diff --git a/libs/core/langchain_core/language_models/chat_models.py b/libs/core/langchain_core/language_models/chat_models.py
index f6967f51c09..f968790e130 100644
--- a/libs/core/langchain_core/language_models/chat_models.py
+++ b/libs/core/langchain_core/language_models/chat_models.py
@@ -13,6 +13,7 @@ from typing import (
     Dict,
     Iterator,
     List,
+    Literal,
     Optional,
     Sequence,
     Type,
@@ -20,6 +21,8 @@ from typing import (
     cast,
 )
 
+from typing_extensions import TypedDict
+
 from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
 from langchain_core.callbacks import (
@@ -60,6 +63,15 @@ if TYPE_CHECKING:
     from langchain_core.tools import BaseTool
 
 
+class LangSmithParams(TypedDict, total=False):
+    ls_provider: str
+    ls_model_name: str
+    ls_model_type: Literal["chat"]
+    ls_temperature: Optional[float]
+    ls_max_tokens: Optional[int]
+    ls_stop: Optional[List[str]]
+
+
 def generate_from_stream(stream: Iterator[ChatGenerationChunk]) -> ChatResult:
     """Generate from a stream."""
 
@@ -206,13 +218,17 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             messages = self._convert_input(input).to_messages()
             params = self._get_invocation_params(stop=stop, **kwargs)
             options = {"stop": stop, **kwargs}
+            inheritable_metadata = {
+                **(config.get("metadata") or {}),
+                **self._get_ls_params(stop=stop, **kwargs),
+            }
             callback_manager = CallbackManager.configure(
                 config.get("callbacks"),
                 self.callbacks,
                 self.verbose,
                 config.get("tags"),
                 self.tags,
-                config.get("metadata"),
+                inheritable_metadata,
                 self.metadata,
             )
             (run_manager,) = callback_manager.on_chat_model_start(
@@ -273,13 +289,17 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         messages = self._convert_input(input).to_messages()
         params = self._get_invocation_params(stop=stop, **kwargs)
         options = {"stop": stop, **kwargs}
+        inheritable_metadata = {
+            **(config.get("metadata") or {}),
+            **self._get_ls_params(stop=stop, **kwargs),
+        }
         callback_manager = AsyncCallbackManager.configure(
             config.get("callbacks"),
             self.callbacks,
             self.verbose,
             config.get("tags"),
             self.tags,
-            config.get("metadata"),
+            inheritable_metadata,
             self.metadata,
         )
         (run_manager,) = await callback_manager.on_chat_model_start(
@@ -336,6 +356,17 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         params["stop"] = stop
         return {**params, **kwargs}
 
+    def _get_ls_params(
+        self,
+        stop: Optional[List[str]] = None,
+        **kwargs: Any,
+    ) -> LangSmithParams:
+        """Get standard params for tracing."""
+        ls_params = LangSmithParams(ls_model_type="chat")
+        if stop:
+            ls_params["ls_stop"] = stop
+        return ls_params
+
     def _get_llm_string(self, stop: Optional[List[str]] = None, **kwargs: Any) -> str:
         if self.is_lc_serializable():
             params = {**kwargs, **{"stop": stop}}
@@ -385,6 +416,10 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         """
         params = self._get_invocation_params(stop=stop, **kwargs)
         options = {"stop": stop}
+        inheritable_metadata = {
+            **(metadata or {}),
+            **self._get_ls_params(stop=stop, **kwargs),
+        }
 
         callback_manager = CallbackManager.configure(
             callbacks,
@@ -392,7 +427,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             self.verbose,
             tags,
             self.tags,
-            metadata,
+            inheritable_metadata,
             self.metadata,
         )
         run_managers = callback_manager.on_chat_model_start(
@@ -472,6 +507,10 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         """
         params = self._get_invocation_params(stop=stop, **kwargs)
         options = {"stop": stop}
+        inheritable_metadata = {
+            **(metadata or {}),
+            **self._get_ls_params(stop=stop, **kwargs),
+        }
 
         callback_manager = AsyncCallbackManager.configure(
             callbacks,
@@ -479,7 +518,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             self.verbose,
             tags,
             self.tags,
-            metadata,
+            inheritable_metadata,
             self.metadata,
         )
 
diff --git a/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr b/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr
index c297a1b06b7..a0a7ce07eff 100644
--- a/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr
+++ b/libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr
@@ -1518,7 +1518,7 @@
 # ---
 # name: test_combining_sequences.3
   list([
-    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'middle': [{'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 4, 'type': 'runnable', 'data': {'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'name': 'RunnableLambda'}}, {'id': 5, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 6, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 7, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 8, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}, {'source': 2, 'target': 3}, {'source': 3, 'target': 4}, {'source': 4, 'target': 5}, {'source': 5, 'target': 6}, {'source': 7, 'target': 8}, {'source': 6, 'target': 7}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ['baz', 'qux']}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo, bar'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo, bar', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo, bar', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002'), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'input': AIMessage(content='foo, bar', id='00000000-0000-4000-8000-000000000004')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000003'), Run(id=UUID('00000000-0000-4000-8000-000000000005'), name='RunnableLambda', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'input': ['foo', 'bar']}, outputs={'question': 'foobar'}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:4'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000005'), Run(id=UUID('00000000-0000-4000-8000-000000000006'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nicer assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'foobar'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nicer assistant.'), HumanMessage(content='foobar')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:5'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000006'), Run(id=UUID('00000000-0000-4000-8000-000000000007'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['baz, qux'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nicer assistant.\nHuman: foobar']}, outputs={'generations': [[{'text': 'baz, qux', 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trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000008')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
+    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 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'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo, bar'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1, 'metadata': {'ls_model_type': 'chat'}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 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'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002'), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 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tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'runnables', 'base', 'RunnableLambda'], 'repr': "RunnableLambda(lambda x: {'question': x[0] + x[1]})"}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'input': ['foo', 'bar']}, outputs={'question': 'foobar'}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:4'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000005'), Run(id=UUID('00000000-0000-4000-8000-000000000006'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 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{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'foobar'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nicer assistant.'), HumanMessage(content='foobar')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:5'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000006'), Run(id=UUID('00000000-0000-4000-8000-000000000007'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['baz, qux'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1, 'metadata': {'ls_model_type': 'chat'}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['baz, qux'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nicer assistant.\nHuman: foobar']}, outputs={'generations': [[{'text': 'baz, qux', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'baz, qux', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000006-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:6'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000007'), Run(id=UUID('00000000-0000-4000-8000-000000000008'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'input': AIMessage(content='baz, qux', id='00000000-0000-4000-8000-000000000009')}, outputs={'output': ['baz', 'qux']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:7'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000008')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
   ])
 # ---
 # name: test_each
@@ -2653,7 +2653,7 @@
 # ---
 # name: test_prompt_with_chat_model.2
   list([
-    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 2, 'target': 3}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': AIMessage(content='foo', id='00000000-0000-4000-8000-000000000003')}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
+    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 2, 'target': 3}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': AIMessage(content='foo', id='00000000-0000-4000-8000-000000000003')}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1, 'metadata': {'ls_model_type': 'chat'}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
   ])
 # ---
 # name: test_prompt_with_chat_model_and_parser
@@ -3033,7 +3033,7 @@
 # ---
 # name: test_prompt_with_chat_model_and_parser.1
   list([
-    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'middle': [{'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 4, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}, {'source': 3, 'target': 4}, {'source': 2, 'target': 3}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo, bar'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo, bar', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo, bar', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002'), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'input': AIMessage(content='foo, bar', id='00000000-0000-4000-8000-000000000004')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000003')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
+    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'middle': [{'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}], 'last': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 4, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}, {'source': 3, 'target': 4}, {'source': 2, 'target': 3}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo, bar'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1, 'metadata': {'ls_model_type': 'chat'}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo, bar'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo, bar', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo, bar', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002'), Run(id=UUID('00000000-0000-4000-8000-000000000003'), name='CommaSeparatedListOutputParser', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='parser', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'kwargs': {}, 'name': 'CommaSeparatedListOutputParser', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'output_parsers', 'list', 'CommaSeparatedListOutputParser'], 'name': 'CommaSeparatedListOutputParser'}}, {'id': 2, 'type': 'schema', 'data': 'CommaSeparatedListOutputParserOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'input': AIMessage(content='foo, bar', id='00000000-0000-4000-8000-000000000004')}, outputs={'output': ['foo', 'bar']}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:3'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000003')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
   ])
 # ---
 # name: test_prompt_with_chat_model_async
@@ -3351,7 +3351,7 @@
 # ---
 # name: test_prompt_with_chat_model_async.2
   list([
-    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 2, 'target': 3}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': AIMessage(content='foo', id='00000000-0000-4000-8000-000000000003')}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
+    Run(id=UUID('00000000-0000-4000-8000-000000000000'), name='RunnableSequence', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='chain', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'runnable', 'RunnableSequence'], 'kwargs': {'first': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, 'last': {'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}, 'name': 'RunnableSequence', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 3, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 2, 'target': 3}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': AIMessage(content='foo', id='00000000-0000-4000-8000-000000000003')}, reference_example_id=None, parent_run_id=None, tags=[], child_runs=[Run(id=UUID('00000000-0000-4000-8000-000000000001'), name='ChatPromptTemplate', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='prompt', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={}, error=None, serialized={'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'kwargs': {'input_variables': ['question'], 'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'SystemMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': [], 'template': 'You are a nice assistant.', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'chat', 'HumanMessagePromptTemplate'], 'kwargs': {'prompt': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'kwargs': {'input_variables': ['question'], 'template': '{question}', 'template_format': 'f-string'}, 'name': 'PromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'prompt', 'PromptTemplate'], 'name': 'PromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'PromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}}}]}, 'name': 'ChatPromptTemplate', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'PromptInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain', 'prompts', 'chat', 'ChatPromptTemplate'], 'name': 'ChatPromptTemplate'}}, {'id': 2, 'type': 'schema', 'data': 'ChatPromptTemplateOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'question': 'What is your name?'}, outputs={'output': ChatPromptValue(messages=[SystemMessage(content='You are a nice assistant.'), HumanMessage(content='What is your name?')])}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:1'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000001'), Run(id=UUID('00000000-0000-4000-8000-000000000002'), name='FakeListChatModel', start_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), run_type='llm', end_time=FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), extra={'invocation_params': {'responses': ['foo'], '_type': 'fake-list-chat-model', 'stop': None}, 'options': {'stop': None}, 'batch_size': 1, 'metadata': {'ls_model_type': 'chat'}}, error=None, serialized={'lc': 1, 'type': 'not_implemented', 'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'repr': "FakeListChatModel(responses=['foo'])", 'name': 'FakeListChatModel', 'graph': {'nodes': [{'id': 0, 'type': 'schema', 'data': 'FakeListChatModelInput'}, {'id': 1, 'type': 'runnable', 'data': {'id': ['langchain_core', 'language_models', 'fake_chat_models', 'FakeListChatModel'], 'name': 'FakeListChatModel'}}, {'id': 2, 'type': 'schema', 'data': 'FakeListChatModelOutput'}], 'edges': [{'source': 0, 'target': 1}, {'source': 1, 'target': 2}]}}, events=[{'name': 'start', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}, {'name': 'end', 'time': FakeDatetime(2023, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)}], inputs={'prompts': ['System: You are a nice assistant.\nHuman: What is your name?']}, outputs={'generations': [[{'text': 'foo', 'generation_info': None, 'type': 'ChatGeneration', 'message': {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'foo', 'type': 'ai', 'id': 'run-00000000-0000-4000-8000-000000000002-0', 'tool_calls': [], 'invalid_tool_calls': []}}}]], 'llm_output': None, 'run': None}, reference_example_id=None, parent_run_id=UUID('00000000-0000-4000-8000-000000000000'), tags=['seq:step:2'], child_runs=[], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000.20230101T000000000000Z00000000-0000-4000-8000-000000000002')], trace_id=UUID('00000000-0000-4000-8000-000000000000'), dotted_order='20230101T000000000000Z00000000-0000-4000-8000-000000000000'),
   ])
 # ---
 # name: test_prompt_with_llm
diff --git a/libs/core/tests/unit_tests/runnables/test_runnable_events_v1.py b/libs/core/tests/unit_tests/runnables/test_runnable_events_v1.py
index aa7ff7c1d4d..26d0825d542 100644
--- a/libs/core/tests/unit_tests/runnables/test_runnable_events_v1.py
+++ b/libs/core/tests/unit_tests/runnables/test_runnable_events_v1.py
@@ -476,7 +476,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"input": {"messages": [[HumanMessage(content="hello")]]}},
             "event": "on_chat_model_start",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -484,7 +484,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -492,7 +492,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -500,7 +500,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -526,7 +526,7 @@ async def test_astream_events_from_model() -> None:
                 },
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -569,7 +569,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"input": {"messages": [[HumanMessage(content="hello")]]}},
             "event": "on_chat_model_start",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -577,7 +577,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -585,7 +585,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -593,7 +593,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -619,7 +619,7 @@ async def test_astream_events_from_model() -> None:
                 },
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -724,7 +724,12 @@ async def test_event_stream_with_simple_chain() -> None:
                 }
             },
             "event": "on_chat_model_start",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -732,7 +737,12 @@ async def test_event_stream_with_simple_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id="ai1")},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -748,7 +758,12 @@ async def test_event_stream_with_simple_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id="ai1")},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -764,7 +779,12 @@ async def test_event_stream_with_simple_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id="ai1")},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -805,7 +825,12 @@ async def test_event_stream_with_simple_chain() -> None:
                 },
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
diff --git a/libs/core/tests/unit_tests/runnables/test_runnable_events_v2.py b/libs/core/tests/unit_tests/runnables/test_runnable_events_v2.py
index 47c69fe5f90..677a560a1aa 100644
--- a/libs/core/tests/unit_tests/runnables/test_runnable_events_v2.py
+++ b/libs/core/tests/unit_tests/runnables/test_runnable_events_v2.py
@@ -417,7 +417,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"input": "hello"},
             "event": "on_chat_model_start",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -425,7 +425,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -433,7 +433,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -441,7 +441,7 @@ async def test_astream_events_from_model() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -451,7 +451,7 @@ async def test_astream_events_from_model() -> None:
                 "output": AIMessageChunk(content="hello world!", id=AnyStr()),
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -495,7 +495,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"input": {"messages": [[HumanMessage(content="hello")]]}},
             "event": "on_chat_model_start",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -503,7 +503,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -511,7 +511,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -519,7 +519,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -530,7 +530,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "output": AIMessage(content="hello world!", id=AnyStr()),
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -573,7 +573,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"input": {"messages": [[HumanMessage(content="hello")]]}},
             "event": "on_chat_model_start",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -581,7 +581,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -589,7 +589,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -597,7 +597,7 @@ async def test_astream_with_model_in_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id=AnyStr())},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -608,7 +608,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "output": AIMessage(content="hello world!", id=AnyStr()),
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b"},
+            "metadata": {"a": "b", "ls_model_type": "chat", "ls_stop": "<stop_token>"},
             "name": "my_model",
             "run_id": "",
             "tags": ["my_model"],
@@ -713,7 +713,12 @@ async def test_event_stream_with_simple_chain() -> None:
                 }
             },
             "event": "on_chat_model_start",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -721,7 +726,12 @@ async def test_event_stream_with_simple_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="hello", id="ai1")},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -737,7 +747,12 @@ async def test_event_stream_with_simple_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id="ai1")},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -753,7 +768,12 @@ async def test_event_stream_with_simple_chain() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world!", id="ai1")},
             "event": "on_chat_model_stream",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -779,7 +799,12 @@ async def test_event_stream_with_simple_chain() -> None:
                 "output": AIMessageChunk(content="hello world!", id="ai1"),
             },
             "event": "on_chat_model_end",
-            "metadata": {"a": "b", "foo": "bar"},
+            "metadata": {
+                "a": "b",
+                "foo": "bar",
+                "ls_model_type": "chat",
+                "ls_stop": "<stop_token>",
+            },
             "name": "my_model",
             "run_id": "",
             "tags": ["my_chain", "my_model", "seq:step:2"],
@@ -1459,7 +1484,7 @@ async def test_events_astream_config() -> None:
         {
             "data": {"input": "hello"},
             "event": "on_chat_model_start",
-            "metadata": {},
+            "metadata": {"ls_model_type": "chat"},
             "name": "GenericFakeChatModel",
             "run_id": "",
             "tags": [],
@@ -1467,7 +1492,7 @@ async def test_events_astream_config() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="Goodbye", id="ai2")},
             "event": "on_chat_model_stream",
-            "metadata": {},
+            "metadata": {"ls_model_type": "chat"},
             "name": "GenericFakeChatModel",
             "run_id": "",
             "tags": [],
@@ -1475,7 +1500,7 @@ async def test_events_astream_config() -> None:
         {
             "data": {"chunk": AIMessageChunk(content=" ", id="ai2")},
             "event": "on_chat_model_stream",
-            "metadata": {},
+            "metadata": {"ls_model_type": "chat"},
             "name": "GenericFakeChatModel",
             "run_id": "",
             "tags": [],
@@ -1483,7 +1508,7 @@ async def test_events_astream_config() -> None:
         {
             "data": {"chunk": AIMessageChunk(content="world", id="ai2")},
             "event": "on_chat_model_stream",
-            "metadata": {},
+            "metadata": {"ls_model_type": "chat"},
             "name": "GenericFakeChatModel",
             "run_id": "",
             "tags": [],
@@ -1493,7 +1518,7 @@ async def test_events_astream_config() -> None:
                 "output": AIMessageChunk(content="Goodbye world", id="ai2"),
             },
             "event": "on_chat_model_end",
-            "metadata": {},
+            "metadata": {"ls_model_type": "chat"},
             "name": "GenericFakeChatModel",
             "run_id": "",
             "tags": [],
diff --git a/libs/partners/ai21/tests/unit_tests/test_standard.py b/libs/partners/ai21/tests/unit_tests/test_standard.py
index e0b9c5b98c7..2884252eef3 100644
--- a/libs/partners/ai21/tests/unit_tests/test_standard.py
+++ b/libs/partners/ai21/tests/unit_tests/test_standard.py
@@ -21,6 +21,17 @@ class TestAI21J2(ChatModelUnitTests):
             "api_key": "test_api_key",
         }
 
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_standard_params(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_standard_params(
+            chat_model_class,
+            chat_model_params,
+        )
+
 
 class TestAI21Jamba(ChatModelUnitTests):
     @pytest.fixture
@@ -33,3 +44,14 @@ class TestAI21Jamba(ChatModelUnitTests):
             "model": "jamba-instruct",
             "api_key": "test_api_key",
         }
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_standard_params(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_standard_params(
+            chat_model_class,
+            chat_model_params,
+        )
diff --git a/libs/partners/anthropic/langchain_anthropic/chat_models.py b/libs/partners/anthropic/langchain_anthropic/chat_models.py
index 82c5554bf05..73b60dfa2ab 100644
--- a/libs/partners/anthropic/langchain_anthropic/chat_models.py
+++ b/libs/partners/anthropic/langchain_anthropic/chat_models.py
@@ -30,6 +30,7 @@ from langchain_core.callbacks import (
 from langchain_core.language_models import LanguageModelInput
 from langchain_core.language_models.chat_models import (
     BaseChatModel,
+    LangSmithParams,
     agenerate_from_stream,
     generate_from_stream,
 )
@@ -326,6 +327,23 @@ class ChatAnthropic(BaseChatModel):
             "default_request_timeout": self.default_request_timeout,
         }
 
+    def _get_ls_params(
+        self, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> LangSmithParams:
+        """Get the parameters used to invoke the model."""
+        params = self._get_invocation_params(stop=stop, **kwargs)
+        ls_params = LangSmithParams(
+            ls_provider="anthropic",
+            ls_model_name=self.model,
+            ls_model_type="chat",
+            ls_temperature=params.get("temperature", self.temperature),
+        )
+        if ls_max_tokens := params.get("max_tokens", self.max_tokens):
+            ls_params["ls_max_tokens"] = ls_max_tokens
+        if ls_stop := stop or params.get("stop", None):
+            ls_params["ls_stop"] = ls_stop
+        return ls_params
+
     @root_validator(pre=True)
     def build_extra(cls, values: Dict) -> Dict:
         extra = values.get("model_kwargs", {})
diff --git a/libs/partners/fireworks/tests/unit_tests/test_standard.py b/libs/partners/fireworks/tests/unit_tests/test_standard.py
index 455af60288d..1e12ffe6ebd 100644
--- a/libs/partners/fireworks/tests/unit_tests/test_standard.py
+++ b/libs/partners/fireworks/tests/unit_tests/test_standard.py
@@ -19,3 +19,14 @@ class TestFireworksStandard(ChatModelUnitTests):
         return {
             "api_key": "test_api_key",
         }
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_standard_params(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_standard_params(
+            chat_model_class,
+            chat_model_params,
+        )
diff --git a/libs/partners/groq/tests/unit_tests/test_standard.py b/libs/partners/groq/tests/unit_tests/test_standard.py
index 38841230a9a..674896076aa 100644
--- a/libs/partners/groq/tests/unit_tests/test_standard.py
+++ b/libs/partners/groq/tests/unit_tests/test_standard.py
@@ -13,3 +13,14 @@ class TestGroqStandard(ChatModelUnitTests):
     @pytest.fixture
     def chat_model_class(self) -> Type[BaseChatModel]:
         return ChatGroq
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_standard_params(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_standard_params(
+            chat_model_class,
+            chat_model_params,
+        )
diff --git a/libs/partners/mistralai/tests/unit_tests/test_standard.py b/libs/partners/mistralai/tests/unit_tests/test_standard.py
index 46ef3ec3a44..03cb5429fa4 100644
--- a/libs/partners/mistralai/tests/unit_tests/test_standard.py
+++ b/libs/partners/mistralai/tests/unit_tests/test_standard.py
@@ -13,3 +13,14 @@ class TestMistralStandard(ChatModelUnitTests):
     @pytest.fixture
     def chat_model_class(self) -> Type[BaseChatModel]:
         return ChatMistralAI
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_standard_params(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_standard_params(
+            chat_model_class,
+            chat_model_params,
+        )
diff --git a/libs/partners/openai/langchain_openai/chat_models/azure.py b/libs/partners/openai/langchain_openai/chat_models/azure.py
index a594aa9e743..0f5133a4e57 100644
--- a/libs/partners/openai/langchain_openai/chat_models/azure.py
+++ b/libs/partners/openai/langchain_openai/chat_models/azure.py
@@ -6,6 +6,7 @@ import os
 from typing import Any, Callable, Dict, List, Optional, Union
 
 import openai
+from langchain_core.language_models.chat_models import LangSmithParams
 from langchain_core.outputs import ChatResult
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
@@ -228,6 +229,16 @@ class AzureChatOpenAI(BaseChatOpenAI):
             "openai_api_version": self.openai_api_version,
         }
 
+    def _get_ls_params(
+        self, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> LangSmithParams:
+        """Get the parameters used to invoke the model."""
+        params = super()._get_ls_params(stop=stop, **kwargs)
+        params["ls_provider"] = "azure"
+        if self.deployment_name:
+            params["ls_model_name"] = self.deployment_name
+        return params
+
     def _create_chat_result(
         self, response: Union[dict, openai.BaseModel]
     ) -> ChatResult:
diff --git a/libs/partners/openai/langchain_openai/chat_models/base.py b/libs/partners/openai/langchain_openai/chat_models/base.py
index 5a21815ec26..1ede891316f 100644
--- a/libs/partners/openai/langchain_openai/chat_models/base.py
+++ b/libs/partners/openai/langchain_openai/chat_models/base.py
@@ -36,6 +36,7 @@ from langchain_core.callbacks import (
 from langchain_core.language_models import LanguageModelInput
 from langchain_core.language_models.chat_models import (
     BaseChatModel,
+    LangSmithParams,
     agenerate_from_stream,
     generate_from_stream,
 )
@@ -639,6 +640,23 @@ class BaseChatOpenAI(BaseChatModel):
             **kwargs,
         }
 
+    def _get_ls_params(
+        self, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> LangSmithParams:
+        """Get standard params for tracing."""
+        params = self._get_invocation_params(stop=stop, **kwargs)
+        ls_params = LangSmithParams(
+            ls_provider="openai",
+            ls_model_name=self.model_name,
+            ls_model_type="chat",
+            ls_temperature=params.get("temperature", self.temperature),
+        )
+        if ls_max_tokens := params.get("max_tokens", self.max_tokens):
+            ls_params["ls_max_tokens"] = ls_max_tokens
+        if ls_stop := stop or params.get("stop", None):
+            ls_params["ls_stop"] = ls_stop
+        return ls_params
+
     @property
     def _llm_type(self) -> str:
         """Return type of chat model."""
diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_azure.py b/libs/partners/openai/tests/unit_tests/chat_models/test_azure.py
index 97d73545ae6..e9f18476328 100644
--- a/libs/partners/openai/tests/unit_tests/chat_models/test_azure.py
+++ b/libs/partners/openai/tests/unit_tests/chat_models/test_azure.py
@@ -28,3 +28,7 @@ def test_initialize_more() -> None:
     assert llm.deployment_name == "35-turbo-dev"
     assert llm.openai_api_version == "2023-05-15"
     assert llm.temperature == 0
+
+    ls_params = llm._get_ls_params()
+    assert ls_params["ls_provider"] == "azure"
+    assert ls_params["ls_model_name"] == "35-turbo-dev"
diff --git a/libs/partners/together/langchain_together/chat_models.py b/libs/partners/together/langchain_together/chat_models.py
index 7dff1ca948e..0ecf9fd57b5 100644
--- a/libs/partners/together/langchain_together/chat_models.py
+++ b/libs/partners/together/langchain_together/chat_models.py
@@ -9,6 +9,7 @@ from typing import (
 )
 
 import openai
+from langchain_core.language_models.chat_models import LangSmithParams
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
@@ -54,6 +55,14 @@ class ChatTogether(BaseChatOpenAI):
         """Return type of chat model."""
         return "together-chat"
 
+    def _get_ls_params(
+        self, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> LangSmithParams:
+        """Get the parameters used to invoke the model."""
+        params = super()._get_ls_params(stop=stop, **kwargs)
+        params["ls_provider"] = "together"
+        return params
+
     model_name: str = Field(default="meta-llama/Llama-3-8b-chat-hf", alias="model")
     """Model name to use."""
     together_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
diff --git a/libs/partners/together/tests/unit_tests/test_chat_models.py b/libs/partners/together/tests/unit_tests/test_chat_models.py
index ca86ecba420..26710878842 100644
--- a/libs/partners/together/tests/unit_tests/test_chat_models.py
+++ b/libs/partners/together/tests/unit_tests/test_chat_models.py
@@ -28,6 +28,8 @@ def test_together_model_param() -> None:
     assert llm.model_name == "foo"
     llm = ChatTogether(model_name="foo")
     assert llm.model_name == "foo"
+    ls_params = llm._get_ls_params()
+    assert ls_params["ls_provider"] == "together"
 
 
 def test_function_dict_to_message_function_message() -> None:
diff --git a/libs/partners/upstage/langchain_upstage/chat_models.py b/libs/partners/upstage/langchain_upstage/chat_models.py
index 1db0421a5b0..a8466a78642 100644
--- a/libs/partners/upstage/langchain_upstage/chat_models.py
+++ b/libs/partners/upstage/langchain_upstage/chat_models.py
@@ -7,6 +7,7 @@ from typing import (
 )
 
 import openai
+from langchain_core.language_models.chat_models import LangSmithParams
 from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
@@ -52,6 +53,14 @@ class ChatUpstage(BaseChatOpenAI):
         """Return type of chat model."""
         return "upstage-chat"
 
+    def _get_ls_params(
+        self, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> LangSmithParams:
+        """Get the parameters used to invoke the model."""
+        params = super()._get_ls_params(stop=stop, **kwargs)
+        params["ls_provider"] = "upstage"
+        return params
+
     model_name: str = Field(default="solar-1-mini-chat", alias="model")
     """Model name to use."""
     upstage_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
diff --git a/libs/partners/upstage/tests/unit_tests/test_chat_models.py b/libs/partners/upstage/tests/unit_tests/test_chat_models.py
index 3997cff4df3..0af4f4acddd 100644
--- a/libs/partners/upstage/tests/unit_tests/test_chat_models.py
+++ b/libs/partners/upstage/tests/unit_tests/test_chat_models.py
@@ -28,6 +28,8 @@ def test_upstage_model_param() -> None:
     assert llm.model_name == "foo"
     llm = ChatUpstage(model_name="foo")
     assert llm.model_name == "foo"
+    ls_params = llm._get_ls_params()
+    assert ls_params["ls_provider"] == "upstage"
 
 
 def test_function_dict_to_message_function_message() -> None:
diff --git a/libs/standard-tests/langchain_standard_tests/unit_tests/chat_models.py b/libs/standard-tests/langchain_standard_tests/unit_tests/chat_models.py
index 44f30969b95..a3e71411b0c 100644
--- a/libs/standard-tests/langchain_standard_tests/unit_tests/chat_models.py
+++ b/libs/standard-tests/langchain_standard_tests/unit_tests/chat_models.py
@@ -1,9 +1,9 @@
 from abc import ABC, abstractmethod
-from typing import Type
+from typing import List, Literal, Optional, Type
 
 import pytest
 from langchain_core.language_models import BaseChatModel
-from langchain_core.pydantic_v1 import BaseModel, Field
+from langchain_core.pydantic_v1 import BaseModel, Field, ValidationError
 from langchain_core.tools import tool
 
 
@@ -89,3 +89,29 @@ class ChatModelUnitTests(ABC):
         model = chat_model_class(**chat_model_params)
         assert model is not None
         assert model.with_structured_output(Person) is not None
+
+    def test_standard_params(
+        self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
+    ) -> None:
+        class ExpectedParams(BaseModel):
+            ls_provider: str
+            ls_model_name: str
+            ls_model_type: Literal["chat"]
+            ls_temperature: Optional[float]
+            ls_max_tokens: Optional[int]
+            ls_stop: Optional[List[str]]
+
+        model = chat_model_class(**chat_model_params)
+        ls_params = model._get_ls_params()
+        try:
+            ExpectedParams(**ls_params)
+        except ValidationError as e:
+            pytest.fail(f"Validation error: {e}")
+
+        # Test optional params
+        model = chat_model_class(max_tokens=10, stop=["test"], **chat_model_params)
+        ls_params = model._get_ls_params()
+        try:
+            ExpectedParams(**ls_params)
+        except ValidationError as e:
+            pytest.fail(f"Validation error: {e}")