fix(langsmith): populate usage_metadata in outputs for Cost column

LangSmith reads the Cost column from outputs.usage_metadata.total_cost,
but LangsmithLogger._prepare_log_data never wrote to that key. The
response_cost was already computed in StandardLoggingPayload but was
not forwarded to the outputs dict.

Inject usage_metadata with input_tokens, output_tokens, total_tokens,
and total_cost into the outputs dict so LangSmith can display cost.

Fixes #24001

Made-with: Cursor

litellm/integrations/langsmith.py

@@ -153,11 +153,23 @@ class LangsmithLogger(CustomBatchLogger):
                     if key in requester_metadata and key not in extra_metadata:
                         extra_metadata[key] = requester_metadata[key]
 
+            outputs = payload["response"]
+            if isinstance(outputs, dict):
+                outputs = {**outputs}
+            else:
+                outputs = {"output": outputs}
+            outputs["usage_metadata"] = {
+                "input_tokens": payload.get("prompt_tokens", 0),
+                "output_tokens": payload.get("completion_tokens", 0),
+                "total_tokens": payload.get("total_tokens", 0),
+                "total_cost": payload.get("response_cost", 0),
+            }
+
             data = {
                 "name": run_name,
                 "run_type": "llm",  # this should always be llm, since litellm always logs llm calls. Langsmith allow us to log "chain"
                 "inputs": payload,
-                "outputs": payload["response"],
+                "outputs": outputs,
                 "session_name": project_name,
                 "start_time": payload["startTime"],
                 "end_time": payload["endTime"],

tests/test_litellm/integrations/test_langsmith_init.py

@@ -132,3 +132,57 @@ class TestLangsmithLoggerInit:
         assert (
             logger.sampling_rate >= 0.0
         ), f"sampling_rate should be non-negative, got {logger.sampling_rate}"
+
+
+class TestLangsmithPrepareLogData:
+    """Regression test for #24001: _prepare_log_data must inject
+    usage_metadata into outputs so LangSmith's Cost column is populated."""
+
+    @patch("asyncio.create_task")
+    @patch.dict(os.environ, {"LANGSMITH_SAMPLING_RATE": "1"}, clear=False)
+    def test_outputs_contain_usage_metadata(self, mock_create_task):
+        logger = LangsmithLogger(
+            langsmith_api_key="test-key",
+            langsmith_project="test-project",
+        )
+
+        payload = {
+            "id": "test-id",
+            "response": {"choices": [{"message": {"content": "hi"}}]},
+            "metadata": {},
+            "startTime": 1.0,
+            "endTime": 2.0,
+            "request_tags": [],
+            "error_str": None,
+            "status": "success",
+            "response_cost": 0.0042,
+            "prompt_tokens": 100,
+            "completion_tokens": 50,
+            "total_tokens": 150,
+        }
+
+        kwargs = {
+            "litellm_params": {"metadata": {}},
+            "standard_logging_object": payload,
+        }
+
+        credentials = {
+            "LANGSMITH_API_KEY": "test-key",
+            "LANGSMITH_PROJECT": "test-project",
+            "LANGSMITH_BASE_URL": "https://api.smith.langchain.com",
+        }
+
+        data = logger._prepare_log_data(
+            kwargs=kwargs,
+            response_obj=None,
+            start_time=1.0,
+            end_time=2.0,
+            credentials=credentials,
+        )
+
+        assert "usage_metadata" in data["outputs"]
+        um = data["outputs"]["usage_metadata"]
+        assert um["total_cost"] == 0.0042
+        assert um["input_tokens"] == 100
+        assert um["output_tokens"] == 50
+        assert um["total_tokens"] == 150