feat：优化流式输出，增加临时多轮对话记录
This commit is contained in:
+3
-1
@@ -12,7 +12,9 @@ router = APIRouter(prefix="/agent", tags=["Agent"])
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@router.post("/run", response_class=AgentEventResponse, status_code=200)
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async def stream_agent(body: DesignRequest, request: Request):
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service = request.app.state.agent_service
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return AgentEventResponse(service, service.stream_run(body), request)
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# 在发送流响应头之前完成会话校验并占用任务
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execution = await service.prepare_run(body)
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return AgentEventResponse(service, execution, request)
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@router.post("/resume", response_class=AgentEventResponse, status_code=200)
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@@ -50,7 +50,20 @@ class Settings:
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default_factory=lambda: int(os.getenv("MAX_ACTION_RETRIES", "2"))
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)
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# 没有任何对话的空会话保留时长（秒），超时后视为不存在
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conversation_empty_ttl: int = field(
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default_factory=lambda: int(os.getenv("CONVERSATION_EMPTY_TTL", "7200"))
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)
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# 每次请求带入模型的最近对话轮数
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conversation_history_turns: int = field(
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default_factory=lambda: int(os.getenv("CONVERSATION_HISTORY_TURNS", "6"))
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)
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def __post_init__(self):
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if self.conversation_empty_ttl <= 0:
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raise ValueError("CONVERSATION_EMPTY_TTL 必须是正整数")
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if self.conversation_history_turns < 0:
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raise ValueError("CONVERSATION_HISTORY_TURNS 必须是非负整数")
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if type(self.max_action_retries) is not int or self.max_action_retries < 0:
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raise ValueError("MAX_ACTION_RETRIES 必须是非负整数")
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if not 0 <= self.intent_min_confidence <= 1:
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+8
-1
@@ -7,6 +7,7 @@ from fastapi import FastAPI
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from loguru import logger
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from app.api.agent import router
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from app.api.conversations import router as conversation_router
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from app.core.exceptions import register_exception_handlers
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from app.core.logging import setup_logging
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@@ -19,7 +20,12 @@ async def lifespan(application: FastAPI):
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from app.processor.graph import build_graph
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from app.services.agent import AgentService
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application.state.agent_service = AgentService(build_graph())
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from app.services.conversation import InMemoryConversationStore
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# TODO 接入 MongoDB 后替换为持久化实现，并同步替换图的 checkpointer
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store = InMemoryConversationStore()
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application.state.conversation_store = store
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application.state.agent_service = AgentService(build_graph(), store)
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try:
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yield
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finally:
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@@ -38,6 +44,7 @@ def create_app() -> FastAPI:
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# 统一处理请求校验、HTTP 错误和未捕获异常
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register_exception_handlers(application)
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application.include_router(router)
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application.include_router(conversation_router)
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return application
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@@ -50,6 +50,7 @@ class IntentNode(BaseNode):
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# 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
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return {
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"prompt": context.prompt,
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"history": context.history,
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"clarification_history": context.clarification_history,
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"context": context.context.model_dump(mode="json", exclude_unset=True),
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"screen_summary": {
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@@ -2,6 +2,7 @@
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from langchain_core.messages import HumanMessage, SystemMessage
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from langchain_core.output_parsers import StrOutputParser
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from langgraph.config import get_stream_writer
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from app.clients.llm import get_llm
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from app.processor.base import BaseNode
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@@ -18,8 +19,16 @@ class QANode(BaseNode):
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# 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
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llm_client = get_llm()
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# 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
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llm_res = await llm_client.ainvoke(
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try:
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# 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
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writer = get_stream_writer()
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except RuntimeError:
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writer = None
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parser = StrOutputParser()
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parts: list[str] = []
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# 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
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async for chunk in llm_client.astream(
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[
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# 系统消息提供稳定的问答规则和回答边界
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SystemMessage(content=QA_SYSTEM_PROMPT),
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@@ -28,10 +37,23 @@ class QANode(BaseNode):
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content=state["input_context"].model_dump_json(exclude_unset=True)
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),
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]
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):
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# 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
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delta = parser.invoke(chunk)
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if not delta:
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continue
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parts.append(delta)
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if writer is not None:
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writer(
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{
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"type": "answer_delta",
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"message_id": state.get("message_id"),
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"delta": delta,
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}
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)
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# 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
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answer = StrOutputParser().invoke(llm_res).strip()
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# 拼接完整回答，并去除首尾的空白
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answer = "".join(parts).strip()
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# 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
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if not answer:
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raise ValueError("问答模型未返回文本回答")
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@@ -9,7 +9,7 @@ def build_intent_question() -> ChoiceDecision:
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instructions=(
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"Classify the user's primary intent. "
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"Classify the latest user answer in `clarification_history`, or `prompt` when there is no history. "
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"Use earlier turns and the selected option to resolve references; the latest answer overrides earlier conflicting intent. "
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"Use earlier turns, `history` (previous turns of this conversation) and the selected option to resolve references; the latest answer overrides earlier conflicting intent. "
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"Once the requested action or response is clear, earlier ambiguity does not require another confirmation. "
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"Choose modify_screen only when the user explicitly requests an actual edit. "
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"Choose qa for clear requests for a textual answer or general conversation, including information, explanation, diagnosis, advice, and assistant identity or capabilities. "
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+2
-1
@@ -5,7 +5,8 @@ QA_SYSTEM_PROMPT = """## 任务
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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
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## 回答依据
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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
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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
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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
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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
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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
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@@ -49,10 +49,14 @@ REQUIREMENT_INPUT_TEMPLATE = """历史会话：
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def build_requirement_input(
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context: InputContext, intent: Intent, *, history_text: str = "未提供"
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context: InputContext, intent: Intent, *, history_text: str | None = None
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) -> str:
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"""整理本次模型输入，历史会话由调用方加载后传入"""
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"""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"""
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data = context.model_dump(mode="json", exclude_unset=True)
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# 会话历史
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history = data.pop("history", [])
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if history_text is None:
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history_text = json.dumps(history, ensure_ascii=False) if history else "未提供"
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content = REQUIREMENT_INPUT_TEMPLATE.format(
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history_text=history_text,
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clarification_text=json.dumps(
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@@ -10,3 +10,5 @@ class InputContext(DesignRequest):
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"""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"""
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clarification_history: list[JsonObject] = Field(default_factory=list)
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# 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
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history: list[JsonObject] = Field(default_factory=list)
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+90
-12
@@ -1,29 +1,61 @@
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"""异步执行与恢复大屏任务，当前使用单进程内存检查点"""
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from contextlib import aclosing
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from datetime import datetime, timezone
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from uuid import uuid4
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from langgraph.types import Command
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from loguru import logger
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from app.config import settings
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from app.core.exceptions import BizException
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from app.observability.tracing import astream_screen
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from app.schemas.agent import AgentResult, ResumeRequest
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from app.schemas.conversation import Turn
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from app.schemas.request import DesignRequest
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from app.services.conversation import ConversationStore
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SUMMARY_MAX_CHARS = 500
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def _clip(text: str) -> str:
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return text if len(text) <= SUMMARY_MAX_CHARS else text[:SUMMARY_MAX_CHARS] + "…"
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class AgentService:
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def __init__(self, graph):
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def __init__(self, graph, store: ConversationStore):
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self.graph = graph
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self.store = store
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# 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
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self._active: set[str] = set()
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self._conversation_of: dict[str, str] = {}
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async def prepare_run(self, request: DesignRequest):
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# 会话 ID 必须由后端签发，不再为缺失的 ID 兜底生成
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conversation_id = request.context.conversation_id
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if conversation_id is None:
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raise BizException(422, "请先创建会话并传入 conversation_id")
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if not await self.store.exists(conversation_id):
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raise BizException(404, "会话不存在或已过期")
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def _prepare_run(self, request: DesignRequest):
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# 新请求始终独立建任务，不用 conversation_id 充当检查点 ID
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thread_id = str(uuid4())
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# 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
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conversation_id = request.context.conversation_id or str(uuid4())
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self._claim(thread_id, conversation_id)
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try:
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turns = await self.store.load_turns(
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conversation_id, settings.conversation_history_turns
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)
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except BaseException:
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self.release(thread_id)
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raise
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payload = request.model_dump(mode="json")
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payload["context"]["conversation_id"] = conversation_id
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# 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
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payload["history"] = [
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{"user": turn.prompt, "assistant": turn.summary, "outcome": turn.outcome}
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for turn in turns
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]
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return (
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thread_id,
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@@ -36,11 +68,6 @@ class AgentService:
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conversation_id,
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)
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def stream_run(self, request: DesignRequest):
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execution = self._prepare_run(request)
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self._claim(execution[0])
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return execution
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async def prepare_resume(self, request: ResumeRequest):
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# 在发送流响应头之前完成校验并占用任务
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thread_id = str(request.thread_id)
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@@ -65,6 +92,7 @@ class AgentService:
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raise BizException(422, "请选择当前问题的有效选项")
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conversation_id = snapshot.values["conversation_id"]
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self._claim_conversation(thread_id, conversation_id)
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# 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
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if reply.context is not None:
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if reply.context.conversation_id not in (None, conversation_id):
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@@ -92,11 +120,56 @@ class AgentService:
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def release(self, thread_id):
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self._active.discard(thread_id)
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self._conversation_of.pop(thread_id, None)
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def _claim(self, thread_id: str) -> None:
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def _claim(self, thread_id: str, conversation_id: str | None = None) -> None:
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if thread_id in self._active:
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raise BizException(409, "任务正在执行，请勿重复提交")
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self._active.add(thread_id)
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if conversation_id is not None:
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try:
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self._claim_conversation(thread_id, conversation_id)
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except BaseException:
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self.release(thread_id)
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raise
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def _claim_conversation(self, thread_id: str, conversation_id: str) -> None:
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if conversation_id in self._conversation_of.values():
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raise BizException(409, "该会话有任务正在执行，请稍后再试")
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self._conversation_of[thread_id] = conversation_id
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@staticmethod
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def _summarize(state, result: AgentResult) -> str:
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"""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"""
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if result.status == "waiting_for_input":
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question = result.clarification.question if result.clarification else ""
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return _clip(f"向用户提问：{question}")
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if result.status == "cancelled":
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return "用户取消了本次补充"
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if result.status == "failed":
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return _clip(f"处理失败：{result.failure_reason or '未知原因'}")
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if result.answer:
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return _clip(result.answer)
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requirement = state.get("requirement")
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goal = requirement.goal if requirement is not None else "修改大屏"
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return _clip(f"{goal}（已生成 {len(result.actions)} 个画布动作）")
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async def _save_turn(self, state, result: AgentResult) -> None:
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# 历史写入失败不影响本次结果交付，只记录日志
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try:
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await self.store.save_turn(
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Turn(
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conversation_id=result.conversation_id,
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thread_id=result.thread_id,
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message_id=result.message_id,
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prompt=state["request"]["prompt"],
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outcome=result.status,
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summary=self._summarize(state, result),
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created_at=datetime.now(timezone.utc),
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)
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)
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except Exception:
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logger.exception("保存对话轮次失败")
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@staticmethod
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def _result(state, thread_id):
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@@ -129,6 +202,11 @@ class AgentService:
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state = data
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elif data.get("type") == "node_progress" and data.get("label"):
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yield "progress", data
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elif data.get("type") == "answer_delta":
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# 问答文本逐段推送，完整回答仍在 final 事件中返回
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yield "answer_delta", data
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if state is None:
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raise RuntimeError("图未返回状态")
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yield "final", self._result(state, thread_id).model_dump(mode="json")
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result = self._result(state, thread_id)
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await self._save_turn(state, result)
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yield "final", result.model_dump(mode="json")
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Block a user