mirror of
https://github.com/BerriAI/litellm.git
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cdda7c243f
* unit testig for prometheus * unit testing for success metrics * use 1 helper for _increment_token_metrics * use helper for _increment_remaining_budget_metrics * use _increment_remaining_budget_metrics * use _increment_top_level_request_and_spend_metrics * use helper for _set_latency_metrics * remove noqa violation * fix test prometheus * test prometheus * unit testing for all prometheus helper functions * fix prom unit tests * fix unit tests prometheus * fix unit test prom
344 lines
12 KiB
Python
344 lines
12 KiB
Python
import io
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import os
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import sys
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sys.path.insert(0, os.path.abspath("../.."))
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import asyncio
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import logging
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import uuid
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import pytest
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from prometheus_client import REGISTRY, CollectorRegistry
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import litellm
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from litellm import completion
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from litellm._logging import verbose_logger
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from litellm.integrations.prometheus import PrometheusLogger
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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from litellm.types.utils import (
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StandardLoggingPayload,
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StandardLoggingMetadata,
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StandardLoggingHiddenParams,
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StandardLoggingModelInformation,
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)
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import pytest
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from unittest.mock import MagicMock, patch
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from datetime import datetime, timedelta
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from litellm.integrations.prometheus import PrometheusLogger
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verbose_logger.setLevel(logging.DEBUG)
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litellm.set_verbose = True
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import time
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@pytest.fixture
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def prometheus_logger():
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collectors = list(REGISTRY._collector_to_names.keys())
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for collector in collectors:
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REGISTRY.unregister(collector)
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return PrometheusLogger()
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def create_standard_logging_payload() -> StandardLoggingPayload:
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return StandardLoggingPayload(
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id="test_id",
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call_type="completion",
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response_cost=0.1,
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response_cost_failure_debug_info=None,
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status="success",
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total_tokens=30,
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prompt_tokens=20,
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completion_tokens=10,
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startTime=1234567890.0,
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endTime=1234567891.0,
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completionStartTime=1234567890.5,
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model_map_information=StandardLoggingModelInformation(
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model_map_key="gpt-3.5-turbo", model_map_value=None
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),
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model="gpt-3.5-turbo",
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model_id="model-123",
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model_group="openai-gpt",
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api_base="https://api.openai.com",
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metadata=StandardLoggingMetadata(
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user_api_key_hash="test_hash",
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user_api_key_alias="test_alias",
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user_api_key_team_id="test_team",
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user_api_key_user_id="test_user",
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user_api_key_team_alias="test_team_alias",
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spend_logs_metadata=None,
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requester_ip_address="127.0.0.1",
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requester_metadata=None,
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),
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cache_hit=False,
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cache_key=None,
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saved_cache_cost=0.0,
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request_tags=[],
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end_user=None,
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requester_ip_address="127.0.0.1",
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messages=[{"role": "user", "content": "Hello, world!"}],
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response={"choices": [{"message": {"content": "Hi there!"}}]},
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error_str=None,
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model_parameters={"stream": True},
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hidden_params=StandardLoggingHiddenParams(
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model_id="model-123",
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cache_key=None,
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api_base="https://api.openai.com",
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response_cost="0.1",
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additional_headers=None,
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),
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)
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def test_safe_get_remaining_budget(prometheus_logger):
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assert prometheus_logger._safe_get_remaining_budget(100, 30) == 70
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assert prometheus_logger._safe_get_remaining_budget(100, None) == 100
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assert prometheus_logger._safe_get_remaining_budget(None, 30) == float("inf")
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assert prometheus_logger._safe_get_remaining_budget(None, None) == float("inf")
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@pytest.mark.asyncio
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async def test_async_log_success_event(prometheus_logger):
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standard_logging_object = create_standard_logging_payload()
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kwargs = {
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"model": "gpt-3.5-turbo",
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"litellm_params": {
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"metadata": {
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"user_api_key": "test_key",
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"user_api_key_user_id": "test_user",
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"user_api_key_team_id": "test_team",
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}
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},
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"start_time": datetime.now(),
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"completion_start_time": datetime.now(),
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"api_call_start_time": datetime.now(),
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"end_time": datetime.now() + timedelta(seconds=1),
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"standard_logging_object": standard_logging_object,
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}
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response_obj = MagicMock()
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# Mock the prometheus client methods
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# High Level Metrics - request/spend
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prometheus_logger.litellm_requests_metric = MagicMock()
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prometheus_logger.litellm_spend_metric = MagicMock()
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# Token Metrics
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prometheus_logger.litellm_tokens_metric = MagicMock()
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prometheus_logger.litellm_input_tokens_metric = MagicMock()
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prometheus_logger.litellm_output_tokens_metric = MagicMock()
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# Remaining Budget Metrics
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prometheus_logger.litellm_remaining_team_budget_metric = MagicMock()
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prometheus_logger.litellm_remaining_api_key_budget_metric = MagicMock()
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# Virtual Key Rate limit Metrics
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prometheus_logger.litellm_remaining_api_key_requests_for_model = MagicMock()
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prometheus_logger.litellm_remaining_api_key_tokens_for_model = MagicMock()
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# Latency Metrics
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prometheus_logger.litellm_llm_api_time_to_first_token_metric = MagicMock()
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prometheus_logger.litellm_llm_api_latency_metric = MagicMock()
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prometheus_logger.litellm_request_total_latency_metric = MagicMock()
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await prometheus_logger.async_log_success_event(
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kwargs, response_obj, kwargs["start_time"], kwargs["end_time"]
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)
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# Assert that the metrics were incremented
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prometheus_logger.litellm_requests_metric.labels.assert_called()
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prometheus_logger.litellm_spend_metric.labels.assert_called()
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# Token Metrics
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prometheus_logger.litellm_tokens_metric.labels.assert_called()
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prometheus_logger.litellm_input_tokens_metric.labels.assert_called()
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prometheus_logger.litellm_output_tokens_metric.labels.assert_called()
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# Remaining Budget Metrics
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prometheus_logger.litellm_remaining_team_budget_metric.labels.assert_called()
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prometheus_logger.litellm_remaining_api_key_budget_metric.labels.assert_called()
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# Virtual Key Rate limit Metrics
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prometheus_logger.litellm_remaining_api_key_requests_for_model.labels.assert_called()
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prometheus_logger.litellm_remaining_api_key_tokens_for_model.labels.assert_called()
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# Latency Metrics
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prometheus_logger.litellm_llm_api_time_to_first_token_metric.labels.assert_called()
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prometheus_logger.litellm_llm_api_latency_metric.labels.assert_called()
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prometheus_logger.litellm_request_total_latency_metric.labels.assert_called()
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def test_increment_token_metrics(prometheus_logger):
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"""
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Test the increment_token_metrics method
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input, output, and total tokens metrics are incremented by the values in the standard logging payload
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"""
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prometheus_logger.litellm_tokens_metric = MagicMock()
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prometheus_logger.litellm_input_tokens_metric = MagicMock()
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prometheus_logger.litellm_output_tokens_metric = MagicMock()
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standard_logging_payload = create_standard_logging_payload()
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standard_logging_payload["total_tokens"] = 100
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standard_logging_payload["prompt_tokens"] = 50
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standard_logging_payload["completion_tokens"] = 50
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prometheus_logger._increment_token_metrics(
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standard_logging_payload,
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end_user_id="user1",
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user_api_key="key1",
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user_api_key_alias="alias1",
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model="gpt-3.5-turbo",
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user_api_team="team1",
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user_api_team_alias="team_alias1",
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user_id="user1",
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)
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prometheus_logger.litellm_tokens_metric.labels.assert_called_once_with(
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"user1", "key1", "alias1", "gpt-3.5-turbo", "team1", "team_alias1", "user1"
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)
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prometheus_logger.litellm_tokens_metric.labels().inc.assert_called_once_with(100)
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prometheus_logger.litellm_input_tokens_metric.labels.assert_called_once_with(
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"user1", "key1", "alias1", "gpt-3.5-turbo", "team1", "team_alias1", "user1"
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)
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prometheus_logger.litellm_input_tokens_metric.labels().inc.assert_called_once_with(
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50
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)
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prometheus_logger.litellm_output_tokens_metric.labels.assert_called_once_with(
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"user1", "key1", "alias1", "gpt-3.5-turbo", "team1", "team_alias1", "user1"
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)
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prometheus_logger.litellm_output_tokens_metric.labels().inc.assert_called_once_with(
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50
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)
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def test_increment_remaining_budget_metrics(prometheus_logger):
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"""
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Test the increment_remaining_budget_metrics method
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team and api key budget metrics are set to the difference between max budget and spend
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"""
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prometheus_logger.litellm_remaining_team_budget_metric = MagicMock()
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prometheus_logger.litellm_remaining_api_key_budget_metric = MagicMock()
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litellm_params = {
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"metadata": {
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"user_api_key_team_spend": 50,
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"user_api_key_team_max_budget": 100,
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"user_api_key_spend": 25,
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"user_api_key_max_budget": 75,
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}
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}
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prometheus_logger._increment_remaining_budget_metrics(
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user_api_team="team1",
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user_api_team_alias="team_alias1",
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user_api_key="key1",
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user_api_key_alias="alias1",
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litellm_params=litellm_params,
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)
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prometheus_logger.litellm_remaining_team_budget_metric.labels.assert_called_once_with(
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"team1", "team_alias1"
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)
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prometheus_logger.litellm_remaining_team_budget_metric.labels().set.assert_called_once_with(
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50
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)
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prometheus_logger.litellm_remaining_api_key_budget_metric.labels.assert_called_once_with(
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"key1", "alias1"
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)
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prometheus_logger.litellm_remaining_api_key_budget_metric.labels().set.assert_called_once_with(
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50
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)
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def test_set_latency_metrics(prometheus_logger):
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"""
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Test the set_latency_metrics method
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time to first token, llm api latency, and request total latency metrics are set to the values in the standard logging payload
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"""
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standard_logging_payload = create_standard_logging_payload()
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standard_logging_payload["model_parameters"] = {"stream": True}
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prometheus_logger.litellm_llm_api_time_to_first_token_metric = MagicMock()
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prometheus_logger.litellm_llm_api_latency_metric = MagicMock()
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prometheus_logger.litellm_request_total_latency_metric = MagicMock()
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now = datetime.now()
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kwargs = {
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"end_time": now, # when the request ends
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"start_time": now - timedelta(seconds=2), # when the request starts
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"api_call_start_time": now - timedelta(seconds=1.5), # when the api call starts
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"completion_start_time": now
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- timedelta(seconds=1), # when the completion starts
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}
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prometheus_logger._set_latency_metrics(
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kwargs=kwargs,
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model="gpt-3.5-turbo",
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user_api_key="key1",
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user_api_key_alias="alias1",
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user_api_team="team1",
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user_api_team_alias="team_alias1",
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standard_logging_payload=standard_logging_payload,
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)
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# completion_start_time - api_call_start_time
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prometheus_logger.litellm_llm_api_time_to_first_token_metric.labels.assert_called_once_with(
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"gpt-3.5-turbo", "key1", "alias1", "team1", "team_alias1"
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)
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prometheus_logger.litellm_llm_api_time_to_first_token_metric.labels().observe.assert_called_once_with(
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0.5
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)
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# end_time - api_call_start_time
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prometheus_logger.litellm_llm_api_latency_metric.labels.assert_called_once_with(
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"gpt-3.5-turbo", "key1", "alias1", "team1", "team_alias1"
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)
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prometheus_logger.litellm_llm_api_latency_metric.labels().observe.assert_called_once_with(
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1.5
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)
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# total latency for the request
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prometheus_logger.litellm_request_total_latency_metric.labels.assert_called_once_with(
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"gpt-3.5-turbo", "key1", "alias1", "team1", "team_alias1"
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)
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prometheus_logger.litellm_request_total_latency_metric.labels().observe.assert_called_once_with(
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2.0
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)
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def test_increment_top_level_request_and_spend_metrics(prometheus_logger):
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"""
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Test the increment_top_level_request_and_spend_metrics method
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- litellm_requests_metric is incremented by 1
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- litellm_spend_metric is incremented by the response cost in the standard logging payload
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"""
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prometheus_logger.litellm_requests_metric = MagicMock()
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prometheus_logger.litellm_spend_metric = MagicMock()
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prometheus_logger._increment_top_level_request_and_spend_metrics(
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end_user_id="user1",
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user_api_key="key1",
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user_api_key_alias="alias1",
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model="gpt-3.5-turbo",
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user_api_team="team1",
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user_api_team_alias="team_alias1",
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user_id="user1",
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response_cost=0.1,
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)
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prometheus_logger.litellm_requests_metric.labels.assert_called_once_with(
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"user1", "key1", "alias1", "gpt-3.5-turbo", "team1", "team_alias1", "user1"
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)
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prometheus_logger.litellm_requests_metric.labels().inc.assert_called_once()
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prometheus_logger.litellm_spend_metric.labels.assert_called_once_with(
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"user1", "key1", "alias1", "gpt-3.5-turbo", "team1", "team_alias1", "user1"
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)
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prometheus_logger.litellm_spend_metric.labels().inc.assert_called_once_with(0.1)
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