core, partners: implement standard tracing params for LLMs (#25410)

libs/partners/ollama/langchain_ollama/llms.py

@@ -16,7 +16,7 @@ from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain_core.language_models import BaseLLM
+from langchain_core.language_models import BaseLLM, LangSmithParams
 from langchain_core.outputs import GenerationChunk, LLMResult
 from langchain_core.pydantic_v1 import Field, root_validator
 from ollama import AsyncClient, Client, Options
@@ -155,6 +155,15 @@ class OllamaLLM(BaseLLM):
         """Return type of LLM."""
         return "ollama-llm"
 
+    def _get_ls_params(
+        self, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> LangSmithParams:
+        """Get standard params for tracing."""
+        params = super()._get_ls_params(stop=stop, **kwargs)
+        if max_tokens := kwargs.get("num_predict", self.num_predict):
+            params["ls_max_tokens"] = max_tokens
+        return params
+
     @root_validator(pre=False, skip_on_failure=True)
     def _set_clients(cls, values: dict) -> dict:
         """Set clients to use for ollama."""

libs/partners/ollama/tests/unit_tests/test_llms.py

@@ -6,3 +6,23 @@ from langchain_ollama import OllamaLLM
 def test_initialization() -> None:
     """Test integration initialization."""
     OllamaLLM(model="llama3")
+
+
+def test_model_params() -> None:
+    # Test standard tracing params
+    llm = OllamaLLM(model="llama3")
+    ls_params = llm._get_ls_params()
+    assert ls_params == {
+        "ls_provider": "ollama",
+        "ls_model_type": "llm",
+        "ls_model_name": "llama3",
+    }
+
+    llm = OllamaLLM(model="llama3", num_predict=3)
+    ls_params = llm._get_ls_params()
+    assert ls_params == {
+        "ls_provider": "ollama",
+        "ls_model_type": "llm",
+        "ls_model_name": "llama3",
+        "ls_max_tokens": 3,
+    }