feat：优化流式输出，增加临时多轮对话记录

app/api/agent.py

@@ -12,7 +12,9 @@ router = APIRouter(prefix="/agent", tags=["Agent"])
 @router.post("/run", response_class=AgentEventResponse, status_code=200)
 async def stream_agent(body: DesignRequest, request: Request):
     service = request.app.state.agent_service
-    return AgentEventResponse(service, service.stream_run(body), request)
+    # 在发送流响应头之前完成会话校验并占用任务
+    execution = await service.prepare_run(body)
+    return AgentEventResponse(service, execution, request)
 
 
 @router.post("/resume", response_class=AgentEventResponse, status_code=200)

app/config.py

@@ -50,7 +50,20 @@ class Settings:
         default_factory=lambda: int(os.getenv("MAX_ACTION_RETRIES", "2"))
     )
 
+    # 没有任何对话的空会话保留时长（秒），超时后视为不存在
+    conversation_empty_ttl: int = field(
+        default_factory=lambda: int(os.getenv("CONVERSATION_EMPTY_TTL", "7200"))
+    )
+    # 每次请求带入模型的最近对话轮数
+    conversation_history_turns: int = field(
+        default_factory=lambda: int(os.getenv("CONVERSATION_HISTORY_TURNS", "6"))
+    )
+
     def __post_init__(self):
+        if self.conversation_empty_ttl <= 0:
+            raise ValueError("CONVERSATION_EMPTY_TTL 必须是正整数")
+        if self.conversation_history_turns < 0:
+            raise ValueError("CONVERSATION_HISTORY_TURNS 必须是非负整数")
         if type(self.max_action_retries) is not int or self.max_action_retries < 0:
             raise ValueError("MAX_ACTION_RETRIES 必须是非负整数")
         if not 0 <= self.intent_min_confidence <= 1:

app/main.py

@@ -7,6 +7,7 @@ from fastapi import FastAPI
 from loguru import logger
 
 from app.api.agent import router
+from app.api.conversations import router as conversation_router
 from app.core.exceptions import register_exception_handlers
 from app.core.logging import setup_logging
 
@@ -19,7 +20,12 @@ async def lifespan(application: FastAPI):
     from app.processor.graph import build_graph
     from app.services.agent import AgentService
 
-    application.state.agent_service = AgentService(build_graph())
+    from app.services.conversation import InMemoryConversationStore
+
+    # TODO 接入 MongoDB 后替换为持久化实现，并同步替换图的 checkpointer
+    store = InMemoryConversationStore()
+    application.state.conversation_store = store
+    application.state.agent_service = AgentService(build_graph(), store)
     try:
         yield
     finally:
@@ -38,6 +44,7 @@ def create_app() -> FastAPI:
     # 统一处理请求校验、HTTP 错误和未捕获异常
     register_exception_handlers(application)
     application.include_router(router)
+    application.include_router(conversation_router)
     return application
 
 

app/processor/nodes/intent_node.py

@@ -50,6 +50,7 @@ class IntentNode(BaseNode):
         # 汇总用户需求、澄清历史、交互上下文和大屏摘要，作为意图判断的输入
         return {
             "prompt": context.prompt,
+            "history": context.history,
             "clarification_history": context.clarification_history,
             "context": context.context.model_dump(mode="json", exclude_unset=True),
             "screen_summary": {

app/processor/nodes/qa_node.py

@@ -2,6 +2,7 @@
 
 from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_core.output_parsers import StrOutputParser
+from langgraph.config import get_stream_writer
 
 from app.clients.llm import get_llm
 from app.processor.base import BaseNode
@@ -18,8 +19,16 @@ class QANode(BaseNode):
 
         # 获取普通对话模型，问答只需文本回答，不绑定结构化输出协议
         llm_client = get_llm()
-        # 异步调用模型，结合用户问题、当前大屏和澄清记录生成回答
+        try:
-        llm_res = await llm_client.ainvoke(
+            # 图执行上下文中通过 custom 流逐段推送回答，独立调用节点时没有写入器
+            writer = get_stream_writer()
+        except RuntimeError:
+            writer = None
+
+        parser = StrOutputParser()
+        parts: list[str] = []
+        # 异步流式调用模型，结合用户问题、当前大屏和澄清记录生成回答
+        async for chunk in llm_client.astream(
             [
                 # 系统消息提供稳定的问答规则和回答边界
                 SystemMessage(content=QA_SYSTEM_PROMPT),
@@ -28,10 +37,23 @@ class QANode(BaseNode):
                     content=state["input_context"].model_dump_json(exclude_unset=True)
                 ),
             ]
-        )
+        ):
+            # 从每个片段提取文本，兼容文本内容块，工具调用等无文本片段会得到空串
+            delta = parser.invoke(chunk)
+            if not delta:
+                continue
+            parts.append(delta)
+            if writer is not None:
+                writer(
+                    {
+                        "type": "answer_delta",
+                        "message_id": state.get("message_id"),
+                        "delta": delta,
+                    }
+                )
 
-        # 从模型响应中提取文本，兼容文本内容块，并去除回答首尾的空白
+        # 拼接完整回答，并去除首尾的空白
-        answer = StrOutputParser().invoke(llm_res).strip()
+        answer = "".join(parts).strip()
         # 如果没有有效文本，抛出异常，避免将空回答标记为处理完成
         if not answer:
             raise ValueError("问答模型未返回文本回答")

app/prompt/intent.py

@@ -9,7 +9,7 @@ def build_intent_question() -> ChoiceDecision:
         instructions=(
             "Classify the user's primary intent. "
             "Classify the latest user answer in `clarification_history`, or `prompt` when there is no history. "
-            "Use earlier turns and the selected option to resolve references; the latest answer overrides earlier conflicting intent. "
+            "Use earlier turns, `history` (previous turns of this conversation) and the selected option to resolve references; the latest answer overrides earlier conflicting intent. "
             "Once the requested action or response is clear, earlier ambiguity does not require another confirmation. "
             "Choose modify_screen only when the user explicitly requests an actual edit. "
             "Choose qa for clear requests for a textual answer or general conversation, including information, explanation, diagnosis, advice, and assistant identity or capabilities. "

app/prompt/qa.py

@@ -5,7 +5,8 @@ QA_SYSTEM_PROMPT = """## 任务
 也可回答助手身份、能力等一般交流请求；介绍自己时以大屏助手的职责和已知能力为依据，不编造模型身份或未提供的能力
 
 ## 回答依据
-结合当前问题、大屏快照和 clarification_history，以用户后续明确补充或纠正为准
+结合当前问题、大屏快照、history（此前各轮的用户输入与助手摘要）和 clarification_history，以用户后续明确补充或纠正为准
+理解“刚才那个”“再大一点”等指代时参考 history，但当前大屏快照才是最新事实
 仅在与请求相关时使用大屏快照；一般交流无需强行关联大屏或要求用户补充大屏信息
 区分快照事实与待验证的推测，证据不足时说明缺少的信息，不编造故障原因
 

app/prompt/requirement.py

@@ -49,10 +49,14 @@ REQUIREMENT_INPUT_TEMPLATE = """历史会话：
 
 
 def build_requirement_input(
-    context: InputContext, intent: Intent, *, history_text: str = "未提供"
+    context: InputContext, intent: Intent, *, history_text: str | None = None
 ) -> str:
-    """整理本次模型输入，历史会话由调用方加载后传入"""
+    """整理本次模型输入，历史会话默认取输入上下文中由服务端写入的记录"""
     data = context.model_dump(mode="json", exclude_unset=True)
+    # 会话历史
+    history = data.pop("history", [])
+    if history_text is None:
+        history_text = json.dumps(history, ensure_ascii=False) if history else "未提供"
     content = REQUIREMENT_INPUT_TEMPLATE.format(
         history_text=history_text,
         clarification_text=json.dumps(

app/schemas/input_context.py

@@ -10,3 +10,5 @@ class InputContext(DesignRequest):
     """当前复用请求协议，后续可添加解析结果而不改变前端传参"""
 
     clarification_history: list[JsonObject] = Field(default_factory=list)
+    # 同一会话此前各轮的用户输入与助手摘要，由服务端按 conversation_id 写入，按时间从早到晚排列
+    history: list[JsonObject] = Field(default_factory=list)

app/services/agent.py

@@ -1,29 +1,61 @@
 """异步执行与恢复大屏任务，当前使用单进程内存检查点"""
 
 from contextlib import aclosing
+from datetime import datetime, timezone
 from uuid import uuid4
 
 from langgraph.types import Command
 from loguru import logger
 
+from app.config import settings
 from app.core.exceptions import BizException
 from app.observability.tracing import astream_screen
 from app.schemas.agent import AgentResult, ResumeRequest
+from app.schemas.conversation import Turn
 from app.schemas.request import DesignRequest
+from app.services.conversation import ConversationStore
+
+
+SUMMARY_MAX_CHARS = 500
+
+
+def _clip(text: str) -> str:
+    return text if len(text) <= SUMMARY_MAX_CHARS else text[:SUMMARY_MAX_CHARS] + "…"
 
 
 class AgentService:
-    def __init__(self, graph):
+    def __init__(self, graph, store: ConversationStore):
         self.graph = graph
+        self.store = store
+        # 同一时刻，一个任务和一个会话都只允许一个执行，避免历史顺序错乱
         self._active: set[str] = set()
+        self._conversation_of: dict[str, str] = {}
+
+    async def prepare_run(self, request: DesignRequest):
+        # 会话 ID 必须由后端签发，不再为缺失的 ID 兜底生成
+        conversation_id = request.context.conversation_id
+        if conversation_id is None:
+            raise BizException(422, "请先创建会话并传入 conversation_id")
+        if not await self.store.exists(conversation_id):
+            raise BizException(404, "会话不存在或已过期")
 
-    def _prepare_run(self, request: DesignRequest):
         # 新请求始终独立建任务，不用 conversation_id 充当检查点 ID
         thread_id = str(uuid4())
-        # 暂无会话创建接口，未传会话 ID 时先分配标识，不创建数据库记录
+        self._claim(thread_id, conversation_id)
-        conversation_id = request.context.conversation_id or str(uuid4())
+        try:
+            turns = await self.store.load_turns(
+                conversation_id, settings.conversation_history_turns
+            )
+        except BaseException:
+            self.release(thread_id)
+            raise
+
         payload = request.model_dump(mode="json")
-        payload["context"]["conversation_id"] = conversation_id
+        # 历史只信任服务端记录，覆盖前端可能携带的同名扩展字段
+        payload["history"] = [
+            {"user": turn.prompt, "assistant": turn.summary, "outcome": turn.outcome}
+            for turn in turns
+        ]
 
         return (
             thread_id,
@@ -36,11 +68,6 @@ class AgentService:
             conversation_id,
         )
 
-    def stream_run(self, request: DesignRequest):
-        execution = self._prepare_run(request)
-        self._claim(execution[0])
-        return execution
-
     async def prepare_resume(self, request: ResumeRequest):
         # 在发送流响应头之前完成校验并占用任务
         thread_id = str(request.thread_id)
@@ -65,6 +92,7 @@ class AgentService:
                 raise BizException(422, "请选择当前问题的有效选项")
 
             conversation_id = snapshot.values["conversation_id"]
+            self._claim_conversation(thread_id, conversation_id)
             # 恢复同一任务不能切换会话，补充编辑上下文时也保留原会话标识
             if reply.context is not None:
                 if reply.context.conversation_id not in (None, conversation_id):
@@ -92,11 +120,56 @@ class AgentService:
 
     def release(self, thread_id):
         self._active.discard(thread_id)
+        self._conversation_of.pop(thread_id, None)
 
-    def _claim(self, thread_id: str) -> None:
+    def _claim(self, thread_id: str, conversation_id: str | None = None) -> None:
         if thread_id in self._active:
             raise BizException(409, "任务正在执行，请勿重复提交")
         self._active.add(thread_id)
+        if conversation_id is not None:
+            try:
+                self._claim_conversation(thread_id, conversation_id)
+            except BaseException:
+                self.release(thread_id)
+                raise
+
+    def _claim_conversation(self, thread_id: str, conversation_id: str) -> None:
+        if conversation_id in self._conversation_of.values():
+            raise BizException(409, "该会话有任务正在执行，请稍后再试")
+        self._conversation_of[thread_id] = conversation_id
+
+    @staticmethod
+    def _summarize(state, result: AgentResult) -> str:
+        """用一句话描述本轮结果，只陈述后端生成了什么，不代表前端已执行"""
+        if result.status == "waiting_for_input":
+            question = result.clarification.question if result.clarification else ""
+            return _clip(f"向用户提问：{question}")
+        if result.status == "cancelled":
+            return "用户取消了本次补充"
+        if result.status == "failed":
+            return _clip(f"处理失败：{result.failure_reason or '未知原因'}")
+        if result.answer:
+            return _clip(result.answer)
+        requirement = state.get("requirement")
+        goal = requirement.goal if requirement is not None else "修改大屏"
+        return _clip(f"{goal}（已生成 {len(result.actions)} 个画布动作）")
+
+    async def _save_turn(self, state, result: AgentResult) -> None:
+        # 历史写入失败不影响本次结果交付，只记录日志
+        try:
+            await self.store.save_turn(
+                Turn(
+                    conversation_id=result.conversation_id,
+                    thread_id=result.thread_id,
+                    message_id=result.message_id,
+                    prompt=state["request"]["prompt"],
+                    outcome=result.status,
+                    summary=self._summarize(state, result),
+                    created_at=datetime.now(timezone.utc),
+                )
+            )
+        except Exception:
+            logger.exception("保存对话轮次失败")
 
     @staticmethod
     def _result(state, thread_id):
@@ -129,6 +202,11 @@ class AgentService:
                         state = data
                     elif data.get("type") == "node_progress" and data.get("label"):
                         yield "progress", data
+                    elif data.get("type") == "answer_delta":
+                        # 问答文本逐段推送，完整回答仍在 final 事件中返回
+                        yield "answer_delta", data
         if state is None:
             raise RuntimeError("图未返回状态")
-        yield "final", self._result(state, thread_id).model_dump(mode="json")
+        result = self._result(state, thread_id)
+        await self._save_turn(state, result)
+        yield "final", result.model_dump(mode="json")