community: add standard chat model params to Ollama (#22446)

libs/community/langchain_community/chat_models/ollama.py

@@ -6,7 +6,7 @@ from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_core.language_models.chat_models import BaseChatModel, LangSmithParams
 from langchain_core.messages import (
     AIMessage,
     AIMessageChunk,
@@ -69,6 +69,23 @@ class ChatOllama(BaseChatModel, _OllamaCommon):
         """Return whether this model can be serialized by Langchain."""
         return False
 
+    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="ollama",
+            ls_model_name=self.model,
+            ls_model_type="chat",
+            ls_temperature=params.get("temperature", self.temperature),
+        )
+        if ls_max_tokens := params.get("num_predict", self.num_predict):
+            ls_params["ls_max_tokens"] = ls_max_tokens
+        if ls_stop := stop or params.get("stop", None) or self.stop:
+            ls_params["ls_stop"] = ls_stop
+        return ls_params
+
     @deprecated("0.0.3", alternative="_convert_messages_to_ollama_messages")
     def _format_message_as_text(self, message: BaseMessage) -> str:
         if isinstance(message, ChatMessage):

libs/community/tests/unit_tests/chat_models/test_ollama.py

@@ -0,0 +1,35 @@
+from typing import List, Literal, Optional
+
+import pytest
+from langchain_core.pydantic_v1 import BaseModel, ValidationError
+
+from langchain_community.chat_models import ChatOllama
+
+
+def test_standard_params() -> 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 = ChatOllama(model="llama3")
+    ls_params = model._get_ls_params()
+    try:
+        ExpectedParams(**ls_params)
+    except ValidationError as e:
+        pytest.fail(f"Validation error: {e}")
+    assert ls_params["ls_model_name"] == "llama3"
+
+    # Test optional params
+    model = ChatOllama(num_predict=10, stop=["test"], temperature=0.33)
+    ls_params = model._get_ls_params()
+    try:
+        ExpectedParams(**ls_params)
+    except ValidationError as e:
+        pytest.fail(f"Validation error: {e}")
+    assert ls_params["ls_max_tokens"] == 10
+    assert ls_params["ls_stop"] == ["test"]
+    assert ls_params["ls_temperature"] == 0.33