feat(workflow_node): question classifier node optimization

api/app/core/workflow/executor.py

@@ -219,17 +219,13 @@ class WorkflowExecutor:
             # 创建节点实例（现在 start 和 end 也会被创建）
             node_instance = NodeFactory.create_node(node, self.workflow_config)
 
-            if node_type in [NodeType.IF_ELSE, NodeType.HTTP_REQUEST]:
-                expressions = node_instance.build_conditional_edge_expressions()
-
-                # Number of branches, usually matches the number of conditional expressions
-                branch_number = len(expressions)
+            if node_type in [NodeType.IF_ELSE, NodeType.HTTP_REQUEST, NodeType.QUESTION_CLASSIFIER]:
 
                 # Find all edges whose source is the current node
                 related_edge = [edge for edge in self.edges if edge.get("source") == node_id]
 
                 # Iterate over each branch
-                for idx in range(branch_number):
+                for idx in range(len(related_edge)):
                     # Generate a condition expression for each edge
                     # Used later to determine which branch to take based on the node's output
                     # Assumes node output `node.<node_id>.output` matches the edge's label

api/app/core/workflow/nodes/question_classifier/config.py

@@ -26,4 +26,3 @@ class QuestionClassifierNodeConfig(BaseNodeConfig):
         default="问题：{question}\n\n可选分类：{categories}\n\n补充指令：{supplement_prompt}\n\n请选择最合适的分类。",
         description="用户提示词模板"
     )
-    output_variable: str = Field(default="class_name", description="输出分类结果的变量名")

api/app/core/workflow/nodes/question_classifier/node.py

@@ -12,6 +12,9 @@ from app.services.model_service import ModelConfigService
 
 logger = logging.getLogger(__name__)
 
+DEFAULT_CASE_PREFIX = "CASE"
+DEFAULT_EMPTY_QUESTION_CASE = f"{DEFAULT_CASE_PREFIX}1"
+
 
 class QuestionClassifierNode(BaseNode):
     """问题分类器节点"""
@@ -19,6 +22,7 @@ class QuestionClassifierNode(BaseNode):
     def __init__(self, node_config: dict[str, Any], workflow_config: dict[str, Any]):
         super().__init__(node_config, workflow_config)
         self.typed_config = QuestionClassifierNodeConfig(**self.config)
+        self.category_to_case_map = self._build_category_case_map()
     
     def _get_llm_instance(self) -> RedBearLLM:
         """获取LLM实例"""
@@ -47,48 +51,73 @@ class QuestionClassifierNode(BaseNode):
             ),
             type=ModelType(model_type)
         )
+
+    def _build_category_case_map(self) -> dict[str, str]:
+        """
+        预构建 分类名称 -> CASE标识 的映射字典
+        示例：{"产品咨询": "CASE1", "售后问题": "CASE2"}
+        """
+        category_map = {}
+        categories = self.typed_config.categories or []
+        for idx, class_item in enumerate(categories, start=1):
+            category_name = class_item.class_name.strip()
+            case_tag = f"{DEFAULT_CASE_PREFIX}{idx}"
+            category_map[category_name] = case_tag
+        return category_map
     
-    async def execute(self, state: WorkflowState) -> dict[str, Any]:
+    async def execute(self, state: WorkflowState) -> str:
         """执行问题分类"""
         question = self.typed_config.input_variable
-
-        supplement_prompt = ""
-        if self.typed_config.user_supplement_prompt is not None:
-            supplement_prompt = self.typed_config.user_supplement_prompt
-        
-        category_names = [class_item.class_name for class_item in self.typed_config.categories]
+        supplement_prompt = self.typed_config.user_supplement_prompt or ""
+        categories = self.typed_config.categories or []
+        category_names = [class_item.class_name.strip() for class_item in categories]
+        category_count = len(category_names)
         
         if not question:
-            logger.warning(f"节点 {self.node_id} 未获取到输入问题")
-            return {self.typed_config.output_variable: category_names[0] if category_names else "unknown"}
-        
-        llm = self._get_llm_instance()
-        
-        # 渲染用户提示词模板，支持工作流变量
-        user_prompt = self._render_template(
-            self.typed_config.user_prompt.format(
-                question=question,
-                categories=", ".join(category_names),
-                supplement_prompt=supplement_prompt
-            ),
-            state
-        )
-        
-        messages = [
-            ("system", self.typed_config.system_prompt),
-            ("user", user_prompt),
-        ]
-        
-        response = await llm.ainvoke(messages)
-        result = response.content.strip()
-        
-        if result in category_names:
-            category = result
-        else:
-            logger.warning(f"LLM返回了未知类别: {result}")
-            category = category_names[0] if category_names else "unknown"
+            logger.warning(
+                f"节点 {self.node_id} 未获取到输入问题，使用默认分支"
+                f"（默认分支：{DEFAULT_EMPTY_QUESTION_CASE}，分类总数：{category_count}）"
+            )
+            # 若分类列表为空，返回默认unknown分支，否则返回CASE1
+            return DEFAULT_EMPTY_QUESTION_CASE if category_count > 0 else "unknown"
 
-        log_supplement = supplement_prompt if supplement_prompt else "无"
-        logger.info(f"节点 {self.node_id} 分类结果: {category}, 用户补充提示词：{log_supplement}")
-        
-        return {self.typed_config.output_variable: category}
+        try:
+            llm = self._get_llm_instance()
+
+            # 渲染用户提示词模板，支持工作流变量
+            user_prompt = self._render_template(
+                self.typed_config.user_prompt.format(
+                    question=question,
+                    categories=", ".join(category_names),
+                    supplement_prompt=supplement_prompt
+                ),
+                state
+            )
+
+            messages = [
+                ("system", self.typed_config.system_prompt),
+                ("user", user_prompt),
+            ]
+
+            response = await llm.ainvoke(messages)
+            result = response.content.strip()
+
+            if result in category_names:
+                category = result
+            else:
+                logger.warning(f"LLM返回了未知类别: {result}")
+                category = category_names[0] if category_names else "unknown"
+
+            log_supplement = supplement_prompt if supplement_prompt else "无"
+            logger.info(f"节点 {self.node_id} 分类结果: {category}, 用户补充提示词：{log_supplement}")
+
+            return f"CASE{category_names.index(category) + 1}"
+        except Exception as e:
+            logger.error(
+                f"节点 {self.node_id} 分类执行异常：{str(e)}",
+                exc_info=True  # 打印堆栈信息，便于调试
+            )
+            # 异常时返回默认分支，保证工作流容错性
+            if category_count > 0:
+                return DEFAULT_EMPTY_QUESTION_CASE
+            return "unknown"