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fix(prometheus.py): make prometheus work for multiple workers

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This commit is contained in:
Krrish Dholakia 2025-09-10 16:20:17 -07:00
parent a504c7dae3
commit a9fddbf4ad
5 changed files with 403 additions and 53 deletions
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298
enterprise/litellm_enterprise/integrations/prometheus.py
View File

@ -1,8 +1,11 @@
# used for /metrics endpoint on LiteLLM Proxy
#### What this does ####
# On success, log events to Prometheus
import os
import sys
import tempfile
from datetime import datetime, timedelta
from pathlib import Path
from typing import (
TYPE_CHECKING,
Any,
@ -16,6 +19,64 @@ from typing import (
cast,
)
# CRITICAL: Set up multiprocess mode BEFORE importing prometheus_client
# This must happen at module import time, not at class instantiation time
def _setup_early_multiprocess_mode():
"""Setup multiprocess mode at import time if needed."""
try:
# Check if we're in a multiprocess environment
num_workers = os.environ.get("NUM_WORKERS", "1")
is_multiprocess = False
try:
if int(num_workers) > 1:
is_multiprocess = True
except (ValueError, TypeError):
pass
# Check for gunicorn worker environment variables
if os.environ.get("GUNICORN_CMD_ARGS") or os.environ.get("GUNICORN_WORKER_ID"):
is_multiprocess = True
# Check if PROMETHEUS_MULTIPROC_DIR is explicitly set (admin override)
if os.environ.get("PROMETHEUS_MULTIPROC_DIR"):
is_multiprocess = True
if is_multiprocess:
existing_dir = os.environ.get("PROMETHEUS_MULTIPROC_DIR")
if not existing_dir:
# Set up multiprocess directory
multiproc_dir = os.path.join(
tempfile.gettempdir(), "litellm_prometheus_multiproc"
)
os.environ["PROMETHEUS_MULTIPROC_DIR"] = multiproc_dir
# Ensure the directory exists
Path(multiproc_dir).mkdir(parents=True, exist_ok=True)
verbose_logger.info(
f"Prometheus multiprocess mode auto-enabled with directory: {multiproc_dir}"
)
else:
# Directory already set, just ensure it exists
Path(existing_dir).mkdir(parents=True, exist_ok=True)
verbose_logger.info(
f"Using existing Prometheus multiprocess directory: {existing_dir}"
)
except PermissionError as e:
verbose_logger.warning(
f"Warning: Unable to create Prometheus multiprocess directory due to permission error. "
f"Running in non-root environment. Prometheus metrics may not work correctly in multiprocess mode. Error: {e}"
)
except Exception as e:
verbose_logger.warning(f"Warning: Failed to setup early multiprocess mode: {e}")
# Set up multiprocess mode before any prometheus imports
_setup_early_multiprocess_mode()
import litellm
from litellm._logging import print_verbose, verbose_logger
from litellm.integrations.custom_logger import CustomLogger
@ -44,6 +105,18 @@ class PrometheusLogger(CustomLogger):
# Always initialize label_filters, even for non-premium users
self.label_filters = self._parse_prometheus_config()
# Initialize multiprocess mode for Prometheus metrics to handle multiple workers
self._setup_multiprocess_mode()
# Debug: Check if multiprocess mode is active
multiproc_dir = os.environ.get("PROMETHEUS_MULTIPROC_DIR")
if multiproc_dir:
verbose_logger.info(
f"Prometheus multiprocess mode active with directory: {multiproc_dir}"
)
else:
verbose_logger.info("Prometheus running in single-process mode")
if premium_user is not True:
verbose_logger.warning(
f"🚨🚨🚨 Prometheus Metrics is on LiteLLM Enterprise\n🚨 {CommonProxyErrors.not_premium_user.value}"
@ -102,7 +175,9 @@ class PrometheusLogger(CustomLogger):
# "team",
# "team_alias",
# ],
labelnames=self.get_labels_for_metric("litellm_llm_api_time_to_first_token_metric"),
labelnames=self.get_labels_for_metric(
"litellm_llm_api_time_to_first_token_metric"
),
buckets=LATENCY_BUCKETS,
)
@ -132,47 +207,52 @@ class PrometheusLogger(CustomLogger):
labelnames=self.get_labels_for_metric("litellm_output_tokens_metric"),
)
# Remaining Budget for Team
# Remaining Budget for Team (use 'mostrecent' for multiprocess mode)
self.litellm_remaining_team_budget_metric = self._gauge_factory(
"litellm_remaining_team_budget_metric",
"Remaining budget for team",
labelnames=self.get_labels_for_metric(
"litellm_remaining_team_budget_metric"
),
multiprocess_mode="mostrecent",
)
# Max Budget for Team
# Max Budget for Team (use 'mostrecent' for multiprocess mode)
self.litellm_team_max_budget_metric = self._gauge_factory(
"litellm_team_max_budget_metric",
"Maximum budget set for team",
labelnames=self.get_labels_for_metric("litellm_team_max_budget_metric"),
multiprocess_mode="mostrecent",
)
# Team Budget Reset At
# Team Budget Reset At (use 'mostrecent' for multiprocess mode)
self.litellm_team_budget_remaining_hours_metric = self._gauge_factory(
"litellm_team_budget_remaining_hours_metric",
"Remaining days for team budget to be reset",
labelnames=self.get_labels_for_metric(
"litellm_team_budget_remaining_hours_metric"
),
multiprocess_mode="mostrecent",
)
# Remaining Budget for API Key
# Remaining Budget for API Key (use 'mostrecent' for multiprocess mode)
self.litellm_remaining_api_key_budget_metric = self._gauge_factory(
"litellm_remaining_api_key_budget_metric",
"Remaining budget for api key",
labelnames=self.get_labels_for_metric(
"litellm_remaining_api_key_budget_metric"
),
multiprocess_mode="mostrecent",
)
# Max Budget for API Key
# Max Budget for API Key (use 'mostrecent' for multiprocess mode)
self.litellm_api_key_max_budget_metric = self._gauge_factory(
"litellm_api_key_max_budget_metric",
"Maximum budget set for api key",
labelnames=self.get_labels_for_metric(
"litellm_api_key_max_budget_metric"
),
multiprocess_mode="mostrecent",
)
self.litellm_api_key_budget_remaining_hours_metric = self._gauge_factory(
@ -181,36 +261,40 @@ class PrometheusLogger(CustomLogger):
labelnames=self.get_labels_for_metric(
"litellm_api_key_budget_remaining_hours_metric"
),
multiprocess_mode="mostrecent",
)
########################################
# LiteLLM Virtual API KEY metrics
########################################
# Remaining MODEL RPM limit for API Key
# Remaining MODEL RPM limit for API Key (use 'mostrecent' for multiprocess mode)
self.litellm_remaining_api_key_requests_for_model = self._gauge_factory(
"litellm_remaining_api_key_requests_for_model",
"Remaining Requests API Key can make for model (model based rpm limit on key)",
labelnames=["hashed_api_key", "api_key_alias", "model"],
multiprocess_mode="mostrecent",
)
# Remaining MODEL TPM limit for API Key
# Remaining MODEL TPM limit for API Key (use 'mostrecent' for multiprocess mode)
self.litellm_remaining_api_key_tokens_for_model = self._gauge_factory(
"litellm_remaining_api_key_tokens_for_model",
"Remaining Tokens API Key can make for model (model based tpm limit on key)",
labelnames=["hashed_api_key", "api_key_alias", "model"],
multiprocess_mode="mostrecent",
)
########################################
# LLM API Deployment Metrics / analytics
########################################
# Remaining Rate Limit for model
# Remaining Rate Limit for model (use 'mostrecent' for multiprocess mode)
self.litellm_remaining_requests_metric = self._gauge_factory(
"litellm_remaining_requests",
"LLM Deployment Analytics - remaining requests for model, returned from LLM API Provider",
labelnames=self.get_labels_for_metric(
"litellm_remaining_requests_metric"
),
multiprocess_mode="mostrecent",
)
self.litellm_remaining_tokens_metric = self._gauge_factory(
@ -219,6 +303,7 @@ class PrometheusLogger(CustomLogger):
labelnames=self.get_labels_for_metric(
"litellm_remaining_tokens_metric"
),
multiprocess_mode="mostrecent",
)
self.litellm_overhead_latency_metric = self._histogram_factory(
@ -229,25 +314,27 @@ class PrometheusLogger(CustomLogger):
),
buckets=LATENCY_BUCKETS,
)
# llm api provider budget metrics
# llm api provider budget metrics (use 'mostrecent' for multiprocess mode)
self.litellm_provider_remaining_budget_metric = self._gauge_factory(
"litellm_provider_remaining_budget_metric",
"Remaining budget for provider - used when you set provider budget limits",
labelnames=["api_provider"],
multiprocess_mode="mostrecent",
)
# Metric for deployment state
# Metric for deployment state (use 'mostrecent' for multiprocess mode)
self.litellm_deployment_state = self._gauge_factory(
"litellm_deployment_state",
"LLM Deployment Analytics - The state of the deployment: 0 = healthy, 1 = partial outage, 2 = complete outage",
labelnames=self.get_labels_for_metric("litellm_deployment_state")
labelnames=self.get_labels_for_metric("litellm_deployment_state"),
multiprocess_mode="mostrecent",
)
self.litellm_deployment_cooled_down = self._counter_factory(
"litellm_deployment_cooled_down",
"LLM Deployment Analytics - Number of times a deployment has been cooled down by LiteLLM load balancing logic. exception_status is the status of the exception that caused the deployment to be cooled down",
# labelnames=_logged_llm_labels + [EXCEPTION_STATUS],
labelnames=self.get_labels_for_metric("litellm_deployment_cooled_down")
labelnames=self.get_labels_for_metric("litellm_deployment_cooled_down"),
)
self.litellm_deployment_success_responses = self._counter_factory(
@ -318,6 +405,105 @@ class PrometheusLogger(CustomLogger):
print_verbose(f"Got exception on init prometheus client {str(e)}")
raise e
def _setup_multiprocess_mode(self):
"""
Setup Prometheus multiprocess mode to handle multiple workers properly.
This ensures that metrics are aggregated correctly across all worker processes.
"""
import os
import tempfile
from pathlib import Path
try:
# Check if we're in a multiprocess environment (multiple workers)
if not self._is_multiprocess_environment():
verbose_logger.debug(
"Single process environment detected, skipping multiprocess setup"
)
return
# Set up multiprocess directory if not already configured
multiproc_dir = os.environ.get("PROMETHEUS_MULTIPROC_DIR")
if not multiproc_dir:
# Create a temp directory for multiprocess metrics
multiproc_dir = os.path.join(
tempfile.gettempdir(), "litellm_prometheus_multiproc"
)
os.environ["PROMETHEUS_MULTIPROC_DIR"] = multiproc_dir
verbose_logger.debug(f"Set PROMETHEUS_MULTIPROC_DIR to {multiproc_dir}")
# Ensure the directory exists
Path(multiproc_dir).mkdir(parents=True, exist_ok=True)
# Force the prometheus_client to recognize multiprocess mode
# This is important because the environment variable must be set BEFORE importing prometheus_client
try:
from prometheus_client import multiprocess
# This will trigger the multiprocess mode if the env var is set
verbose_logger.debug(
"Prometheus multiprocess module imported successfully"
)
except Exception as e:
verbose_logger.warning(
f"Failed to import prometheus multiprocess module: {e}"
)
verbose_logger.info(
f"Prometheus multiprocess mode enabled with directory: {multiproc_dir}"
)
except Exception as e:
verbose_logger.warning(f"Failed to setup Prometheus multiprocess mode: {e}")
def _is_multiprocess_environment(self) -> bool:
"""
Detect if we're running in a multiprocess environment (uvicorn/gunicorn with multiple workers).
"""
import os
# Check for common environment variables that indicate multiple workers
num_workers = os.environ.get("NUM_WORKERS", "1")
try:
if int(num_workers) > 1:
return True
except (ValueError, TypeError):
pass
# Check for gunicorn worker environment variables
if os.environ.get("GUNICORN_CMD_ARGS") or os.environ.get("GUNICORN_WORKER_ID"):
return True
# Check if PROMETHEUS_MULTIPROC_DIR is explicitly set (admin override)
if os.environ.get("PROMETHEUS_MULTIPROC_DIR"):
return True
return False
@staticmethod
def cleanup_multiprocess_metrics():
"""
Clean up multiprocess metrics directory on startup.
This should be called once during application startup to prevent stale metrics.
"""
import os
from pathlib import Path
multiproc_dir = os.environ.get("PROMETHEUS_MULTIPROC_DIR")
if multiproc_dir and os.path.exists(multiproc_dir):
try:
# Remove all files in the directory but keep the directory itself
for file_path in Path(multiproc_dir).glob("*"):
if file_path.is_file():
file_path.unlink()
verbose_logger.info(
f"Cleaned up Prometheus multiprocess metrics directory: {multiproc_dir}"
)
except Exception as e:
verbose_logger.warning(
f"Failed to cleanup Prometheus multiprocess directory: {e}"
)
def _parse_prometheus_config(self) -> Dict[str, List[str]]:
"""Parse prometheus metrics configuration for label filtering and enabled metrics"""
import litellm
@ -727,7 +913,16 @@ class PrometheusLogger(CustomLogger):
metric_name = args[0] if args else kwargs.get("name", "")
if self._is_metric_enabled(metric_name):
return metric_class(*args, **kwargs)
# Handle multiprocess_mode parameter for Gauge metrics
if metric_class.__name__ == "Gauge" and "multiprocess_mode" in kwargs:
# Pass through multiprocess_mode to the Gauge constructor
return metric_class(*args, **kwargs)
else:
# For Counter and Histogram, remove multiprocess_mode if present
filtered_kwargs = {
k: v for k, v in kwargs.items() if k != "multiprocess_mode"
}
return metric_class(*args, **filtered_kwargs)
else:
return NoOpMetric()
@ -1039,20 +1234,11 @@ class PrometheusLogger(CustomLogger):
_labels = prometheus_label_factory(
supported_enum_labels=self.get_labels_for_metric(
metric_name="litellm_proxy_total_requests_metric"
metric_name="litellm_spend_metric"
),
enum_values=enum_values,
)
self.litellm_spend_metric.labels(
end_user_id,
user_api_key,
user_api_key_alias,
model,
user_api_team,
user_api_team_alias,
user_id,
).inc(response_cost)
self.litellm_spend_metric.labels(**_labels).inc(response_cost)
def _set_virtual_key_rate_limit_metrics(
self,
@ -2179,13 +2365,14 @@ class PrometheusLogger(CustomLogger):
def _mount_metrics_endpoint(premium_user: bool):
"""
Mount the Prometheus metrics endpoint with optional authentication.
Uses multiprocess collector when running with multiple workers.
Args:
premium_user (bool): Whether the user is a premium user
require_auth (bool, optional): Whether to require authentication for the metrics endpoint.
Defaults to False.
"""
from prometheus_client import make_asgi_app
import os
from prometheus_client import CollectorRegistry, make_asgi_app
from litellm._logging import verbose_proxy_logger
from litellm.proxy._types import CommonProxyErrors
@ -2196,14 +2383,34 @@ class PrometheusLogger(CustomLogger):
f"Prometheus metrics are only available for premium users. {CommonProxyErrors.not_premium_user.value}"
)
# Create metrics ASGI app
metrics_app = make_asgi_app()
# Check if we're in multiprocess mode
multiproc_dir = os.environ.get("PROMETHEUS_MULTIPROC_DIR")
if multiproc_dir:
# Use multiprocess collector for worker aggregation
try:
from prometheus_client import multiprocess
registry = CollectorRegistry()
multiprocess.MultiProcessCollector(registry)
metrics_app = make_asgi_app(registry)
verbose_proxy_logger.info(
f"Starting Prometheus Metrics on /metrics with multiprocess collector (directory: {multiproc_dir})"
)
except Exception as e:
verbose_proxy_logger.warning(
f"Failed to setup multiprocess collector, falling back to default: {e}"
)
metrics_app = make_asgi_app()
else:
# Use default single-process collector
metrics_app = make_asgi_app()
verbose_proxy_logger.debug(
"Starting Prometheus Metrics on /metrics (single process mode)"
)
# Mount the metrics app to the app
app.mount("/metrics", metrics_app)
verbose_proxy_logger.debug(
"Starting Prometheus Metrics on /metrics (no authentication)"
)
def prometheus_label_factory(
@ -2280,7 +2487,9 @@ def get_custom_labels_from_metadata(metadata: dict) -> Dict[str, str]:
return result
def _tag_matches_wildcard_configured_pattern(tags: List[str], configured_tag: str) -> bool:
def _tag_matches_wildcard_configured_pattern(
tags: List[str], configured_tag: str
) -> bool:
"""
Check if any of the request tags matches a wildcard configured pattern
@ -2305,6 +2514,7 @@ def _tag_matches_wildcard_configured_pattern(tags: List[str], configured_tag: st
import re
from litellm.router_utils.pattern_match_deployments import PatternMatchRouter
pattern_router = PatternMatchRouter()
regex_pattern = pattern_router._pattern_to_regex(configured_tag)
return any(re.match(pattern=regex_pattern, string=tag) for tag in tags)
@ -2313,11 +2523,11 @@ def _tag_matches_wildcard_configured_pattern(tags: List[str], configured_tag: st
def get_custom_labels_from_tags(tags: List[str]) -> Dict[str, str]:
"""
Get custom labels from tags based on admin configuration.
Supports both exact matches and wildcard patterns:
- Exact match: "prod" matches "prod" exactly
- Wildcard pattern: "User-Agent: curl/*" matches "User-Agent: curl/7.68.0"
- Wildcard pattern: "User-Agent: curl/*" matches "User-Agent: curl/7.68.0"
Reuses PatternMatchRouter for wildcard pattern matching.
Returns dict of label_name: "true" if the tag matches the configured tag, "false" otherwise
@ -2331,9 +2541,6 @@ def get_custom_labels_from_tags(tags: List[str]) -> Dict[str, str]:
"tag_Service_web_app_v1": "false",
}
"""
import re
from litellm.router_utils.pattern_match_deployments import PatternMatchRouter
from litellm.types.integrations.prometheus import _sanitize_prometheus_label_name
configured_tags = litellm.custom_prometheus_tags
@ -2341,21 +2548,22 @@ def get_custom_labels_from_tags(tags: List[str]) -> Dict[str, str]:
return {}
result: Dict[str, str] = {}
pattern_router = PatternMatchRouter()
for configured_tag in configured_tags:
label_name = _sanitize_prometheus_label_name(f"tag_{configured_tag}")
# Check for exact match first (backwards compatibility)
if configured_tag in tags:
result[label_name] = "true"
continue
# Use PatternMatchRouter for wildcard pattern matching
if "*" in configured_tag and _tag_matches_wildcard_configured_pattern(tags=tags, configured_tag=configured_tag):
if "*" in configured_tag and _tag_matches_wildcard_configured_pattern(
tags=tags, configured_tag=configured_tag
):
result[label_name] = "true"
continue
# No match found
result[label_name] = "false"

28
litellm/proxy/_new_secret_config.yaml
View File

@ -1,9 +1,21 @@
model_list:
- model_name: fake-openai-endpoint
litellm_params:
model: openai/fake
api_key: fake-key
api_base: https://exampleopenaiendpoint-production.up.railway.app/
- model_name: wildcard_models/*
litellm_params:
model: openai/*
- model_name: fake-openai-endpoint
litellm_params:
model: openai/fake
api_key: fake-key
api_base: https://exampleopenaiendpoint-production.up.railway.app/
- model_name: gpt-5-mini
litellm_params:
model: azure/gpt-5-mini
api_base: os.environ/AZURE_GPT_5_MINI_API_BASE # runs os.getenv("AZURE_API_BASE")
api_key: os.environ/AZURE_GPT_5_MINI_API_KEY # runs os.getenv("AZURE_API_KEY")
stream_timeout: 60
merge_reasoning_content_in_choices: true
model_info:
mode: chat
router_settings:
model_group_alias: {"my-fake-gpt-4": "fake-openai-endpoint"}
litellm_settings:
callbacks: ["prometheus"]

31
litellm/proxy/common_utils/callback_utils.py
View File

@ -268,12 +268,43 @@ def initialize_callbacks_on_proxy( # noqa: PLR0915
litellm.callbacks = imported_list # type: ignore
if "prometheus" in value:
# CRITICAL: Set up prometheus multiprocess mode BEFORE importing
import os
import tempfile
from pathlib import Path
# Check if we're in a multiprocess environment
num_workers = os.environ.get('NUM_WORKERS', '1')
is_multiprocess = False
try:
if int(num_workers) > 1:
is_multiprocess = True
except (ValueError, TypeError):
pass
# Check for gunicorn worker environment variables
if os.environ.get('GUNICORN_CMD_ARGS') or os.environ.get('GUNICORN_WORKER_ID'):
is_multiprocess = True
if is_multiprocess and not os.environ.get('PROMETHEUS_MULTIPROC_DIR'):
# Set up multiprocess directory
multiproc_dir = os.path.join(tempfile.gettempdir(), 'litellm_prometheus_multiproc')
os.environ['PROMETHEUS_MULTIPROC_DIR'] = multiproc_dir
# Ensure the directory exists
Path(multiproc_dir).mkdir(parents=True, exist_ok=True)
verbose_proxy_logger.info(f"Prometheus multiprocess mode enabled with directory: {multiproc_dir}")
try:
from litellm_enterprise.integrations.prometheus import PrometheusLogger
except Exception:
PrometheusLogger = None
if PrometheusLogger:
# Clean up any existing multiprocess metrics before mounting
PrometheusLogger.cleanup_multiprocess_metrics()
PrometheusLogger._mount_metrics_endpoint(premium_user)
else:
litellm.callbacks = [

53
litellm/proxy/proxy_cli.py
View File

@ -186,6 +186,39 @@ class ProxyInitializationHelpers:
ssl_certfile_path: str,
ssl_keyfile_path: str,
):
# Set up Prometheus multiprocess mode for gunicorn workers
import os
import tempfile
from pathlib import Path
from litellm._logging import verbose_proxy_logger
if num_workers > 1 and not os.environ.get("PROMETHEUS_MULTIPROC_DIR"):
multiproc_dir = os.path.join(
tempfile.gettempdir(), "litellm_prometheus_multiproc"
)
os.environ["PROMETHEUS_MULTIPROC_DIR"] = multiproc_dir
try:
Path(multiproc_dir).mkdir(parents=True, exist_ok=True)
# Clean up any stale files from previous runs
for file in Path(multiproc_dir).glob("*"):
if file.is_file():
try:
file.unlink()
except Exception:
pass # Ignore errors if file is in use
except PermissionError:
verbose_proxy_logger.warning(
f"Warning: Unable to create Prometheus multiprocess directory at {multiproc_dir} due to permission error. "
f"Running in non-root environment. Prometheus metrics may not work correctly in multiprocess mode."
)
except Exception as e:
verbose_proxy_logger.warning(
f"Warning: Failed to create Prometheus multiprocess directory at {multiproc_dir}: {e}"
)
"""
Run litellm with `gunicorn`
"""
@ -525,6 +558,26 @@ def run_server( # noqa: PLR0915
skip_server_startup,
keepalive_timeout,
):
# CRITICAL: Set up Prometheus multiprocess mode BEFORE any imports
# This ensures all worker processes will use multiprocess mode
import os
import tempfile
from pathlib import Path
if num_workers > 1 and not os.environ.get("PROMETHEUS_MULTIPROC_DIR"):
multiproc_dir = os.path.join(
tempfile.gettempdir(), "litellm_prometheus_multiproc"
)
os.environ["PROMETHEUS_MULTIPROC_DIR"] = multiproc_dir
Path(multiproc_dir).mkdir(parents=True, exist_ok=True)
# Clean up any stale files from previous runs
for file in Path(multiproc_dir).glob("*"):
if file.is_file():
try:
file.unlink()
except Exception:
pass # Ignore errors if file is in use
args = locals()
if local:
from proxy_server import (

46
litellm/proxy/proxy_server.py
View File

@ -1910,6 +1910,48 @@ class ProxyConfig:
callback
)
if "prometheus" in callback:
# CRITICAL: Set up prometheus multiprocess mode BEFORE importing
import os
import tempfile
from pathlib import Path
# Check if we're in a multiprocess environment
num_workers = os.environ.get("NUM_WORKERS", "1")
is_multiprocess = False
try:
if int(num_workers) > 1:
is_multiprocess = True
except (ValueError, TypeError):
pass
# Check for gunicorn worker environment variables
if os.environ.get(
"GUNICORN_CMD_ARGS"
) or os.environ.get("GUNICORN_WORKER_ID"):
is_multiprocess = True
if is_multiprocess and not os.environ.get(
"PROMETHEUS_MULTIPROC_DIR"
):
# Set up multiprocess directory
multiproc_dir = os.path.join(
tempfile.gettempdir(),
"litellm_prometheus_multiproc",
)
os.environ["PROMETHEUS_MULTIPROC_DIR"] = (
multiproc_dir
)
# Ensure the directory exists
Path(multiproc_dir).mkdir(
parents=True, exist_ok=True
)
verbose_proxy_logger.info(
f"Prometheus multiprocess mode enabled with directory: {multiproc_dir}"
)
try:
from litellm_enterprise.integrations.prometheus import (
PrometheusLogger,
@ -1921,6 +1963,8 @@ class ProxyConfig:
verbose_proxy_logger.debug(
"mounting metrics endpoint"
)
# Clean up any existing multiprocess metrics before mounting
PrometheusLogger.cleanup_multiprocess_metrics()
PrometheusLogger._mount_metrics_endpoint(
premium_user
)
@ -2165,6 +2209,8 @@ class ProxyConfig:
if assistant_settings:
for k, v in assistant_settings["litellm_params"].items():
if isinstance(v, str) and v.startswith("os.environ/"):
import os
_v = v.replace("os.environ/", "")
v = os.getenv(_v)
assistant_settings["litellm_params"][k] = v