litellm/tests/proxy_unit_tests/test_search_api_logging.py
yuneng-jiang 6a0d03914c
test: drop the cwd-relative sys.path.insert calls from the test suite (#37802)
* test: drop the cwd-relative sys.path.insert calls from the test suite

TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.

Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.

Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.

* test: drop the duplicate imports the sys.path sweep exposed to F811

* test(pre-call-utils): restore the os import the new bedrock tests need
2026-08-22 09:25:58 -07:00

204 lines
7 KiB
Python

"""
Test search API logging and cost tracking in proxy.
Tests that search API requests are properly logged to LiteLLM_SpendLogs
with correct fields populated (call_type, model, custom_llm_provider,
model_group, spend, etc.)
"""
import asyncio
import os
import time
from datetime import datetime
from unittest.mock import AsyncMock, patch
import pytest
import litellm
from litellm import Router
from litellm.caching import DualCache
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.hooks.proxy_track_cost_callback import _ProxyDBLogger
from litellm.proxy.spend_tracking.spend_management_endpoints import view_spend_logs
from litellm.proxy.utils import ProxyLogging, hash_token, update_spend
from litellm.llms.base_llm.search.transformation import SearchResponse, SearchResult
@pytest.fixture
def prisma_client():
from litellm.proxy import proxy_server
from litellm.proxy.proxy_cli import append_query_params
from litellm.proxy.utils import PrismaClient
params = {"connection_limit": 100, "pool_timeout": 60}
database_url = os.getenv("DATABASE_URL")
if database_url is None:
pytest.skip("DATABASE_URL not set")
modified_url = append_query_params(database_url, params)
os.environ["DATABASE_URL"] = modified_url
user_api_key_cache = DualCache()
proxy_logging_obj = ProxyLogging(user_api_key_cache=user_api_key_cache)
prisma_client = PrismaClient(
database_url=os.environ["DATABASE_URL"], proxy_logging_obj=proxy_logging_obj
)
proxy_server.litellm_proxy_budget_name = f"litellm-proxy-budget-{time.time()}"
proxy_server.user_custom_key_generate = None
return prisma_client
@pytest.mark.skip(reason="Requires reliable external DB connection (prisma).")
@pytest.mark.asyncio
async def test_search_api_logging_and_cost_tracking(prisma_client):
"""
Test that search API requests are logged with correct fields and cost tracking.
Verifies:
1. Search request creates a spend log entry
2. call_type is set to "asearch"
3. model is set to search_tool_name
4. custom_llm_provider is set correctly
5. model_group is set to search_tool_name
6. spend is calculated and logged
"""
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()
# Setup router with search tool
search_tool_name = "tavily-search"
search_provider = "tavily"
router = Router(model_list=[])
router.search_tools = [
{
"search_tool_name": search_tool_name,
"litellm_params": {
"search_provider": search_provider,
},
}
]
setattr(litellm.proxy.proxy_server, "llm_router", router)
# Generate a test API key
from litellm.proxy.management_endpoints.key_management_endpoints import (
generate_key_fn,
)
from litellm.proxy._types import GenerateKeyRequest
from litellm.proxy._types import LitellmUserRoles
user_api_key_dict = UserAPIKeyAuth(
user_role=LitellmUserRoles.PROXY_ADMIN,
api_key="sk-1234",
user_id="test_user",
)
key_request = GenerateKeyRequest(models=[], duration=None)
key_response = await generate_key_fn(
data=key_request, user_api_key_dict=user_api_key_dict
)
generated_key = key_response.key
user_id = key_response.user_id
# Create mock search response
mock_search_result = SearchResult(
title="Test Result",
url="https://example.com",
snippet="Test snippet",
)
mock_search_response = SearchResponse(
object="search",
results=[mock_search_result],
)
# Mock the search function to return our mock response
with patch("litellm.search.main.asearch", new_callable=AsyncMock) as mock_asearch:
mock_asearch.return_value = mock_search_response
# Setup proxy logging
user_api_key_cache = DualCache()
proxy_logging_obj = ProxyLogging(user_api_key_cache=user_api_key_cache)
setattr(litellm.proxy.proxy_server, "proxy_logging_obj", proxy_logging_obj)
# Call the track_cost_callback directly to simulate what happens after a search
proxy_db_logger = _ProxyDBLogger()
# Simulate the kwargs that would be passed from the search endpoint
request_id = "search_test_123"
kwargs = {
"call_type": "asearch",
"model": search_tool_name,
"custom_llm_provider": search_provider,
"litellm_call_id": request_id, # Set request_id in kwargs
"litellm_params": {
"metadata": {
"user_api_key": hash_token(generated_key),
"user_api_key_user_id": user_id,
"model_group": search_tool_name,
}
},
"metadata": {
"user_api_key": hash_token(generated_key),
"user_api_key_user_id": user_id,
"model_group": search_tool_name,
},
"response_cost": 0.008, # Mock cost for tavily search
}
# Set id on the response object
mock_search_response.id = request_id
await proxy_db_logger._PROXY_track_cost_callback(
kwargs=kwargs,
completion_response=mock_search_response,
start_time=datetime.now(),
end_time=datetime.now(),
)
# Wait for async operations
await asyncio.sleep(2)
await update_spend(
prisma_client=prisma_client,
db_writer_client=None,
proxy_logging_obj=proxy_logging_obj,
)
# Query spend logs
spend_logs = await view_spend_logs(
request_id=request_id,
user_api_key_dict=UserAPIKeyAuth(api_key=generated_key),
)
# Verify spend log was created
assert len(spend_logs) == 1, f"Expected 1 spend log, got {len(spend_logs)}"
spend_log = spend_logs[0]
# Verify all fields are populated correctly
assert spend_log.request_id == request_id
assert spend_log.call_type == "asearch"
assert spend_log.model == search_tool_name
assert spend_log.custom_llm_provider == search_provider
assert spend_log.model_group == search_tool_name
assert spend_log.spend == 0.008
# API key should be hashed (either the generated key or the one from metadata)
assert spend_log.api_key != "" # Should be populated
# Note: user field may be empty if not set in the request, but user_id should be in metadata
assert (
spend_log.metadata.get("user_api_key_user_id") == user_id
or spend_log.user == user_id
)
print(f"✅ Search API logging test passed!")
print(f" - call_type: {spend_log.call_type}")
print(f" - model: {spend_log.model}")
print(f" - custom_llm_provider: {spend_log.custom_llm_provider}")
print(f" - model_group: {spend_log.model_group}")
print(f" - spend: {spend_log.spend}")