fix: add isinstance guard in structured output, add tool_calls extraction in LangChainAgentRunner, add _coerce_input comment

Author: jsonbailey

packages/ai-providers/server-ai-langchain/src/ldai_langchain/langchain_agent_runner.py

@@ -54,11 +54,13 @@ async def run(
             })
             messages = result.get("messages", [])
             output = extract_last_message_content(messages)
+            tool_calls = _extract_tool_calls(messages)
             return RunnerResult(
                 content=output,
                 metrics=LDAIMetrics(
                     success=True,
                     usage=sum_token_usage_from_messages(messages),
+                    tool_calls=tool_calls if tool_calls else None,
                 ),
                 raw=result,
             )
@@ -72,3 +74,27 @@ async def run(
     def get_agent(self) -> Any:
         """Return the underlying compiled LangChain agent."""
         return self._agent
+
+
+def _extract_tool_calls(messages: Any) -> list:
+    """
+    Extract tool-call names from a LangChain agent's message list.
+
+    LangChain's ``AIMessage`` exposes ``.tool_calls`` as a list of dicts
+    (``{'name': ..., 'args': ..., 'id': ...}``). Some providers emit
+    OpenAI-style objects with ``.function.name`` instead; handle both shapes.
+    """
+    tool_calls: list = []
+    for msg in messages or []:
+        msg_tool_calls = getattr(msg, 'tool_calls', None)
+        if not msg_tool_calls:
+            continue
+        for tc in msg_tool_calls:
+            if isinstance(tc, dict) and 'name' in tc:
+                tool_calls.append(tc['name'])
+            else:
+                fn = getattr(tc, 'function', None)
+                name = getattr(fn, 'name', None) if fn is not None else None
+                if name:
+                    tool_calls.append(name)
+    return tool_calls

packages/ai-providers/server-ai-langchain/src/ldai_langchain/langchain_model_runner.py

@@ -56,6 +56,8 @@ async def run(
             return await self._run_structured(messages, output_type)
         return await self._run_completion(messages)
 
+    # convert_messages_to_langchain only accepts List[LDMessage]; _coerce_input
+    # normalizes a bare string to [LDMessage(role='user', ...)] before that step.
     @staticmethod
     def _coerce_input(input: Any) -> List[LDMessage]:
         if isinstance(input, str):
@@ -116,7 +118,13 @@ async def _run_structured(
             raw_content = ''
             if raw_response is not None:
                 if hasattr(raw_response, 'content'):
-                    raw_content = raw_response.content or ''
+                    if isinstance(raw_response.content, str):
+                        raw_content = raw_response.content
+                    else:
+                        log.warning(
+                            f'Multimodal response not supported in structured mode. '
+                            f'Content type: {type(raw_response.content)}, Content: {raw_response.content}'
+                        )
                 usage = get_ai_usage_from_response(raw_response)
 
             if response.get('parsing_error'):