add metadata

libs/core/langchain_core/language_models/base.py

@@ -69,6 +69,8 @@ class LangSmithParams(TypedDict, total=False):
 
     ls_stop: list[str] | None
     """Stop words for generation."""
+    ls_integration: str
+    """Integration that created the trace."""
 
 
 @cache  # Cache the tokenizer
@@ -299,6 +301,16 @@ class BaseLanguageModel(
         # generate responses that match a given schema.
         raise NotImplementedError
 
+    def _get_ls_params_with_defaults(
+        self,
+        stop: list[str] | None = None,
+        **kwargs: Any,
+    ) -> LangSmithParams:
+        """Wrap _get_ls_params to always include ls_integration."""
+        ls_params = self._get_ls_params(stop=stop, **kwargs)
+        ls_params["ls_integration"] = "langchain"
+        return ls_params
+
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""

libs/core/langchain_core/language_models/chat_models.py

@@ -505,7 +505,7 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
             options = {"stop": stop, **kwargs, **ls_structured_output_format_dict}
             inheritable_metadata = {
                 **(config.get("metadata") or {}),
-                **self._get_ls_params(stop=stop, **kwargs),
+                **self._get_ls_params_with_defaults(stop=stop, **kwargs),
             }
             callback_manager = CallbackManager.configure(
                 config.get("callbacks"),
@@ -633,7 +633,7 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
         options = {"stop": stop, **kwargs, **ls_structured_output_format_dict}
         inheritable_metadata = {
             **(config.get("metadata") or {}),
-            **self._get_ls_params(stop=stop, **kwargs),
+            **self._get_ls_params_with_defaults(stop=stop, **kwargs),
         }
         callback_manager = AsyncCallbackManager.configure(
             config.get("callbacks"),
@@ -899,7 +899,7 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
         options = {"stop": stop, **ls_structured_output_format_dict}
         inheritable_metadata = {
             **(metadata or {}),
-            **self._get_ls_params(stop=stop, **kwargs),
+            **self._get_ls_params_with_defaults(stop=stop, **kwargs),
         }
 
         callback_manager = CallbackManager.configure(
@@ -1022,7 +1022,7 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
         options = {"stop": stop, **ls_structured_output_format_dict}
         inheritable_metadata = {
             **(metadata or {}),
-            **self._get_ls_params(stop=stop, **kwargs),
+            **self._get_ls_params_with_defaults(stop=stop, **kwargs),
         }
 
         callback_manager = AsyncCallbackManager.configure(

libs/core/langchain_core/language_models/llms.py

@@ -527,7 +527,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             options = {"stop": stop}
             inheritable_metadata = {
                 **(config.get("metadata") or {}),
-                **self._get_ls_params(stop=stop, **kwargs),
+                **self._get_ls_params_with_defaults(stop=stop, **kwargs),
             }
             callback_manager = CallbackManager.configure(
                 config.get("callbacks"),
@@ -597,7 +597,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         options = {"stop": stop}
         inheritable_metadata = {
             **(config.get("metadata") or {}),
-            **self._get_ls_params(stop=stop, **kwargs),
+            **self._get_ls_params_with_defaults(stop=stop, **kwargs),
         }
         callback_manager = AsyncCallbackManager.configure(
             config.get("callbacks"),
@@ -906,14 +906,14 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             metadata = [
                 {
                     **(meta or {}),
-                    **self._get_ls_params(stop=stop, **kwargs),
+                    **self._get_ls_params_with_defaults(stop=stop, **kwargs),
                 }
                 for meta in metadata
             ]
         elif isinstance(metadata, dict):
             metadata = {
                 **(metadata or {}),
-                **self._get_ls_params(stop=stop, **kwargs),
+                **self._get_ls_params_with_defaults(stop=stop, **kwargs),
             }
         if (
             isinstance(callbacks, list)
@@ -1173,14 +1173,14 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             metadata = [
                 {
                     **(meta or {}),
-                    **self._get_ls_params(stop=stop, **kwargs),
+                    **self._get_ls_params_with_defaults(stop=stop, **kwargs),
                 }
                 for meta in metadata
             ]
         elif isinstance(metadata, dict):
             metadata = {
                 **(metadata or {}),
-                **self._get_ls_params(stop=stop, **kwargs),
+                **self._get_ls_params_with_defaults(stop=stop, **kwargs),
             }
         # Create callback managers
         if isinstance(callbacks, list) and (

libs/langchain_v1/langchain/agents/factory.py

@@ -1630,8 +1630,9 @@ def create_agent(
         )
 
     config: RunnableConfig = {"recursion_limit": 10_000}
+    config["metadata"] = {"ls_integration": "langchain"}
     if name:
-        config["metadata"] = {"lc_agent_name": name}
+        config["metadata"]["lc_agent_name"] = name
 
     return graph.compile(
         checkpointer=checkpointer,