Merge #76 into develop from feature/20251219_xjn

feat(workflow-node): question_classfier node development

* feature/20251219_xjn: (1 commits)
  feat(workflow-node): question_classfier node development

Signed-off-by: 谢俊男 <accounts_6853d0ea6f8174722fb0c8f1@mail.teambition.com>
Reviewed-by: zhuwenhui5566@163.com <zhuwenhui5566@163.com>
Merged-by: zhuwenhui5566@163.com <zhuwenhui5566@163.com>

CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/76

api/app/core/workflow/nodes/configs.py

@@ -20,6 +20,7 @@ from app.core.workflow.nodes.start.config import StartNodeConfig
 from app.core.workflow.nodes.transform.config import TransformNodeConfig
 from app.core.workflow.nodes.variable_aggregator.config import VariableAggregatorNodeConfig
 from app.core.workflow.nodes.parameter_extractor.config import ParameterExtractorNodeConfig
+from app.core.workflow.nodes.question_classifier.config import QuestionClassifierNodeConfig
 
 __all__ = [
     # 基础类
@@ -40,4 +41,5 @@ __all__ = [
     "JinjaRenderNodeConfig",
     "VariableAggregatorNodeConfig",
     "ParameterExtractorNodeConfig",
+    "QuestionClassifierNodeConfig"
 ]

api/app/core/workflow/nodes/node_factory.py

@@ -21,6 +21,7 @@ from app.core.workflow.nodes.parameter_extractor import ParameterExtractorNode
 from app.core.workflow.nodes.start import StartNode
 from app.core.workflow.nodes.transform import TransformNode
 from app.core.workflow.nodes.variable_aggregator import VariableAggregatorNode
+from app.core.workflow.nodes.question_classifier import QuestionClassifierNode
 
 logger = logging.getLogger(__name__)
 
@@ -37,7 +38,8 @@ WorkflowNode = Union[
     KnowledgeRetrievalNode,
     JinjaRenderNode,
     VariableAggregatorNode,
-    ParameterExtractorNode
+    ParameterExtractorNode,
+    QuestionClassifierNode
 ]
 
 
@@ -61,6 +63,7 @@ class NodeFactory:
         NodeType.JINJARENDER: JinjaRenderNode,
         NodeType.VAR_AGGREGATOR: VariableAggregatorNode,
         NodeType.PARAMETER_EXTRACTOR: ParameterExtractorNode,
+        NodeType.QUESTION_CLASSIFIER: QuestionClassifierNode,
     }
 
     @classmethod

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

@@ -0,0 +1,6 @@
+from app.core.workflow.nodes.question_classifier.config import QuestionClassifierNodeConfig
+from app.core.workflow.nodes.question_classifier.node import QuestionClassifierNode
+
+__all__ = ["QuestionClassifierNode", "QuestionClassifierNodeConfig"]
+
+

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

@@ -0,0 +1,29 @@
+import uuid
+from typing import Optional
+
+from pydantic import Field, BaseModel
+
+from app.core.workflow.nodes.base_config import BaseNodeConfig
+
+class ClassifierConfig(BaseModel):
+    """分类器节点配置"""
+
+    class_name: str = Field(..., description="分类类别名称")
+
+
+class QuestionClassifierNodeConfig(BaseNodeConfig):
+    """问题分类器节点配置"""
+    
+    model_id: uuid.UUID = Field(..., description="LLM模型ID")
+    input_variable: str = Field(default="{{sys.message}}", description="输入变量选择器(用户问题)")
+    user_supplement_prompt: Optional[str] = Field(default=None, description="用户补充提示词，额外分类指令")
+    categories: list[ClassifierConfig] = Field(..., description="分类类别列表")
+    system_prompt: str = Field(
+        default="你是一个问题分类器，请根据用户问题选择最合适的分类。只返回分类名称，不要其他内容。",
+        description="系统提示词"
+    )
+    user_prompt: str = Field(
+        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

@@ -0,0 +1,94 @@
+import logging
+from typing import Any
+
+from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
+from app.core.workflow.nodes.question_classifier.config import QuestionClassifierNodeConfig
+from app.core.models import RedBearLLM, RedBearModelConfig
+from app.core.exceptions import BusinessException
+from app.core.error_codes import BizCode
+from app.db import get_db_read
+from app.models import ModelType
+from app.services.model_service import ModelConfigService
+
+logger = logging.getLogger(__name__)
+
+
+class QuestionClassifierNode(BaseNode):
+    """问题分类器节点"""
+    
+    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)
+    
+    def _get_llm_instance(self) -> RedBearLLM:
+        """获取LLM实例"""
+        with get_db_read() as db:
+            config = ModelConfigService.get_model_by_id(db=db, model_id=self.typed_config.model_id)
+            
+            if not config:
+                raise BusinessException("配置的模型不存在", BizCode.NOT_FOUND)
+            
+            if not config.api_keys or len(config.api_keys) == 0:
+                raise BusinessException("模型配置缺少 API Key", BizCode.INVALID_PARAMETER)
+            
+            api_config = config.api_keys[0]
+            model_name = api_config.model_name
+            provider = api_config.provider
+            api_key = api_config.api_key
+            base_url = api_config.api_base
+            model_type = config.type
+        
+        return RedBearLLM(
+            RedBearModelConfig(
+                model_name=model_name,
+                provider=provider,
+                api_key=api_key,
+                base_url=base_url,
+            ),
+            type=ModelType(model_type)
+        )
+    
+    async def execute(self, state: WorkflowState) -> dict[str, Any]:
+        """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]
+        
+        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"
+
+        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}