Pass litellm proxy specific metadata

litellm/llms/anthropic.py

@@ -385,6 +385,11 @@ class AnthropicConfig:
             if "user_id" in anthropic_message_request["metadata"]:
                 new_kwargs["user"] = anthropic_message_request["metadata"]["user_id"]
 
+        # Pass litellm proxy specific metadata
+        if "litellm_metadata" in anthropic_message_request:
+            # metadata will be passed to litellm.acompletion(), it's a litellm_param
+            new_kwargs["metadata"] = anthropic_message_request.pop("litellm_metadata")
+
         ## CONVERT TOOL CHOICE
         if "tool_choice" in anthropic_message_request:
             new_kwargs["tool_choice"] = self.translate_anthropic_tool_choice_to_openai(

litellm/proxy/litellm_pre_call_utils.py

@@ -39,6 +39,9 @@ def _get_metadata_variable_name(request: Request) -> str:
     """
     if "thread" in request.url.path or "assistant" in request.url.path:
         return "litellm_metadata"
+    if "/v1/messages" in request.url.path:
+        # anthropic API has a field called metadata
+        return "litellm_metadata"
     else:
         return "metadata"
 

litellm/types/llms/anthropic.py

@@ -1,4 +1,4 @@
-from typing import Iterable, List, Optional, Union
+from typing import Any, Dict, Iterable, List, Optional, Union
 
 from pydantic import BaseModel, validator
 from typing_extensions import Literal, Required, TypedDict
@@ -113,6 +113,9 @@ class AnthropicMessagesRequest(TypedDict, total=False):
     top_k: int
     top_p: float
 
+    # litellm param - used for tracking litellm proxy metadata in the request
+    litellm_metadata: dict
+
 
 class ContentTextBlockDelta(TypedDict):
     """

litellm/types/llms/openai.py

@@ -436,6 +436,7 @@ class ChatCompletionRequest(TypedDict, total=False):
     function_call: Union[str, dict]
     functions: List
     user: str
+    metadata: dict  # litellm specific param
 
 
 class ChatCompletionDeltaChunk(TypedDict, total=False):