.

Signed-off-by: Bryan Qiu <bryan.qiu@databricks.com>

Author: bbqiu

integrations/langchain/src/databricks_langchain/chat_models.py

@@ -1055,6 +1055,7 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
         return {"role": "user", **message_dict}
     elif isinstance(message, AIMessage):
         if tool_calls := _get_tool_calls_from_ai_message(message):
+            print(tool_calls)
             message_dict["tool_calls"] = tool_calls  # type: ignore[assignment]
             # If tool calls present, content null value should be None not empty string.
             message_dict["content"] = message_dict["content"] or None  # type: ignore[assignment]
@@ -1196,6 +1197,14 @@ def _get_tool_calls_from_ai_message(message: AIMessage) -> List[Dict]:
         for tc in message.invalid_tool_calls
     ]
 
+    """
+    thought signature encodes model reasoning
+    it is required for each tool call to gemini 3 pro - https://arc.net/l/quote/jhoeoqbl
+    this means we need to encode this info in the responses events in order to fix this bug, in addition to the work on this PR
+    
+    will have to change _langchain_message_stream_to_responses_stream
+    """
+
     if tool_calls or invalid_tool_calls:
         # Merge thoughtSignature from additional_kwargs if present
         all_tool_calls = tool_calls + invalid_tool_calls

integrations/langchain/tests/integration_tests/test_chat_models.py

@@ -877,6 +877,34 @@ def test_chat_databricks_with_gemini():
     os.environ["DATABRICKS_CONFIG_PROFILE"] = "dogfood"
     from .agent import AGENT
 
-    result = AGENT.predict({"input": [{"role": "user", "content": "What is 6*7 in Python?"}]})
+    result = AGENT.predict(
+        {
+            "input": [
+                {"role": "user", "content": "What is 6*7 in Python?"},
+                {
+                    "type": "function_call",
+                    "id": "lc_run--e58dec26-ce5d-4597-b4f8-28e6db62cd49",
+                    "call_id": "system__ai__python_exec",
+                    "name": "system__ai__python_exec",
+                    "arguments": '{"code": "print(6 * 7)"}',
+                },
+                {
+                    "type": "function_call_output",
+                    "call_id": "system__ai__python_exec",
+                    "output": '{"format": "SCALAR", "value": "42\\n"}',
+                },
+                {
+                    "type": "message",
+                    "id": "lc_run--dd658def-dfdc-4bc7-b0d9-b6e25d1ecc48",
+                    "content": [
+                        {"text": "The result of `6 * 7` in Python is 42.", "type": "output_text"}
+                    ],
+                    "role": "assistant",
+                },
+            ]
+        }
+    )
     assert result is not None
     assert result.output is not None
+    print(result.model_dump())
+    assert False