fix: preserve metadata for custom callbacks on codex/responses path (…

litellm/responses/main.py

@@ -600,8 +600,12 @@ def responses(
         # Update input and tools with provider-specific file IDs if managed files are used
         #########################################################
         model_file_id_mapping = kwargs.get("model_file_id_mapping")
-        model_info_id = kwargs.get("model_info", {}).get("id") if isinstance(kwargs.get("model_info"), dict) else None
-
+        model_info_id = (
+            kwargs.get("model_info", {}).get("id")
+            if isinstance(kwargs.get("model_info"), dict)
+            else None
+        )
+
         input = cast(
             Union[str, ResponseInputParam],
             update_responses_input_with_model_file_ids(
@@ -611,7 +615,7 @@ def responses(
             ),
         )
         local_vars["input"] = input
-        
+
         # Update tools with provider-specific file IDs if needed
         if tools:
             tools = cast(
@@ -696,7 +700,10 @@ def responses(
             )
         )
 
-        # Pre Call logging
+        # Pre Call logging - preserve metadata for custom callbacks
+        # When called from completion bridge (codex models), metadata is in litellm_metadata
+        metadata_for_callbacks = metadata or kwargs.get("litellm_metadata") or {}
+
         litellm_logging_obj.update_environment_variables(
             model=model,
             user=user,
@@ -705,7 +712,7 @@ def responses(
                 **responses_api_request_params,
                 "aresponses": _is_async,
                 "litellm_call_id": litellm_call_id,
-                "metadata": metadata,
+                "metadata": metadata_for_callbacks,
             },
             custom_llm_provider=custom_llm_provider,
         )

tests/test_litellm/responses/test_metadata_codex_callback.py

@@ -0,0 +1,176 @@
+"""
+Test that metadata is passed to custom callbacks during chat completion calls to codex models.
+
+Fixes issue: Metadata is no longer passed to custom callback during chat completion
+calls to codex models (#21204)
+
+Codex models (gpt-5.1-codex, gpt-5.2-codex) use mode=responses and route through
+responses_api_bridge. The bridge converts metadata to litellm_metadata. This test
+verifies metadata is preserved for custom callbacks via kwargs['litellm_params']['metadata'].
+"""
+
+import asyncio
+import os
+import sys
+from typing import Optional
+from unittest.mock import AsyncMock, patch
+
+sys.path.insert(0, os.path.abspath("../../.."))
+
+import pytest
+
+import litellm
+from litellm.integrations.custom_logger import CustomLogger
+
+
+def _make_mock_http_response(response_dict: dict):
+    """Create a mock HTTP response that returns response_dict from .json()."""
+
+    class MockResponse:
+        def __init__(self, json_data, status_code=200):
+            self._json_data = json_data
+            self.status_code = status_code
+            self.text = str(json_data)
+            self.headers = {}
+
+        def json(self):
+            return self._json_data
+
+    return MockResponse(response_dict, 200)
+
+
+class MetadataCaptureCallback(CustomLogger):
+    """Custom callback that captures kwargs passed to async_log_success_event."""
+
+    def __init__(self):
+        self.captured_kwargs: Optional[dict] = None
+
+    async def async_log_success_event(
+        self, kwargs, response_obj, start_time, end_time
+    ):
+        self.captured_kwargs = kwargs
+
+
+@pytest.mark.asyncio
+async def test_metadata_passed_to_custom_callback_codex_models():
+    """
+    Test that metadata passed to completion() is available in custom callback
+    when using codex models (responses API bridge path).
+
+    Codex models have mode=responses and route through responses_api_bridge,
+    which passes litellm_metadata. The fix ensures this is preserved as
+    litellm_params.metadata for callback compatibility.
+    """
+    from litellm.types.llms.openai import ResponsesAPIResponse
+
+    mock_response = ResponsesAPIResponse.model_construct(
+        id="resp-test",
+        created_at=0,
+        output=[
+            {
+                "type": "message",
+                "id": "msg-1",
+                "status": "completed",
+                "role": "assistant",
+                "content": [{"type": "output_text", "text": "Hello!"}],
+            }
+        ],
+        object="response",
+        model="gpt-5.1-codex",
+        status="completed",
+        usage={
+            "input_tokens": 5,
+            "output_tokens": 10,
+            "total_tokens": 15,
+        },
+    )
+
+    test_metadata = {"foo": "bar", "trace_id": "test-123"}
+    callback = MetadataCaptureCallback()
+    original_callbacks = litellm.callbacks.copy() if litellm.callbacks else []
+    litellm.callbacks = [callback]
+
+    with patch(
+        "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
+        new_callable=AsyncMock,
+    ) as mock_post:
+        mock_post.return_value = _make_mock_http_response(
+            mock_response.model_dump()
+        )
+        # gpt-5.1-codex has mode=responses - routes through responses bridge
+        await litellm.acompletion(
+            model="gpt-5.1-codex",
+            messages=[{"role": "user", "content": "Hello"}],
+            metadata=test_metadata,
+        )
+
+    await asyncio.sleep(1)
+
+    assert callback.captured_kwargs is not None, "Callback should have been invoked"
+
+    litellm_params = callback.captured_kwargs.get("litellm_params", {})
+    metadata = litellm_params.get("metadata") or {}
+
+    assert "foo" in metadata, "metadata['foo'] should be accessible in callback"
+    assert metadata["foo"] == "bar"
+    assert metadata.get("trace_id") == "test-123"
+
+
+@pytest.mark.asyncio
+async def test_metadata_passed_via_litellm_metadata_responses_api():
+    """
+    Test that when calling responses() directly with litellm_metadata,
+    metadata is preserved for custom callbacks.
+
+    Uses HTTP mock since mock_response returns early before update_environment_variables.
+    """
+    from litellm.types.llms.openai import ResponsesAPIResponse
+
+    mock_response = ResponsesAPIResponse.model_construct(
+        id="resp-test-2",
+        created_at=0,
+        output=[
+            {
+                "type": "message",
+                "id": "msg-2",
+                "status": "completed",
+                "role": "assistant",
+                "content": [{"type": "output_text", "text": "Hi there!"}],
+            }
+        ],
+        object="response",
+        model="gpt-4o",
+        status="completed",
+        usage={
+            "input_tokens": 2,
+            "output_tokens": 3,
+            "total_tokens": 5,
+        },
+    )
+
+    test_metadata = {"request_id": "req-456"}
+    callback = MetadataCaptureCallback()
+    litellm.callbacks = [callback]
+
+    with patch(
+        "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
+        new_callable=AsyncMock,
+    ) as mock_post:
+        mock_post.return_value = _make_mock_http_response(
+            mock_response.model_dump()
+        )
+        await litellm.aresponses(
+            model="gpt-4o",
+            input="hi",
+            litellm_metadata=test_metadata,
+        )
+
+    await asyncio.sleep(1)
+
+    assert callback.captured_kwargs is not None
+
+    litellm_params = callback.captured_kwargs.get("litellm_params", {})
+    metadata = litellm_params.get("metadata") or {}
+
+    assert "request_id" in metadata
+    assert metadata["request_id"] == "req-456"