Litellm router trace (#6742)

* feat(router.py): add trace_id to parent functions - allows tracking retry/fallbacks

* feat(router.py): log trace id across retry/fallback logic

allows grouping llm logs for the same request

* test: fix tests

* fix: fix test

* fix(transformation.py): only set non-none stop_sequences

litellm/litellm_core_utils/litellm_logging.py

@@ -201,6 +201,7 @@ class Logging:
         start_time,
         litellm_call_id: str,
         function_id: str,
+        litellm_trace_id: Optional[str] = None,
         dynamic_input_callbacks: Optional[
             List[Union[str, Callable, CustomLogger]]
         ] = None,
@@ -238,6 +239,7 @@ class Logging:
         self.start_time = start_time  # log the call start time
         self.call_type = call_type
         self.litellm_call_id = litellm_call_id
+        self.litellm_trace_id = litellm_trace_id
         self.function_id = function_id
         self.streaming_chunks: List[Any] = []  # for generating complete stream response
         self.sync_streaming_chunks: List[Any] = (
@@ -274,6 +276,11 @@ class Logging:
         self.completion_start_time: Optional[datetime.datetime] = None
         self._llm_caching_handler: Optional[LLMCachingHandler] = None
 
+        self.model_call_details = {
+            "litellm_trace_id": litellm_trace_id,
+            "litellm_call_id": litellm_call_id,
+        }
+
     def process_dynamic_callbacks(self):
         """
         Initializes CustomLogger compatible callbacks in self.dynamic_* callbacks
@@ -381,7 +388,8 @@ class Logging:
         self.logger_fn = litellm_params.get("logger_fn", None)
         verbose_logger.debug(f"self.optional_params: {self.optional_params}")
 
-        self.model_call_details = {
+        self.model_call_details.update(
+            {
                 "model": self.model,
                 "messages": self.messages,
                 "optional_params": self.optional_params,
@@ -396,6 +404,7 @@ class Logging:
                 **self.optional_params,
                 **additional_params,
             }
+        )
 
         ## check if stream options is set ##  - used by CustomStreamWrapper for easy instrumentation
         if "stream_options" in additional_params:
@@ -2806,6 +2815,7 @@ def get_standard_logging_object_payload(
 
         payload: StandardLoggingPayload = StandardLoggingPayload(
             id=str(id),
+            trace_id=kwargs.get("litellm_trace_id"),  # type: ignore
             call_type=call_type or "",
             cache_hit=cache_hit,
             status=status,

litellm/main.py

@@ -1066,6 +1066,7 @@ def completion(  # type: ignore # noqa: PLR0915
             azure_ad_token_provider=kwargs.get("azure_ad_token_provider"),
             user_continue_message=kwargs.get("user_continue_message"),
             base_model=base_model,
+            litellm_trace_id=kwargs.get("litellm_trace_id"),
         )
         logging.update_environment_variables(
             model=model,

litellm/router.py

@@ -679,9 +679,8 @@ class Router:
             kwargs["model"] = model
             kwargs["messages"] = messages
             kwargs["original_function"] = self._completion
-            kwargs.get("request_timeout", self.timeout)
+            self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
+
-            kwargs.setdefault("metadata", {}).update({"model_group": model})
             response = self.function_with_fallbacks(**kwargs)
             return response
         except Exception as e:
@@ -783,8 +782,7 @@ class Router:
             kwargs["stream"] = stream
             kwargs["original_function"] = self._acompletion
             kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
-
+            self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            kwargs.setdefault("metadata", {}).update({"model_group": model})
 
             request_priority = kwargs.get("priority") or self.default_priority
 
@@ -948,6 +946,17 @@ class Router:
                 self.fail_calls[model_name] += 1
             raise e
 
+    def _update_kwargs_before_fallbacks(self, model: str, kwargs: dict) -> None:
+        """
+        Adds/updates to kwargs:
+        - num_retries
+        - litellm_trace_id
+        - metadata
+        """
+        kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
+        kwargs.setdefault("litellm_trace_id", str(uuid.uuid4()))
+        kwargs.setdefault("metadata", {}).update({"model_group": model})
+
     def _update_kwargs_with_default_litellm_params(self, kwargs: dict) -> None:
         """
         Adds default litellm params to kwargs, if set.
@@ -1511,9 +1520,7 @@ class Router:
             kwargs["model"] = model
             kwargs["file"] = file
             kwargs["original_function"] = self._atranscription
-            kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
+            self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            kwargs.get("request_timeout", self.timeout)
-            kwargs.setdefault("metadata", {}).update({"model_group": model})
             response = await self.async_function_with_fallbacks(**kwargs)
 
             return response
@@ -1688,9 +1695,7 @@ class Router:
             kwargs["model"] = model
             kwargs["input"] = input
             kwargs["original_function"] = self._arerank
-            kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
+            self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            kwargs.get("request_timeout", self.timeout)
-            kwargs.setdefault("metadata", {}).update({"model_group": model})
 
             response = await self.async_function_with_fallbacks(**kwargs)
 
@@ -1839,9 +1844,7 @@ class Router:
             kwargs["model"] = model
             kwargs["prompt"] = prompt
             kwargs["original_function"] = self._atext_completion
-            kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
+            self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            kwargs.get("request_timeout", self.timeout)
-            kwargs.setdefault("metadata", {}).update({"model_group": model})
             response = await self.async_function_with_fallbacks(**kwargs)
 
             return response
@@ -2112,9 +2115,7 @@ class Router:
             kwargs["model"] = model
             kwargs["input"] = input
             kwargs["original_function"] = self._aembedding
-            kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries)
+            self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            kwargs.get("request_timeout", self.timeout)
-            kwargs.setdefault("metadata", {}).update({"model_group": model})
             response = await self.async_function_with_fallbacks(**kwargs)
             return response
         except Exception as e:
@@ -2616,6 +2617,7 @@ class Router:
         content_policy_fallbacks: Optional[List] = kwargs.get(
             "content_policy_fallbacks", self.content_policy_fallbacks
         )
+
         try:
             self._handle_mock_testing_fallbacks(
                 kwargs=kwargs,

litellm/types/router.py

@@ -150,6 +150,8 @@ class GenericLiteLLMParams(BaseModel):
     max_retries: Optional[int] = None
     organization: Optional[str] = None  # for openai orgs
     configurable_clientside_auth_params: CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS = None
+    ## LOGGING PARAMS ##
+    litellm_trace_id: Optional[str] = None
     ## UNIFIED PROJECT/REGION ##
     region_name: Optional[str] = None
     ## VERTEX AI ##
@@ -186,6 +188,8 @@ class GenericLiteLLMParams(BaseModel):
             None  # timeout when making stream=True calls, if str, pass in as os.environ/
         ),
         organization: Optional[str] = None,  # for openai orgs
+        ## LOGGING PARAMS ##
+        litellm_trace_id: Optional[str] = None,
         ## UNIFIED PROJECT/REGION ##
         region_name: Optional[str] = None,
         ## VERTEX AI ##

litellm/types/utils.py

@@ -1334,6 +1334,7 @@ class ResponseFormatChunk(TypedDict, total=False):
 
 all_litellm_params = [
     "metadata",
+    "litellm_trace_id",
     "tags",
     "acompletion",
     "aimg_generation",
@@ -1523,6 +1524,7 @@ StandardLoggingPayloadStatus = Literal["success", "failure"]
 
 class StandardLoggingPayload(TypedDict):
     id: str
+    trace_id: str  # Trace multiple LLM calls belonging to same overall request (e.g. fallbacks/retries)
     call_type: str
     response_cost: float
     response_cost_failure_debug_info: Optional[

litellm/utils.py

@@ -527,6 +527,7 @@ def function_setup(  # noqa: PLR0915
             messages=messages,
             stream=stream,
             litellm_call_id=kwargs["litellm_call_id"],
+            litellm_trace_id=kwargs.get("litellm_trace_id"),
             function_id=function_id or "",
             call_type=call_type,
             start_time=start_time,
@@ -2056,6 +2057,7 @@ def get_litellm_params(
     azure_ad_token_provider=None,
     user_continue_message=None,
     base_model=None,
+    litellm_trace_id=None,
 ):
     litellm_params = {
         "acompletion": acompletion,
@@ -2084,6 +2086,7 @@ def get_litellm_params(
         "user_continue_message": user_continue_message,
         "base_model": base_model
         or _get_base_model_from_litellm_call_metadata(metadata=metadata),
+        "litellm_trace_id": litellm_trace_id,
     }
 
     return litellm_params

tests/local_testing/test_custom_callback_input.py

@@ -1624,3 +1624,55 @@ async def test_standard_logging_payload_stream_usage(sync_mode):
             print(f"standard_logging_object usage: {built_response.usage}")
     except litellm.InternalServerError:
         pass
+
+
+def test_standard_logging_retries():
+    """
+    know if a request was retried.
+    """
+    from litellm.types.utils import StandardLoggingPayload
+    from litellm.router import Router
+
+    customHandler = CompletionCustomHandler()
+    litellm.callbacks = [customHandler]
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {
+                    "model": "openai/gpt-3.5-turbo",
+                    "api_key": "test-api-key",
+                },
+            }
+        ]
+    )
+
+    with patch.object(
+        customHandler, "log_failure_event", new=MagicMock()
+    ) as mock_client:
+        try:
+            router.completion(
+                model="gpt-3.5-turbo",
+                messages=[{"role": "user", "content": "Hey, how's it going?"}],
+                num_retries=1,
+                mock_response="litellm.RateLimitError",
+            )
+        except litellm.RateLimitError:
+            pass
+
+        assert mock_client.call_count == 2
+        assert (
+            mock_client.call_args_list[0].kwargs["kwargs"]["standard_logging_object"][
+                "trace_id"
+            ]
+            is not None
+        )
+        assert (
+            mock_client.call_args_list[0].kwargs["kwargs"]["standard_logging_object"][
+                "trace_id"
+            ]
+            == mock_client.call_args_list[1].kwargs["kwargs"][
+                "standard_logging_object"
+            ]["trace_id"]
+        )

tests/local_testing/test_router_utils.py

@@ -14,6 +14,7 @@ from litellm.router import Deployment, LiteLLM_Params, ModelInfo
 from concurrent.futures import ThreadPoolExecutor
 from collections import defaultdict
 from dotenv import load_dotenv
+from unittest.mock import patch, MagicMock, AsyncMock
 
 load_dotenv()
 
@@ -83,3 +84,93 @@ def test_returned_settings():
     except Exception:
         print(traceback.format_exc())
         pytest.fail("An error occurred - " + traceback.format_exc())
+
+
+from litellm.types.utils import CallTypes
+
+
+def test_update_kwargs_before_fallbacks_unit_test():
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {
+                    "model": "azure/chatgpt-v-2",
+                    "api_key": "bad-key",
+                    "api_version": os.getenv("AZURE_API_VERSION"),
+                    "api_base": os.getenv("AZURE_API_BASE"),
+                },
+            }
+        ],
+    )
+
+    kwargs = {"messages": [{"role": "user", "content": "write 1 sentence poem"}]}
+
+    router._update_kwargs_before_fallbacks(
+        model="gpt-3.5-turbo",
+        kwargs=kwargs,
+    )
+
+    assert kwargs["litellm_trace_id"] is not None
+
+
+@pytest.mark.parametrize(
+    "call_type",
+    [
+        CallTypes.acompletion,
+        CallTypes.atext_completion,
+        CallTypes.aembedding,
+        CallTypes.arerank,
+        CallTypes.atranscription,
+    ],
+)
+@pytest.mark.asyncio
+async def test_update_kwargs_before_fallbacks(call_type):
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {
+                    "model": "azure/chatgpt-v-2",
+                    "api_key": "bad-key",
+                    "api_version": os.getenv("AZURE_API_VERSION"),
+                    "api_base": os.getenv("AZURE_API_BASE"),
+                },
+            }
+        ],
+    )
+
+    if call_type.value.startswith("a"):
+        with patch.object(router, "async_function_with_fallbacks") as mock_client:
+            if call_type.value == "acompletion":
+                input_kwarg = {
+                    "messages": [{"role": "user", "content": "Hello, how are you?"}],
+                }
+            elif (
+                call_type.value == "atext_completion"
+                or call_type.value == "aimage_generation"
+            ):
+                input_kwarg = {
+                    "prompt": "Hello, how are you?",
+                }
+            elif call_type.value == "aembedding" or call_type.value == "arerank":
+                input_kwarg = {
+                    "input": "Hello, how are you?",
+                }
+            elif call_type.value == "atranscription":
+                input_kwarg = {
+                    "file": "path/to/file",
+                }
+            else:
+                input_kwarg = {}
+
+            await getattr(router, call_type.value)(
+                model="gpt-3.5-turbo",
+                **input_kwarg,
+            )
+
+            mock_client.assert_called_once()
+
+            print(mock_client.call_args.kwargs)
+            assert mock_client.call_args.kwargs["litellm_trace_id"] is not None