Files
litellm/tests/logging_callback_tests/test_log_db_redis_services.py
T
Krish Dholakia 61b35c12bb LiteLLM Minor Fixes & Improvements (12/05/2024) (#7037)
* fix(together_ai/chat): only return response_format + tools for supported models

Fixes https://github.com/BerriAI/litellm/issues/6972

* feat(bedrock/rerank): initial working commit for bedrock rerank api support

Closes https://github.com/BerriAI/litellm/issues/7021

* feat(bedrock/rerank): async bedrock rerank api support

Addresses https://github.com/BerriAI/litellm/issues/7021

* build(model_prices_and_context_window.json): add 'supports_prompt_caching' for bedrock models + cleanup cross-region from model list (duplicate information - lead to inconsistencies )

* docs(json_mode.md): clarify model support for json schema

Closes https://github.com/BerriAI/litellm/issues/6998

* fix(_service_logger.py): handle dd callback in list

ensure failed spend tracking is logged to datadog

* feat(converse_transformation.py): translate from anthropic format to bedrock format

Closes https://github.com/BerriAI/litellm/issues/7030

* fix: fix linting errors

* test: fix test
2024-12-05 00:02:31 -08:00

207 lines
7.2 KiB
Python

import io
import os
import sys
sys.path.insert(0, os.path.abspath("../.."))
import asyncio
import gzip
import json
import logging
import time
from unittest.mock import AsyncMock, patch
import pytest
import litellm
from litellm import completion
from litellm._logging import verbose_logger
from litellm.proxy.utils import log_db_metrics, ServiceTypes
from datetime import datetime
import httpx
from prisma.errors import ClientNotConnectedError
# Test async function to decorate
@log_db_metrics
async def sample_db_function(*args, **kwargs):
return "success"
@log_db_metrics
async def sample_proxy_function(*args, **kwargs):
return "success"
@pytest.mark.asyncio
async def test_log_db_metrics_success():
# Mock the proxy_logging_obj
with patch("litellm.proxy.proxy_server.proxy_logging_obj") as mock_proxy_logging:
# Setup mock
mock_proxy_logging.service_logging_obj.async_service_success_hook = AsyncMock()
# Call the decorated function
result = await sample_db_function(parent_otel_span="test_span")
# Assertions
assert result == "success"
mock_proxy_logging.service_logging_obj.async_service_success_hook.assert_called_once()
call_args = (
mock_proxy_logging.service_logging_obj.async_service_success_hook.call_args[
1
]
)
assert call_args["service"] == ServiceTypes.DB
assert call_args["call_type"] == "sample_db_function"
assert call_args["parent_otel_span"] == "test_span"
assert isinstance(call_args["duration"], float)
assert isinstance(call_args["start_time"], datetime)
assert isinstance(call_args["end_time"], datetime)
assert "function_name" in call_args["event_metadata"]
@pytest.mark.asyncio
async def test_log_db_metrics_duration():
# Mock the proxy_logging_obj
with patch("litellm.proxy.proxy_server.proxy_logging_obj") as mock_proxy_logging:
# Setup mock
mock_proxy_logging.service_logging_obj.async_service_success_hook = AsyncMock()
# Add a delay to the function to test duration
@log_db_metrics
async def delayed_function(**kwargs):
await asyncio.sleep(1) # 1 second delay
return "success"
# Call the decorated function
start = time.time()
result = await delayed_function(parent_otel_span="test_span")
end = time.time()
# Get the actual duration
actual_duration = end - start
# Get the logged duration from the mock call
call_args = (
mock_proxy_logging.service_logging_obj.async_service_success_hook.call_args[
1
]
)
logged_duration = call_args["duration"]
# Assert the logged duration is approximately equal to actual duration (within 0.1 seconds)
assert abs(logged_duration - actual_duration) < 0.1
assert result == "success"
@pytest.mark.asyncio
async def test_log_db_metrics_failure():
"""
should log a failure if a prisma error is raised
"""
# Mock the proxy_logging_obj
from prisma.errors import ClientNotConnectedError
with patch("litellm.proxy.proxy_server.proxy_logging_obj") as mock_proxy_logging:
# Setup mock
mock_proxy_logging.service_logging_obj.async_service_failure_hook = AsyncMock()
# Create a failing function
@log_db_metrics
async def failing_function(**kwargs):
raise ClientNotConnectedError()
# Call the decorated function and expect it to raise
with pytest.raises(ClientNotConnectedError) as exc_info:
await failing_function(parent_otel_span="test_span")
# Assertions
assert "Client is not connected to the query engine" in str(exc_info.value)
mock_proxy_logging.service_logging_obj.async_service_failure_hook.assert_called_once()
call_args = (
mock_proxy_logging.service_logging_obj.async_service_failure_hook.call_args[
1
]
)
assert call_args["service"] == ServiceTypes.DB
assert call_args["call_type"] == "failing_function"
assert call_args["parent_otel_span"] == "test_span"
assert isinstance(call_args["duration"], float)
assert isinstance(call_args["start_time"], datetime)
assert isinstance(call_args["end_time"], datetime)
assert isinstance(call_args["error"], ClientNotConnectedError)
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception,should_log",
[
(ValueError("Generic error"), False),
(KeyError("Missing key"), False),
(TypeError("Type error"), False),
(httpx.ConnectError("Failed to connect"), True),
(httpx.TimeoutException("Request timed out"), True),
(ClientNotConnectedError(), True), # Prisma error
],
)
async def test_log_db_metrics_failure_error_types(exception, should_log):
"""
Why Test?
Users were seeing that non-DB errors were being logged as DB Service Failures
Example a failure to read a value from cache was being logged as a DB Service Failure
Parameterized test to verify:
- DB-related errors (Prisma, httpx) are logged as service failures
- Non-DB errors (ValueError, KeyError, etc.) are not logged
"""
with patch("litellm.proxy.proxy_server.proxy_logging_obj") as mock_proxy_logging:
mock_proxy_logging.service_logging_obj.async_service_failure_hook = AsyncMock()
@log_db_metrics
async def failing_function(**kwargs):
raise exception
# Call the function and expect it to raise the exception
with pytest.raises(type(exception)):
await failing_function(parent_otel_span="test_span")
if should_log:
# Assert failure was logged for DB-related errors
mock_proxy_logging.service_logging_obj.async_service_failure_hook.assert_called_once()
call_args = mock_proxy_logging.service_logging_obj.async_service_failure_hook.call_args[
1
]
assert call_args["service"] == ServiceTypes.DB
assert call_args["call_type"] == "failing_function"
assert call_args["parent_otel_span"] == "test_span"
assert isinstance(call_args["duration"], float)
assert isinstance(call_args["start_time"], datetime)
assert isinstance(call_args["end_time"], datetime)
assert isinstance(call_args["error"], type(exception))
else:
# Assert failure was NOT logged for non-DB errors
mock_proxy_logging.service_logging_obj.async_service_failure_hook.assert_not_called()
@pytest.mark.asyncio
async def test_dd_log_db_spend_failure_metrics():
from litellm._service_logger import ServiceLogging
from litellm.integrations.datadog.datadog import DataDogLogger
dd_logger = DataDogLogger()
with patch.object(dd_logger, "async_service_failure_hook", new_callable=AsyncMock):
service_logging_obj = ServiceLogging()
litellm.service_callback = [dd_logger]
await service_logging_obj.async_service_failure_hook(
service=ServiceTypes.DB,
call_type="test_call_type",
error="test_error",
duration=1.0,
)