core, standard tests, partner packages: add test for model params (#21677)

1. Adds `.get_ls_params` to BaseChatModel which returns ```python 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]] ``` by default it will only return ```python {ls_model_type="chat", ls_stop=stop} ``` 2. Add these params to inheritable metadata in `CallbackManager.configure` 3. Implement `.get_ls_params` and populate all params for Anthropic + all subclasses of BaseChatOpenAI Sample trace: https://smith.langchain.com/public/d2962673-4c83-47c7-b51e-61d07aaffb1b/r **OpenAI**: <img width="984" alt="Screenshot 2024-05-17 at 10 03 35 AM" src="https://github.com/langchain-ai/langchain/assets/26529506/2ef41f74-a9df-4e0e-905d-da74fa82a910"> **Anthropic**: <img width="978" alt="Screenshot 2024-05-17 at 10 06 07 AM" src="https://github.com/langchain-ai/langchain/assets/26529506/39701c9f-7da5-4f1a-ab14-84e9169d63e7"> **Mistral** (and all others for which params are not yet populated): <img width="977" alt="Screenshot 2024-05-17 at 10 08 43 AM" src="https://github.com/langchain-ai/langchain/assets/26529506/37d7d894-fec2-4300-986f-49a5f0191b03">
2025-06-26 16:43:35 +00:00 · 2024-05-17 13:51:26 -04:00 · 2024-05-17 13:51:26 -04:00 · 181dfef118
commit 181dfef118
parent 4ca2149b70
17 changed files with 293 additions and 50 deletions
--- 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,
        )

--- a/libs/core/tests/unit_tests/runnables/snapshots/test_runnable.ambr
+++ b/libs/core/tests/unit_tests/runnables/snapshots/test_runnable.ambr
--- 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"],
--- 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": [],
--- 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,
+        )
--- 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", {})
--- 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,
+        )
--- 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,
+        )
--- 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,
+        )
--- 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:
--- 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."""
--- 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"
--- 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")
--- 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:
--- 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")
--- 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:
--- 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}")