forked from phoenix/litellm-mirror
refactor: move all testing to top-level of repo
Closes https://github.com/BerriAI/litellm/issues/486
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213 changed files with 74 additions and 217 deletions
167
tests/local_testing/test_prometheus.py
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167
tests/local_testing/test_prometheus.py
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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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verbose_logger.setLevel(logging.DEBUG)
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litellm.set_verbose = True
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import time
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@pytest.mark.skip(reason="duplicate test of logging with callbacks")
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@pytest.mark.asyncio()
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async def test_async_prometheus_success_logging():
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from litellm.integrations.prometheus import PrometheusLogger
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pl = PrometheusLogger()
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run_id = str(uuid.uuid4())
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litellm.set_verbose = True
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litellm.callbacks = [pl]
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response = await litellm.acompletion(
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model="claude-instant-1.2",
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messages=[{"role": "user", "content": "what llm are u"}],
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max_tokens=10,
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mock_response="hi",
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temperature=0.2,
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metadata={
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"id": run_id,
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"tags": ["tag1", "tag2"],
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"user_api_key": "6eb81e014497d89f3cc1aa9da7c2b37bda6b7fea68e4b710d33d94201e68970c",
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"user_api_key_alias": "ishaans-prometheus-key",
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"user_api_end_user_max_budget": None,
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"litellm_api_version": "1.40.19",
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"global_max_parallel_requests": None,
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"user_api_key_user_id": "admin",
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"user_api_key_org_id": None,
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"user_api_key_team_id": "dbe2f686-a686-4896-864a-4c3924458709",
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"user_api_key_team_alias": "testing-team",
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},
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)
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print(response)
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await asyncio.sleep(3)
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# get prometheus logger
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test_prometheus_logger = pl
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print("done with success request")
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print(
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"vars of test_prometheus_logger",
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vars(test_prometheus_logger.litellm_requests_metric),
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)
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# Get the metrics
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metrics = {}
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for metric in REGISTRY.collect():
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for sample in metric.samples:
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metrics[sample.name] = sample.value
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print("metrics from prometheus", metrics)
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assert metrics["litellm_requests_metric_total"] == 1.0
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assert metrics["litellm_total_tokens_total"] == 30.0
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assert metrics["litellm_deployment_success_responses_total"] == 1.0
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assert metrics["litellm_deployment_total_requests_total"] == 1.0
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assert metrics["litellm_deployment_latency_per_output_token_bucket"] == 1.0
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@pytest.mark.asyncio()
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async def test_async_prometheus_success_logging_with_callbacks():
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pl = PrometheusLogger()
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run_id = str(uuid.uuid4())
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litellm.set_verbose = True
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litellm.success_callback = []
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litellm.failure_callback = []
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litellm.callbacks = [pl]
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# Get initial metric values
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initial_metrics = {}
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for metric in REGISTRY.collect():
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for sample in metric.samples:
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initial_metrics[sample.name] = sample.value
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response = await litellm.acompletion(
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model="claude-instant-1.2",
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messages=[{"role": "user", "content": "what llm are u"}],
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max_tokens=10,
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mock_response="hi",
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temperature=0.2,
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metadata={
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"id": run_id,
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"tags": ["tag1", "tag2"],
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"user_api_key": "6eb81e014497d89f3cc1aa9da7c2b37bda6b7fea68e4b710d33d94201e68970c",
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"user_api_key_alias": "ishaans-prometheus-key",
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"user_api_end_user_max_budget": None,
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"litellm_api_version": "1.40.19",
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"global_max_parallel_requests": None,
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"user_api_key_user_id": "admin",
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"user_api_key_org_id": None,
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"user_api_key_team_id": "dbe2f686-a686-4896-864a-4c3924458709",
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"user_api_key_team_alias": "testing-team",
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},
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)
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print(response)
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await asyncio.sleep(3)
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# get prometheus logger
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test_prometheus_logger = pl
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print("done with success request")
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print(
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"vars of test_prometheus_logger",
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vars(test_prometheus_logger.litellm_requests_metric),
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)
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# Get the updated metrics
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updated_metrics = {}
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for metric in REGISTRY.collect():
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for sample in metric.samples:
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updated_metrics[sample.name] = sample.value
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print("metrics from prometheus", updated_metrics)
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# Assert the delta for each metric
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assert (
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updated_metrics["litellm_requests_metric_total"]
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- initial_metrics.get("litellm_requests_metric_total", 0)
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== 1.0
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)
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assert (
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updated_metrics["litellm_total_tokens_total"]
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- initial_metrics.get("litellm_total_tokens_total", 0)
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== 30.0
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)
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assert (
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updated_metrics["litellm_deployment_success_responses_total"]
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- initial_metrics.get("litellm_deployment_success_responses_total", 0)
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== 1.0
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)
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assert (
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updated_metrics["litellm_deployment_total_requests_total"]
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- initial_metrics.get("litellm_deployment_total_requests_total", 0)
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== 1.0
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)
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assert (
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updated_metrics["litellm_deployment_latency_per_output_token_bucket"]
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- initial_metrics.get("litellm_deployment_latency_per_output_token_bucket", 0)
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== 1.0
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)
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