"""输入解析与校验;澄清恢复时把用户的回答合并进上下文""" from app.processor.base import BaseNode from app.processor.state import QueryState from app.schemas.input_context import InputContext class InputNode(BaseNode): """纯输入节点,不依赖模型配置;校验失败保留 ValidationError""" name = "input_node" def process(self, state: QueryState) -> QueryState: updated_state: QueryState = state.copy() reply = state.get("clarification_reply") if reply is None: # 首次请求:校验原始输入,并深拷贝隔离提交时的快照 updated_state["input_context"] = InputContext.model_validate( state["request"] ).model_copy(deep=True) updated_state["status"] = "running" return updated_state data = state["input_context"].model_dump(mode="json") # 记录本轮澄清问题和用户回答;选了选项时保存完整选项 turn = {"question": state["clarification"].question, "answer": reply.answer} if reply.option_id is not None: option = next( option for option in state["clarification"].options if option.id == reply.option_id ) turn["selected_option"] = option.model_dump(mode="json") data["clarification_history"].append(turn) # 回复携带最新大屏时替换旧快照;没有同时提供交互上下文时,清空可能已失效的选中节点和版本号 if reply.screen is not None: data["screen"] = reply.screen.model_dump(mode="json") if reply.context is None: data["context"]["selected_node_ids"] = [] data["context"]["screen_revision"] = None if reply.context is not None: data["context"] = reply.context.model_dump(mode="json") updated_state["input_context"] = InputContext.model_validate(data) # LangGraph 的状态合并不会删除省略字段,需要显式清空上一轮的结果,再重新判断意图 updated_state["clarification_reply"] = None updated_state["intent_decision"] = None updated_state["intent"] = None updated_state["actions"] = None updated_state["clarification"] = None updated_state["answer"] = None updated_state["status"] = "running" return updated_state