch.setattr(proxy_server, "health_check_details", None) | |
monkeypatch.setattr(proxy_server, "llm_model_list", copy.deepcopy(test_model_list_1)) | |
monkeypatch.setattr(proxy_server, "perform_health_check", fake_perform_health_check) | |
monkeypatch.setattr(proxy_server, "health_check_results", {}) | |
async def fake_sleep(interval): | |
raise asyncio.CancelledError() | |
monkeypatch.setattr(asyncio, "sleep", fake_sleep) | |
try: | |
await proxy_server._run_background_health_check() | |
except asyncio.CancelledError: | |
pass | |
monkeypatch.setattr(proxy_server, "llm_model_list", copy.deepcopy(test_model_list_2)) | |
try: | |
await proxy_server._run_background_health_check() | |
except asyncio.CancelledError: | |
pass | |
assert len(called_model_lists) >= 2 | |
assert called_model_lists[0] == test_model_list_1 | |
assert called_model_lists[1] == test_model_list_2 | |
def test_get_timeout_from_request(): | |
from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup | |
headers = { | |
"x-litellm-timeout": "90", | |
} | |
timeout = LiteLLMProxyRequestSetup._get_timeout_from_request(headers) | |
assert timeout == 90 | |
headers = { | |
"x-litellm-timeout": "90.5", | |
} | |
timeout = LiteLLMProxyRequestSetup._get_timeout_from_request(headers) | |
assert timeout == 90.5 | |