feat(genai): add logprobs support

libs/genai/langchain_google_genai/chat_models.py

@@ -896,6 +896,8 @@
             except (AttributeError, TypeError):
                 thought_sig = None
 
+        has_function_call = hasattr(part, "function_call") and part.function_call
+
         if hasattr(part, "thought") and part.thought:
             thinking_message = {
                 "type": "thinking",
@@ -1031,21 +1033,37 @@
 
             # If this function_call Part has a signature, track it separately
             if thought_sig:
-                if _FUNCTION_CALL_THOUGHT_SIGNATURES_MAP_KEY not in additional_kwargs:
-                    additional_kwargs[_FUNCTION_CALL_THOUGHT_SIGNATURES_MAP_KEY] = {}
-                additional_kwargs[_FUNCTION_CALL_THOUGHT_SIGNATURES_MAP_KEY][
-                    tool_call_id
-                ] = (
-                    _bytes_to_base64(thought_sig)
-                    if isinstance(thought_sig, bytes)
-                    else thought_sig
-                )
+                sig_block = {
+                    "type": "function_call_signature",
+                    "signature": thought_sig,
+                }
+                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:
-        if _is_gemini_3_or_later(model_name or ""):
-            content = []
-        else:
-            content = ""
+        content = ""
+
+    if (
+        hasattr(response_candidate, "logprobs_result")
+        and response_candidate.logprobs_result
+    ):
+        # Note: logprobs is flaky, sometimes available, sometimes not
+        # https://discuss.ai.google.dev/t/logprobs-is-not-enabled-for-gemini-models/107989/15
+        response_metadata["logprobs"] = MessageToDict(
+            response_candidate.logprobs_result._pb,
+            preserving_proto_field_name=True,
+        )
+
+    if _is_gemini_3_or_later(model_name or ""):
+        content = []
+    else:
+        content = ""
     if isinstance(content, list) and any(
         isinstance(item, dict) and "executable_code" in item for item in content
     ):
@@ -1922,6 +1940,9 @@
     stop: list[str] | None = None
     """Stop sequences for the model."""
 
+    logprobs: int | None = None
+    """The number of logprobs to return."""
+
     streaming: bool | None = None
     """Whether to stream responses from the model."""
 
@@ -2102,6 +2123,7 @@
             "media_resolution": self.media_resolution,
             "thinking_budget": self.thinking_budget,
             "include_thoughts": self.include_thoughts,
+            "logprobs": self.logprobs,
             "thinking_level": self.thinking_level,
         }
 
@@ -2216,6 +2238,10 @@
             }.items()
             if v is not None
         }
+        logprobs = getattr(self, "logprobs", None)
+        if logprobs:
+            gen_config["logprobs"] = logprobs
+            gen_config["response_logprobs"] = True
         if generation_config:
             gen_config = {**gen_config, **generation_config}
 

libs/genai/tests/unit_tests/test_chat_models.py

@@ -147,24 +147,98 @@ def test_initialization_inside_threadpool() -> None:
         ).result()
 
 
-def test_client_transport() -> None:
+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
+
+    # Create proper mock response with logprobs_result
+    raw_response = {
+        "candidates": [
+            {
+                "content": {"parts": [{"text": "Test response"}]},
+                "finish_reason": 1,
+                "safety_ratings": [],
+                "logprobs_result": {
+                    "top_candidates": [
+                        {
+                            "candidates": [
+                                {"token": "Test", "log_probability": -0.1},
+                            ]
+                        }
+                    ]
+                },
+            }
+        ],
+        "prompt_feedback": {"block_reason": 0, "safety_ratings": []},
+        "usage_metadata": {
+            "prompt_token_count": 5,
+            "candidates_token_count": 2,
+            "total_token_count": 7,
+        },
+    }
+    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},
+                    ]
+                }
+            ]
+        }
+
+        mock_chat_with_retry.assert_called_once()
+        request = mock_chat_with_retry.call_args.kwargs["request"]
+        assert request.generation_config.logprobs == 1
+        assert request.generation_config.response_logprobs is True
+
+
+@pytest.mark.enable_socket
+@patch("langchain_google_genai._genai_extension.v1betaGenerativeServiceAsyncClient")
+@patch("langchain_google_genai._genai_extension.v1betaGenerativeServiceClient")
+def test_client_transport(mock_client: Mock, mock_async_client: Mock) -> None:
     """Test client transport configuration."""
-    model = ChatGoogleGenerativeAI(model=MODEL_NAME, google_api_key=FAKE_API_KEY)
+    mock_client.return_value.transport = Mock()
+    mock_client.return_value.transport.kind = "grpc"
+    model = ChatGoogleGenerativeAI(model=MODEL_NAME, google_api_key="fake-key")
     assert model.client.transport.kind == "grpc"
 
+    mock_client.return_value.transport.kind = "rest"
     model = ChatGoogleGenerativeAI(
         model=MODEL_NAME, google_api_key="fake-key", transport="rest"
     )
     assert model.client.transport.kind == "rest"
 
     async def check_async_client() -> None:
-        model = ChatGoogleGenerativeAI(model=MODEL_NAME, google_api_key=FAKE_API_KEY)
+        mock_async_client.return_value.transport = Mock()
+        mock_async_client.return_value.transport.kind = "grpc_asyncio"
+        model = ChatGoogleGenerativeAI(model=MODEL_NAME, google_api_key="fake-key")
+        _ = model.async_client
         assert model.async_client.transport.kind == "grpc_asyncio"
 
         # Test auto conversion of transport to "grpc_asyncio" from "rest"
         model = ChatGoogleGenerativeAI(
             model=MODEL_NAME, google_api_key=FAKE_API_KEY, transport="rest"
         )
+        model.async_client_running = None
+        _ = model.async_client
         assert model.async_client.transport.kind == "grpc_asyncio"
 
     asyncio.run(check_async_client())
@@ -178,6 +252,7 @@ def test_initalization_without_async() -> None:
     assert chat.async_client is None
 
 
+@pytest.mark.enable_socket
 def test_initialization_with_async() -> None:
     async def initialize_chat_with_async_client() -> ChatGoogleGenerativeAI:
         model = ChatGoogleGenerativeAI(
@@ -1720,6 +1795,7 @@ def test_grounding_metadata_multiple_parts() -> None:
     assert grounding["grounding_supports"][0]["segment"]["part_index"] == 1
 
 
+@pytest.mark.enable_socket
 @pytest.mark.parametrize(
     "is_async,mock_target,method_name",
     [
@@ -1846,6 +1922,7 @@ def mock_stream() -> Iterator[GenerateContentResponse]:
         assert "timeout" not in call_kwargs
 
 
+@pytest.mark.enable_socket
 @pytest.mark.parametrize(
     "is_async,mock_target,method_name",
     [