fix(middleware): normalize tool result adjacency before model calls (#2939)

* normalizing tool-call transcripts before invocation

* test(middleware): cover tool result regrouping edge cases

backend/packages/harness/deerflow/agents/middlewares/dangling_tool_call_middleware.py

@@ -104,45 +104,46 @@ class DanglingToolCallMiddleware(AgentMiddleware[AgentState]):
         return "[Tool call was interrupted and did not return a result.]"
 
     def _build_patched_messages(self, messages: list) -> list | None:
-        """Return a new message list with patches inserted at the correct positions.
+        """Return messages with tool results grouped after their tool-call AIMessage.
 
-        For each AIMessage with dangling tool_calls (no corresponding ToolMessage),
-        a synthetic ToolMessage is inserted immediately after that AIMessage.
-        Returns None if no patches are needed.
+        This normalizes model-bound causal order before provider serialization while
+        preserving already-valid transcripts unchanged.
         """
-        # Collect IDs of all existing ToolMessages
-        existing_tool_msg_ids: set[str] = set()
+        tool_messages_by_id: dict[str, ToolMessage] = {}
         for msg in messages:
             if isinstance(msg, ToolMessage):
-                existing_tool_msg_ids.add(msg.tool_call_id)
+                tool_messages_by_id.setdefault(msg.tool_call_id, msg)
 
-        # Check if any patching is needed
-        needs_patch = False
+        tool_call_ids: set[str] = set()
         for msg in messages:
             if getattr(msg, "type", None) != "ai":
                 continue
             for tc in self._message_tool_calls(msg):
                 tc_id = tc.get("id")
-                if tc_id and tc_id not in existing_tool_msg_ids:
-                    needs_patch = True
-                    break
-            if needs_patch:
-                break
+                if tc_id:
+                    tool_call_ids.add(tc_id)
 
-        if not needs_patch:
-            return None
-
-        # Build new list with patches inserted right after each dangling AIMessage
         patched: list = []
-        patched_ids: set[str] = set()
+        consumed_tool_msg_ids: set[str] = set()
         patch_count = 0
         for msg in messages:
+            if isinstance(msg, ToolMessage) and msg.tool_call_id in tool_call_ids:
+                continue
+
             patched.append(msg)
             if getattr(msg, "type", None) != "ai":
                 continue
+
             for tc in self._message_tool_calls(msg):
                 tc_id = tc.get("id")
-                if tc_id and tc_id not in existing_tool_msg_ids and tc_id not in patched_ids:
+                if not tc_id or tc_id in consumed_tool_msg_ids:
+                    continue
+
+                existing_tool_msg = tool_messages_by_id.get(tc_id)
+                if existing_tool_msg is not None:
+                    patched.append(existing_tool_msg)
+                    consumed_tool_msg_ids.add(tc_id)
+                else:
                     patched.append(
                         ToolMessage(
                             content=self._synthetic_tool_message_content(tc),
@@ -151,10 +152,14 @@ class DanglingToolCallMiddleware(AgentMiddleware[AgentState]):
                             status="error",
                         )
                     )
-                    patched_ids.add(tc_id)
+                    consumed_tool_msg_ids.add(tc_id)
                     patch_count += 1
 
-        logger.warning(f"Injecting {patch_count} placeholder ToolMessage(s) for dangling tool calls")
+        if patched == messages:
+            return None
+
+        if patch_count:
+            logger.warning(f"Injecting {patch_count} placeholder ToolMessage(s) for dangling tool calls")
         return patched
 
     @override