Litellm dev 01 20 2025 p1 (#7884)

* fix(initial-test-to-return-api-timeout-value-in-openai-timeout-exception): Makes it easier for user to debug why request timed out

* feat(openai.py): return timeout value + time taken on openai timeout errors

helps debug timeout errors

* fix(utils.py): fix num retries extraction logic when num_retries = 0

* fix(config_settings.md): litellm_logging.py

support printing payload to console if 'LITELLM_PRINT_STANDARD_LOGGING_PAYLOAD' is true

 Enables easier debug

* test(test_auth_checks.py'): remove common checks userapikeyauth enforcement check

* fix(litellm_logging.py): fix linting error

docs/my-website/docs/proxy/config_settings.md

@@ -437,6 +437,7 @@ router_settings:
 | LITELLM_SALT_KEY | Salt key for encryption in LiteLLM
 | LITELLM_SECRET_AWS_KMS_LITELLM_LICENSE | AWS KMS encrypted license for LiteLLM
 | LITELLM_TOKEN | Access token for LiteLLM integration
+| LITELLM_PRINT_STANDARD_LOGGING_PAYLOAD | If true, prints the standard logging payload to the console - useful for debugging
 | LOGFIRE_TOKEN | Token for Logfire logging service
 | MICROSOFT_CLIENT_ID | Client ID for Microsoft services
 | MICROSOFT_CLIENT_SECRET | Client secret for Microsoft services

litellm/litellm_core_utils/exception_mapping_utils.py

@@ -224,8 +224,9 @@ def exception_type(  # type: ignore  # noqa: PLR0915
                 or "Timed out generating response" in error_str
             ):
                 exception_mapping_worked = True
+
                 raise Timeout(
-                    message=f"APITimeoutError - Request timed out. \nerror_str: {error_str}",
+                    message=f"APITimeoutError - Request timed out. Error_str: {error_str}",
                     model=model,
                     llm_provider=custom_llm_provider,
                     litellm_debug_info=extra_information,

litellm/litellm_core_utils/litellm_logging.py

@@ -3069,8 +3069,7 @@ def get_standard_logging_object_payload(
     original_exception: Optional[Exception] = None,
 ) -> Optional[StandardLoggingPayload]:
     try:
-        if kwargs is None:
+        kwargs = kwargs or {}
-            kwargs = {}
 
         hidden_params: Optional[dict] = None
         if init_response_obj is None:
@@ -3239,6 +3238,7 @@ def get_standard_logging_object_payload(
             ),
         )
 
+        emit_standard_logging_payload(payload)
         return payload
     except Exception as e:
         verbose_logger.exception(
@@ -3247,6 +3247,11 @@ def get_standard_logging_object_payload(
         return None
 
 
+def emit_standard_logging_payload(payload: StandardLoggingPayload):
+    if os.getenv("LITELLM_PRINT_STANDARD_LOGGING_PAYLOAD"):
+        verbose_logger.info(json.dumps(payload, indent=4))
+
+
 def get_standard_logging_metadata(
     metadata: Optional[Dict[str, Any]]
 ) -> StandardLoggingMetadata:

litellm/llms/openai/openai.py

@@ -1,4 +1,5 @@
 import hashlib
+import time
 import types
 from typing import (
     Any,
@@ -390,12 +391,14 @@ class OpenAIChatCompletion(BaseLLM):
         - call chat.completions.create.with_raw_response when litellm.return_response_headers is True
         - call chat.completions.create by default
         """
+        start_time = time.time()
         try:
             raw_response = (
                 await openai_aclient.chat.completions.with_raw_response.create(
                     **data, timeout=timeout
                 )
             )
+            end_time = time.time()
 
             if hasattr(raw_response, "headers"):
                 headers = dict(raw_response.headers)
@@ -403,6 +406,11 @@ class OpenAIChatCompletion(BaseLLM):
                 headers = {}
             response = raw_response.parse()
             return headers, response
+        except openai.APITimeoutError as e:
+            end_time = time.time()
+            time_delta = round(end_time - start_time, 2)
+            e.message += f" - timeout value={timeout}, time taken={time_delta} seconds"
+            raise e
         except Exception as e:
             raise e
 
@@ -521,6 +529,7 @@ class OpenAIChatCompletion(BaseLLM):
             for _ in range(
                 2
             ):  # if call fails due to alternating messages, retry with reformatted message
+
                 if provider_config is not None:
                     data = provider_config.transform_request(
                         model=model,
@@ -725,6 +734,7 @@ class OpenAIChatCompletion(BaseLLM):
         for _ in range(
             2
         ):  # if call fails due to alternating messages, retry with reformatted message
+
             try:
                 openai_aclient: AsyncOpenAI = self._get_openai_client(  # type: ignore
                     is_async=True,
@@ -792,9 +802,10 @@ class OpenAIChatCompletion(BaseLLM):
                 error_headers = getattr(e, "headers", None)
                 if error_headers is None and exception_response:
                     error_headers = getattr(exception_response, "headers", None)
+                message = getattr(e, "message", str(e))
 
                 raise OpenAIError(
-                    status_code=status_code, message=str(e), headers=error_headers
+                    status_code=status_code, message=message, headers=error_headers
                 )
 
     def streaming(

litellm/proxy/_new_secret_config.yaml

@@ -9,5 +9,5 @@ model_list:
       model: openai/random_sleep
       api_key: sk-1234
       api_base: http://0.0.0.0:8090
-    model_info:
+      timeout: 2
-      health_check_timeout: 1
+      num_retries: 0

litellm/router.py

@@ -3073,6 +3073,7 @@ class Router:
                 deployment_num_retries, int
             ):
                 num_retries = deployment_num_retries
+
             """
             Retry Logic
             """
@@ -3119,6 +3120,7 @@ class Router:
             )
 
             await asyncio.sleep(retry_after)
+
             for current_attempt in range(num_retries):
                 try:
                     # if the function call is successful, no exception will be raised and we'll break out of the loop

litellm/utils.py

@@ -622,6 +622,28 @@ async def _client_async_logging_helper(
         )
 
 
+def _get_wrapper_num_retries(
+    kwargs: Dict[str, Any], exception: Exception
+) -> Tuple[Optional[int], Dict[str, Any]]:
+    """
+    Get the number of retries from the kwargs and the retry policy.
+    Used for the wrapper functions.
+    """
+    num_retries = kwargs.get("num_retries", None)
+    if num_retries is None:
+        num_retries = litellm.num_retries
+    if kwargs.get("retry_policy", None):
+        retry_policy_num_retries = get_num_retries_from_retry_policy(
+            exception=exception,
+            retry_policy=kwargs.get("retry_policy"),
+        )
+        kwargs["retry_policy"] = reset_retry_policy()
+        if retry_policy_num_retries is not None:
+            num_retries = retry_policy_num_retries
+
+    return num_retries, kwargs
+
+
 def client(original_function):  # noqa: PLR0915
     rules_obj = Rules()
 
@@ -736,19 +758,6 @@ def client(original_function):  # noqa: PLR0915
         except Exception as e:
             raise e
 
-    def _get_num_retries(
-        kwargs: Dict[str, Any], exception: Exception
-    ) -> Tuple[Optional[int], Dict[str, Any]]:
-        num_retries = kwargs.get("num_retries", None) or litellm.num_retries or None
-        if kwargs.get("retry_policy", None):
-            num_retries = get_num_retries_from_retry_policy(
-                exception=exception,
-                retry_policy=kwargs.get("retry_policy"),
-            )
-            kwargs["retry_policy"] = reset_retry_policy()
-
-        return num_retries, kwargs
-
     @wraps(original_function)
     def wrapper(*args, **kwargs):  # noqa: PLR0915
         # DO NOT MOVE THIS. It always needs to run first
@@ -1200,7 +1209,7 @@ def client(original_function):  # noqa: PLR0915
                     raise e
 
             call_type = original_function.__name__
-            num_retries, kwargs = _get_num_retries(kwargs=kwargs, exception=e)
+            num_retries, kwargs = _get_wrapper_num_retries(kwargs=kwargs, exception=e)
             if call_type == CallTypes.acompletion.value:
                 context_window_fallback_dict = kwargs.get(
                     "context_window_fallback_dict", {}

tests/local_testing/test_auth_checks.py

@@ -201,31 +201,6 @@ async def test_can_team_call_model(model, expect_to_work):
         assert not model_in_access_group(**args)
 
 
-def test_common_checks_import():
-    """
-    Enforce that common_checks can only be imported by the 'user_api_key_auth()' function.
-    """
-    try:
-        from litellm.proxy.auth.user_api_key_auth import common_checks
-        from litellm.proxy._types import CommonProxyErrors
-
-        common_checks(
-            request_body={},
-            team_object=None,
-            user_object=None,
-            end_user_object=None,
-            global_proxy_spend=None,
-            general_settings={},
-            route="",
-            llm_router=None,
-        )
-        pytest.fail(
-            "common_checks can only be imported by the 'user_api_key_auth()' function."
-        )
-    except Exception as e:
-        assert CommonProxyErrors.not_premium_user.value in str(e)
-
-
 @pytest.mark.asyncio
 async def test_is_valid_fallback_model():
     from litellm.proxy.auth.auth_checks import is_valid_fallback_model

tests/local_testing/test_azure_openai.py

@@ -74,6 +74,7 @@ async def test_aaaaazure_tenant_id_auth(respx_mock: MockRouter):
         created=int(datetime.now().timestamp()),
     )
     litellm.set_verbose = True
+
     mock_request = respx_mock.post(url__regex=r".*/chat/completions.*").mock(
         return_value=httpx.Response(200, json=obj.model_dump(mode="json"))
     )

tests/local_testing/test_router.py

@@ -20,7 +20,7 @@ import os
 from collections import defaultdict
 from concurrent.futures import ThreadPoolExecutor
 from unittest.mock import AsyncMock, MagicMock, patch
-
+from respx import MockRouter
 import httpx
 from dotenv import load_dotenv
 from pydantic import BaseModel

tests/local_testing/test_utils.py

@@ -1480,3 +1480,17 @@ def test_get_potential_model_names():
         model="bedrock/ap-northeast-1/anthropic.claude-instant-v1",
         custom_llm_provider="bedrock",
     )
+
+
+@pytest.mark.parametrize("num_retries", [0, 1, 5])
+def test_get_num_retries(num_retries):
+    from litellm.utils import _get_wrapper_num_retries
+
+    assert _get_wrapper_num_retries(
+        kwargs={"num_retries": num_retries}, exception=Exception("test")
+    ) == (
+        num_retries,
+        {
+            "num_retries": num_retries,
+        },
+    )