fix: map agent workflow inputs

backend-fastapi/ai_platform/nodes/builtin/template_node.py

@@ -91,6 +91,8 @@ class TemplateNode(BaseNode):
                 return NodeResult(success=False, error=f'智能体不存在或未发布: {agent_code}')
 
             model_id = self.config.get('model_id') or agent.model_id
+            if not model_id:
+                model_id = await self._resolve_default_chat_model_id(context)
             if not model_id:
                 return NodeResult(success=False, error=f'智能体未配置模型: {agent.name}({agent.code})')
 
@@ -148,6 +150,22 @@ class TemplateNode(BaseNode):
                 elapsed_time=int((time.time() - start_time) * 1000),
             )
 
+    @staticmethod
+    async def _resolve_default_chat_model_id(context: NodeContext) -> str:
+        from ai_platform.models import LLMModel
+
+        result = await context.db_session.execute(
+            select(LLMModel)
+            .where(
+                LLMModel.is_deleted == False,
+                LLMModel.is_active == True,
+                LLMModel.model_type == 'chat',
+            )
+            .order_by(LLMModel.sort.desc(), LLMModel.sys_create_datetime.desc())
+        )
+        model = result.scalars().first()
+        return str(model.id) if model else ''
+
     @staticmethod
     def _build_agent_system_prompt(agent: Any) -> str:
         base_prompt = agent.system_prompt or ''

backend-fastapi/ai_platform/services/agent_service.py

@@ -9,7 +9,7 @@ from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from ai_platform.models import (
-    Agent, AgentConversation, AgentMessage, LLMModel,
+    Agent, AgentConversation, AgentMessage, AIWorkflow, LLMModel,
 )
 from .llm_service import LLMService
 
@@ -433,16 +433,16 @@ class AgentService:
                         if accumulated:
                             final_content = accumulated
                     elif event_type == 'node_complete':
-                        node_type = event.get('node_type')
+                        output = (event.get('outputs') or {}).get('output', '')
-                        if node_type == 'llm':
+                        if output:
-                            outputs = event.get('outputs', {})
+                            final_content = output
-                            output = outputs.get('output', '')
-                            if output:
-                                final_content = output
                     elif event_type == 'waiting_input':
                         is_waiting = True
                     elif event_type == 'complete':
                         total_tokens = event.get('total_tokens', 0)
+                        output = (event.get('outputs') or {}).get('output', '')
+                        if output:
+                            final_content = output
                     
                     yield event
             else:
@@ -465,7 +465,7 @@ class AgentService:
                     if attachment_texts:
                         enhanced_user_input = user_message + '\n' + '\n'.join(attachment_texts)
                 
-                workflow_inputs = {'user_input': enhanced_user_input}
+                workflow_inputs = await self._build_workflow_inputs(agent, enhanced_user_input)
                 if application_id:
                     workflow_inputs['application_id'] = application_id
                 if form_code:
@@ -495,12 +495,9 @@ class AgentService:
                         if accumulated:
                             final_content = accumulated
                     elif event_type == 'node_complete':
-                        node_type = event.get('node_type')
+                        output = (event.get('outputs') or {}).get('output', '')
-                        if node_type == 'llm':
+                        if output:
-                            outputs = event.get('outputs', {})
+                            final_content = output
-                            output = outputs.get('output', '')
-                            if output:
-                                final_content = output
                     elif event_type == 'waiting_input':
                         is_waiting = True
                         # 保存工作流运行 ID 到对话元数据
@@ -509,6 +506,9 @@ class AgentService:
                             conversation.extra_data['workflow_run_id'] = current_run_id
                     elif event_type == 'complete':
                         total_tokens = event.get('total_tokens', 0)
+                        output = (event.get('outputs') or {}).get('output', '')
+                        if output:
+                            final_content = output
                     
                     yield event
             
@@ -552,6 +552,35 @@ class AgentService:
                 'type': 'error',
                 'content': str(e),
             }
+
+    async def _build_workflow_inputs(self, agent: Agent, user_input: str) -> Dict[str, Any]:
+        workflow_inputs: Dict[str, Any] = {'user_input': user_input}
+        if not self._db or not agent.workflow_id:
+            return workflow_inputs
+
+        result = await self._db.execute(
+            select(AIWorkflow).where(
+                AIWorkflow.id == agent.workflow_id,
+                AIWorkflow.is_deleted == False,
+            )
+        )
+        workflow = result.scalar_one_or_none()
+        if not workflow:
+            return workflow_inputs
+
+        input_variables = workflow.input_variables or []
+        if any((item or {}).get('name') == 'request' for item in input_variables):
+            workflow_inputs.setdefault('request', user_input)
+        if any((item or {}).get('name') == 'issue_id' for item in input_variables):
+            workflow_inputs.setdefault('issue_id', self._extract_issue_id(user_input))
+        return workflow_inputs
+
+    @staticmethod
+    def _extract_issue_id(text: str) -> str:
+        import re
+
+        match = re.search(r'\b[A-Z][A-Z0-9]+-\d+\b', text or '', re.IGNORECASE)
+        return match.group(0).upper() if match else 'MANUAL-1'
     
     def _build_system_prompt_simple(self, agent: Agent) -> str:
         """构建简化的系统提示词"""

backend-fastapi/ai_platform/services/workflow_service.py

@@ -1594,6 +1594,7 @@ class AIWorkflowService:
                         node_type,
                         status='completed',
                         output=result.output,
+                        metadata=_node_result_metadata(result),
                         inputs=copy.deepcopy(node_inputs),
                     ))
                     yield {