feat(genai): add logprobs support

libs/genai/langchain_google_genai/chat_models.py

@@ -929,15 +929,18 @@ def _parse_response_candidate(
                 }
                 function_call_signatures.append(sig_block)
 
-    # Add function call signatures to content only if there's already other content
-    # This preserves backward compatibility where content is "" for
-    # function-only responses
-    if function_call_signatures and content is not None:
-        for sig_block in function_call_signatures:
-            content = _append_to_content(content, sig_block)
-
-    if content is None:
-        content = ""
+        # Add function call signatures to content only if there's already other content
+        # This preserves backward compatibility where content is "" for
+        # function-only responses
+        if function_call_signatures and content is not None:
+            for sig_block in function_call_signatures:
+                content = _append_to_content(content, sig_block)
+        if hasattr(response_candidate, "logprobs_result"):
+            response_metadata["logprobs"] = proto.Message.to_dict(
+                response_candidate.logprobs_result
+            )
+        if content is None:
+            content = ""
     if isinstance(content, list) and any(
         isinstance(item, dict) and "executable_code" in item for item in content
     ):
@@ -1825,6 +1828,9 @@ class Joke(BaseModel):
     stop: Optional[List[str]] = None
     """Stop sequences for the model."""
 
+    logprobs: Optional[int] = None
+    """The number of logprobs to return."""
+
     streaming: Optional[bool] = None
     """Whether to stream responses from the model."""
 
@@ -2037,6 +2043,7 @@ def _prepare_params(
                 "max_output_tokens": self.max_output_tokens,
                 "top_k": self.top_k,
                 "top_p": self.top_p,
+                "logprobs": getattr(self, "logprobs", None),
                 "response_modalities": self.response_modalities,
                 "thinking_config": (
                     (
@@ -2058,6 +2065,8 @@ def _prepare_params(
             }.items()
             if v is not None
         }
+        if getattr(self, "logprobs", None) is not None:
+            gen_config["response_logprobs"] = True
         if generation_config:
             gen_config = {**gen_config, **generation_config}
 

libs/genai/tests/unit_tests/test_chat_models.py

@@ -137,6 +137,55 @@ def test_initialization_inside_threadpool() -> None:
         ).result()
 
 
+def test_logprobs() -> None:
+    """Test that logprobs parameter is set correctly and is in the response."""
+    llm = ChatGoogleGenerativeAI(
+        model=MODEL_NAME,
+        google_api_key=SecretStr("secret-api-key"),
+        logprobs=10,
+    )
+    assert llm.logprobs == 10
+
+    raw_response = {
+        "candidates": [
+            {
+                "content": {"parts": [{"text": "Test response"}]},
+                "logprobs_result": {
+                    "top_candidates": [
+                        {
+                            "candidates": [
+                                {"token": "Test", "log_probability": -0.1},
+                            ]
+                        }
+                    ]
+                },
+            }
+        ],
+    }
+    response = GenerateContentResponse(raw_response)
+
+    with patch(
+        "langchain_google_genai.chat_models._chat_with_retry"
+    ) as mock_chat_with_retry:
+        mock_chat_with_retry.return_value = response
+        llm = ChatGoogleGenerativeAI(
+            model=MODEL_NAME,
+            google_api_key="test-key",
+            logprobs=1,
+        )
+        result = llm.invoke("test")
+        assert "logprobs" in result.response_metadata
+        assert result.response_metadata["logprobs"] == {
+            "top_candidates": [
+                {
+                    "candidates": [
+                        {"token": "Test", "log_probability": -0.1},
+                    ]
+                }
+            ]
+        }
+
+
 def test_client_transport() -> None:
     """Test client transport configuration."""
     model = ChatGoogleGenerativeAI(model=MODEL_NAME, google_api_key="fake-key")