feat(core): allow overriding ls_model_name from kwargs (#32541)

libs/core/langchain_core/language_models/chat_models.py

@@ -720,7 +720,9 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             ls_params["ls_stop"] = stop
 
         # model
-        if hasattr(self, "model") and isinstance(self.model, str):
+        if "model" in kwargs and isinstance(kwargs["model"], str):
+            ls_params["ls_model_name"] = kwargs["model"]
+        elif hasattr(self, "model") and isinstance(self.model, str):
             ls_params["ls_model_name"] = self.model
         elif hasattr(self, "model_name") and isinstance(self.model_name, str):
             ls_params["ls_model_name"] = self.model_name

libs/core/langchain_core/language_models/llms.py

@@ -357,7 +357,9 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             ls_params["ls_stop"] = stop
 
         # model
-        if hasattr(self, "model") and isinstance(self.model, str):
+        if "model" in kwargs and isinstance(kwargs["model"], str):
+            ls_params["ls_model_name"] = kwargs["model"]
+        elif hasattr(self, "model") and isinstance(self.model, str):
             ls_params["ls_model_name"] = self.model
         elif hasattr(self, "model_name") and isinstance(self.model_name, str):
             ls_params["ls_model_name"] = self.model_name

libs/core/tests/unit_tests/language_models/chat_models/test_base.py

@@ -654,3 +654,57 @@ def test_normalize_messages_edge_cases() -> None:
         )
     ]
     assert messages == _normalize_messages(messages)
+
+
+def test_get_ls_params() -> None:
+    class LSParamsModel(BaseChatModel):
+        model: str = "foo"
+        temperature: float = 0.1
+        max_tokens: int = 1024
+
+        def _generate(
+            self,
+            messages: list[BaseMessage],
+            stop: Optional[list[str]] = None,
+            run_manager: Optional[CallbackManagerForLLMRun] = None,
+            **kwargs: Any,
+        ) -> ChatResult:
+            raise NotImplementedError
+
+        @override
+        def _stream(
+            self,
+            messages: list[BaseMessage],
+            stop: Optional[list[str]] = None,
+            run_manager: Optional[CallbackManagerForLLMRun] = None,
+            **kwargs: Any,
+        ) -> Iterator[ChatGenerationChunk]:
+            raise NotImplementedError
+
+        @property
+        def _llm_type(self) -> str:
+            return "fake-chat-model"
+
+    llm = LSParamsModel()
+
+    # Test standard tracing params
+    ls_params = llm._get_ls_params()
+    assert ls_params == {
+        "ls_provider": "lsparamsmodel",
+        "ls_model_type": "chat",
+        "ls_model_name": "foo",
+        "ls_temperature": 0.1,
+        "ls_max_tokens": 1024,
+    }
+
+    ls_params = llm._get_ls_params(model="bar")
+    assert ls_params["ls_model_name"] == "bar"
+
+    ls_params = llm._get_ls_params(temperature=0.2)
+    assert ls_params["ls_temperature"] == 0.2
+
+    ls_params = llm._get_ls_params(max_tokens=2048)
+    assert ls_params["ls_max_tokens"] == 2048
+
+    ls_params = llm._get_ls_params(stop=["stop"])
+    assert ls_params["ls_stop"] == ["stop"]

libs/core/tests/unit_tests/language_models/llms/test_base.py

@@ -232,3 +232,48 @@ async def test_astream_implementation_uses_astream() -> None:
     model = ModelWithAsyncStream()
     chunks = [chunk async for chunk in model.astream("anything")]
     assert chunks == ["a", "b"]
+
+
+def test_get_ls_params() -> None:
+    class LSParamsModel(BaseLLM):
+        model: str = "foo"
+        temperature: float = 0.1
+        max_tokens: int = 1024
+
+        @override
+        def _generate(
+            self,
+            prompts: list[str],
+            stop: Optional[list[str]] = None,
+            run_manager: Optional[CallbackManagerForLLMRun] = None,
+            **kwargs: Any,
+        ) -> LLMResult:
+            raise NotImplementedError
+
+        @property
+        def _llm_type(self) -> str:
+            return "fake-model"
+
+    llm = LSParamsModel()
+
+    # Test standard tracing params
+    ls_params = llm._get_ls_params()
+    assert ls_params == {
+        "ls_provider": "lsparamsmodel",
+        "ls_model_type": "llm",
+        "ls_model_name": "foo",
+        "ls_temperature": 0.1,
+        "ls_max_tokens": 1024,
+    }
+
+    ls_params = llm._get_ls_params(model="bar")
+    assert ls_params["ls_model_name"] == "bar"
+
+    ls_params = llm._get_ls_params(temperature=0.2)
+    assert ls_params["ls_temperature"] == 0.2
+
+    ls_params = llm._get_ls_params(max_tokens=2048)
+    assert ls_params["ls_max_tokens"] == 2048
+
+    ls_params = llm._get_ls_params(stop=["stop"])
+    assert ls_params["ls_stop"] == ["stop"]