feat: 新增需求理解并实现human in loop

app/processor/nodes/clarify_node.py

@@ -1,5 +1,7 @@
 """整理澄清问题，等待用户补充"""
 
+import json
+
 from langchain_core.messages import HumanMessage, SystemMessage
 
 from app.clients.llm import get_llm
@@ -16,23 +18,20 @@ class ClarifyNode(BaseNode):
         intent = state["intent"]
         print(intent)
         print("=================")
-        if intent == "unclear":
-            llm = get_llm(Clarification)
-            clarification = await llm.ainvoke(
-                [
-                    SystemMessage(content=CLARIFY_SYSTEM_PROMPT),
-                    HumanMessage(
-                        content=state["input_context"].model_dump_json(
-                            exclude_unset=True
-                        )
-                    ),
-                ]
-            )
-        else:
-            # 需求理解已经给出问题，直接复用
-            clarification = Clarification(
-                question=state["requirement"].clarification_question
-            )
+        payload = {
+            "intent": intent,
+            "input_context": state["input_context"].model_dump(mode="json"),
+        }
+        if intent != "unclear":
+            # 以需求节点的问题为依据补齐选项，不重新判断意图
+            payload["requirement"] = state["requirement"].model_dump(mode="json")
+        llm = get_llm(Clarification)
+        clarification = await llm.ainvoke(
+            [
+                SystemMessage(content=CLARIFY_SYSTEM_PROMPT),
+                HumanMessage(content=json.dumps(payload, ensure_ascii=False)),
+            ]
+        )
         return {**state, "clarification": clarification}
 
 
@@ -54,7 +53,9 @@ if __name__ == "__main__":
             }
         }
         try:
-            final_state = await query_app.ainvoke(state)
+            final_state = await query_app.ainvoke(
+                state, config={"configurable": {"thread_id": "clarify-test"}}
+            )
         finally:
             await close_decision_engine()
         print(
@@ -67,6 +68,7 @@ if __name__ == "__main__":
                 },
                 ensure_ascii=False,
                 indent=2,
+                default=str,
             )
         )
 

app/processor/nodes/input_node.py

@@ -11,6 +11,41 @@ class InputNode(BaseNode):
     name = "input_node"
 
     def process(self, state: QueryState) -> QueryState:
+        reply = state.get("clarification_reply")
+        if reply is not None:
+            data = state["input_context"].model_dump(mode="json")
+            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)
+            if reply.screen is not None:
+                data["screen"] = reply.screen.model_dump(mode="json")
+                # 新快照不沿用可能已经失效的选中节点
+                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")
+            context = InputContext.model_validate(data)
+            # 显式清空旧推导结果，LangGraph 的状态合并不会删除省略字段
+            return {
+                **state,
+                "input_context": context,
+                "clarification_reply": None,
+                "intent_decision": None,
+                "intent": None,
+                "requirement": None,
+                "clarification": None,
+                "status": "running",
+            }
         # 深拷贝隔离原始请求，后续修改上下文不会改变提交时的快照
         context = InputContext.model_validate(state["request"]).model_copy(deep=True)
         updated_state: QueryState = {**state, "input_context": context}

app/processor/nodes/intent_node.py

@@ -38,6 +38,7 @@ class IntentNode(BaseNode):
             )
         return {
             "prompt": context.prompt,
+            "clarification_history": context.clarification_history,
             "context": context.context.model_dump(mode="json", exclude_unset=True),
             "screen_summary": {
                 "canvas": {