fix(workflow): prevent fixed speech continuation

backend/services/brains/workflow_brain.py

@@ -42,6 +42,7 @@ from services.action_runtime import (
     ActionStatus,
 )
 from services.action_stage import ActionStageRunner, ActionStageSpec, StageAction
+from services.fixed_speech import fixed_speech_context_message
 from services.knowledge import search as search_knowledge
 from services.message_policy import (
     MESSAGE_COMPLETION_POLICIES,
@@ -794,9 +795,9 @@ class WorkflowBrain(BaseBrain):
                     source="workflow-edge-transition",
                     node_id=str(edge.get("target") or "") or None,
                 )
-                context_messages.append(
-                    {"role": "assistant", "content": content}
-                )
+                context_message = fixed_speech_context_message(content)
+                if context_message is not None:
+                    context_messages.append(context_message)
         return await self._resolve_path(
             str(edge.get("target") or ""),
             leading_messages=context_messages,
@@ -828,10 +829,11 @@ class WorkflowBrain(BaseBrain):
                         if triggering_user_message
                         else {"role": "user", "content": triggering_user_text}
                     )
-                    agent_messages = [
-                        current_user_message,
-                        *context_messages,
-                    ]
+                    # Fixed speech is represented by system facts. Put those
+                    # facts before the triggering user turn so RESET contexts
+                    # still end with the real user input rather than a control
+                    # message.
+                    agent_messages = [*context_messages, current_user_message]
                 return self._agent_config(node_id, agent_messages)
             if node_type == "end":
                 await self._enter_end(node_id)
@@ -871,9 +873,9 @@ class WorkflowBrain(BaseBrain):
                         source="workflow-edge-transition",
                         node_id=target_id or None,
                     )
-                    context_messages.append(
-                        {"role": "assistant", "content": content}
-                    )
+                    context_message = fixed_speech_context_message(content)
+                    if context_message is not None:
+                        context_messages.append(context_message)
             node_id = str(edge.get("target") or "")
         raise RuntimeError("工作流连续自动跳转超过安全上限")
 
@@ -974,9 +976,9 @@ class WorkflowBrain(BaseBrain):
                 dict(message) for message in continuation.context_messages
             ]
             if result.speech:
-                context_messages.append(
-                    {"role": "assistant", "content": result.speech}
-                )
+                context_message = fixed_speech_context_message(result.speech)
+                if context_message is not None:
+                    context_messages.append(context_message)
 
             if not self._engine.has_outgoing(continuation.node_id):
                 self._state.enter(