Files
baozaotumao df48c36422 refactor: 规则中性化——剥离 PPT 业务,统一为订单示范域
把规则从原 ppt-gen 项目泛化为通用脚手架,覆盖 19 个文件:
- ddd/architecture/design-discipline/error-codes/communication-* 等:
  领域术语、错误码、消息示例、扩展点、状态流统一为「订单」示范域
- agent-dag/agent.md/agent-concurrency/agent-llm-*:DAG 节点、配置、并发、
  LLM 适配从「对话→预览→生成→截图→合成」改为「intake→process→validate→finalize」
- backend-db:Session 实体/状态机/ORM/仓储/checkpoint 对齐新流水线
- 移除幻灯片专属依赖与产物:agent 去 playwright/python-pptx,
  Dockerfile 去 Chromium 系统库,.gitignore 去 *.pptx
- 保留合法通用项:ANSI(PTY 处理)、Playwright(E2E 测试工具)、Gemini CLI(真实 provider)

验证:gemini-cli/openai-api 两变体生成退出 0,生成项目零 PPT 残留,
backend/agent 骨架均可 import 运行。
2026-06-01 23:15:05 -07:00

7.1 KiB
Raw Permalink Blame History

paths
paths
agent/**

Agent DAG 编排与异常体系

SessionState 聚合根、DAG 节点表、runner 协调器(含 checkpoint 恢复与写入点)以及异常体系与传播规则。

下文以一条「会话→LLM 处理→结果」的通用流水线作示范,仅占位;节点与状态按你的业务替换,DAG 结构、checkpoint 与异常规则不变。

DAG 编排(dag/

SessionStatedomain/state.py,聚合根状态)

属领域层:是会话聚合根的状态载体,封装状态机不变量(如合法的 status 迁移),纯逻辑零 IO。

@dataclass
class SessionState:
    session_id: str
    work_dir: Path
    input_payload: dict | None = None
    result_path: Path | None = None
    status: Literal[
        "idle", "intake", "processing", "validating",
        "finalizing", "done", "revising", "error"
    ] = "idle"
    error_message: str | None = None

DAG 节点(dag/nodes.py

节点签名统一:

async def node_xxx(state: SessionState, send: Callable, recv_queue: asyncio.Queue) -> SessionState
节点 触发条件 行为
session_start 收到 start_session 创建 work_dir,启动 LLM 会话(PTY 或 API),就绪检查
intake 会话就绪后 收集/校验输入;用户 user_input → 转交 LLM
process 输入就绪 调 LLM 产出结果,流式推 log 进度
validate process 完成 业务规则校验产出,不合规则回错误或重试
finalize validate 通过 落地最终结果文件,推 result_ready
revise_loop done 状态下收到 user_input 转交 LLM → 重进 process

DAG 协调器(dag/runner.py

runner.py 有两个职责:恢复入口(连接建立时检查 checkpoint)和正常流程(串联所有节点)。

async def run_session(state: SessionState, send, recv_queue: asyncio.Queue,
                      checkpoint: dict | None = None):
    try:
        # ── 断点恢复入口 ──────────────────────────────────────────────
        if checkpoint:
            resume_status = checkpoint.get("status")

            if resume_status == "done":
                # 完全恢复:直接推送已有结果,无需任何 LLM 调用
                state.result_path = Path(checkpoint["result_path"])
                await send({"type": "result_ready", "session_id": state.session_id})
                await send({"type": "done"})
                # 进入 revise 循环等待用户继续
                await _revise_loop(state, send, recv_queue)
                return

            if resume_status in ("validating", "finalizing"):
                # 中间产物已在磁盘,跳过 LLM,直接从校验节点恢复
                state.result_path = Path(checkpoint["result_path"])
                state.status = "validating"
                logger.info("Resuming from checkpoint | status={}", resume_status)
                state = await validate(state, send)         # ← checkpoint 写入点 A
                state = await finalize(state, send)          # ← checkpoint 写入点 B
                await send({"type": "done"})
                await _revise_loop(state, send, recv_queue)
                return

            # intake / processing / error:无法恢复,LLM 会话已死
            await send({"type": "checkpoint_lost",
                        "message": "上次会话在处理过程中中断,需要重新开始"})

        # ── 正常流程 ──────────────────────────────────────────────────
        state = await session_start(state, send, recv_queue)
        state = await intake(state, send, recv_queue)
        state = await process(state, send, recv_queue)
        state = await validate(state, send)                 # ← checkpoint 写入点 A
        state = await finalize(state, send)                 # ← checkpoint 写入点 B
        await send({"type": "done"})
        await _revise_loop(state, send, recv_queue)

    except AgentException as e:
        logger.error("DAG error | code={} msg={}", e.code, e.message)
        await send({"type": "error", "code": e.code, "message": e.message})
    except Exception as e:
        logger.exception("Unexpected DAG error")
        await send({"type": "error", "code": "INTERNAL_ERROR", "message": str(e)})
    finally:
        cleanup_session(state)


async def _revise_loop(state, send, recv_queue):
    while True:
        msg = await recv_queue.get()
        if msg["type"] == "user_input":
            state = await revise_loop(state, send, recv_queue, msg["text"])
            state = await validate(state, send)             # ← checkpoint 写入点 A
            state = await finalize(state, send)             # ← checkpoint 写入点 B
            await send({"type": "done"})

Checkpoint 写入点

validatefinalize 节点完成后,通过推送特定消息触发 Backend 写入 DB:

写入点 节点 推送消息(Backend 监听后写 DB)
A validate 完成 {"type": "validated", "result_path": "..."}
B finalize 完成 {"type": "result_ready", "result_path": "..."}
done {"type": "done"} → Backend 将 status 更新为 "done"

checkpoint 写入由 Backend 负责(监听 Agent 推送的消息),Agent 只负责推送正确的消息。

异常体系(domain/exceptions.py

异常类型是领域错误词汇(统一语言的一部分,且 code 对应错误码契约 error-codes.md),故归领域层 domain/exceptions.py,由 domain 拥有。框架级的 exception_handler 注册属接口/基础设施关注点,放 middleware/error_handler.py,不污染 domain 的纯净(零框架/IO 依赖)。

domain/exceptions.py

class AgentException(Exception):
    def __init__(self, code: str, message: str, status_code: int = 500):
        self.code = code
        self.message = message
        self.status_code = status_code

class LLMStartupError(AgentException):
    def __init__(self):
        super().__init__("LLM_STARTUP_ERROR", "LLM 启动/连接失败")

class ExternalServiceTimeoutError(AgentException):
    def __init__(self, phase: str):
        super().__init__("EXTERNAL_SERVICE_TIMEOUT", f"外部依赖在 {phase} 阶段超时")

class ExternalServiceError(AgentException):
    def __init__(self, detail: str):
        super().__init__("EXTERNAL_SERVICE_ERROR", f"外部依赖返回错误: {detail}")

class OutputValidationError(AgentException):
    def __init__(self):
        super().__init__("INVALID_INPUT", "无法从输出中提取有效结果")

异常传播规则

  • DAG 节点内捕获异常 → 更新 state.status = "error" → 通过 send({"type": "error", "message": ...}) 推送给前端 → 抛给 runner
  • Runner 捕获 → 记录日志 → 关闭 LLM 会话 → 清理资源
  • 禁止在节点内静默 swallow 异常