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cb8a1e3c0f
CI / lint / typecheck / import-linter / tests / secrets (push) Canceled after 0s
FE↔后端联调实测暴露并修复： 1. 问卷键名三处错位（FE height_cm/weight_kg/psych_style vs 文档 height/weight/psyche_style）——vision._bmi 多键取值、diagnosis 维度 装配与规则上下文双键或运算，两侧谁改键名都不再炸 2. celery worker asyncio.run 每投递起新 loop + 模块级引擎缓存 → asyncpg 连接跨 loop（同进程第 3 个报告任务必现 RuntimeError: attached to a different loop；集成测试单循环掩盖）。新增 apps/worker/loop.py 持久 loop，report/ping 两任务接入 E2E 终态： psyche_style/height_weight 恢复、BMI 体型确定值、ok 26/32、 真实 LLM 文案通过校验 degraded=False。
298 lines
13 KiB
Python
298 lines
13 KiB
Python
"""报告生成的 celery 任务（name=``meida.report.generate``，cpu 队列，T-P3-07/09）。
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注册说明：``apps/worker/celery_app.py`` 的 include 目前只含 apps.worker.tasks
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（本批禁改文件），worker 进程要注册本模块需要把 include 补上——由协调者在
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合并阶段处理；API 侧用 send_task 按任务名投递，两侧只靠名字衔接，互不 import。
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worker 侧 LLM 网关装配：apps.api.deps 属 HTTP 层，worker 不得 import apps.api
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（apps 互不依赖契约），这里按同一配方自建；改网关装配时两处同步。
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成本归因约定：阶段经 gateway 调用时以 ``ref_type="report"``、
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``ref_id=str(report_id)`` 记账——成功结案按这个口径聚合写
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``rp_report.model_info`` / ``cost_cents``（ob_ai_call 是唯一数据源，架构 §13）。
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"""
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from __future__ import annotations
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from datetime import UTC, datetime
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from decimal import Decimal
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from typing import Any, cast
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from sqlalchemy import func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.orm.attributes import flag_modified
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from apps.worker import loop as worker_loop
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from apps.worker.celery_app import celery_app
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from packages.billing.service import BillingService
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from packages.domain.task.state import TERMINAL_STATUSES, TaskStatus
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from packages.llm.budget import DailyBudgetGuard, RedisCostCounter
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from packages.llm.circuit import CircuitBreakerRegistry
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from packages.llm.cost import (
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CompositeAICallRecorder,
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ModelRate,
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PeakAwareRateTable,
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RateTable,
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)
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from packages.llm.gateway import LLMGateway
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from packages.llm.prompts import PromptRegistry
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from packages.llm.providers.base import LLMProvider
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from packages.llm.providers.deepseek import DeepSeekProvider
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from packages.llm.providers.zhipu import ZhipuGLMProvider
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from packages.llm.recording import PrometheusAICallRecorder, SqlAlchemyAICallRecorder
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from packages.llm.routing import SceneRouter, build_scene_configs
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from packages.report import repo as report_repo
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from packages.report.pipeline import (
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ReportContext,
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StageFailureError,
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assemble_stages,
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load_reservation,
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run_pipeline,
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)
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from packages.shared.config import Settings, get_settings
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from packages.shared.context import bind_context
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from packages.shared.db import get_session_factory
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from packages.shared.errors import AppError, ErrorCode
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from packages.shared.logging import get_logger
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from packages.shared.models import AiCall, RpReport, Task
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from packages.shared.redis_client import get_redis
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from packages.task import repo as task_repo
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from packages.task.service import TaskService
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logger = get_logger(__name__)
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def build_llm_gateway(settings: Settings) -> LLMGateway:
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"""worker 侧装配，与 apps.api.deps.build_llm_gateway 同构（见模块 docstring）。"""
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providers: dict[str, LLMProvider] = {
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"deepseek": DeepSeekProvider(
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api_key=settings.deepseek_api_key,
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base_url=settings.deepseek_base_url,
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default_model=settings.deepseek_model,
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),
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"zhipu": ZhipuGLMProvider(
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api_key=settings.zhipu_api_key,
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base_url=settings.zhipu_base_url,
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default_model=settings.zhipu_model,
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),
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}
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default_rate = ModelRate.from_mapping(settings.llm_default_cost_rate)
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rates = PeakAwareRateTable(
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RateTable(
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{
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model: ModelRate.from_mapping(rate)
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for model, rate in settings.llm_cost_rates.items()
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},
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default=default_rate,
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),
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RateTable(
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{
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model: ModelRate.from_mapping(rate)
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for model, rate in settings.llm_cost_rates_peak.items()
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},
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default=default_rate,
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)
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if settings.llm_cost_rates_peak
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else None,
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enabled=settings.llm_peak_pricing_enabled,
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)
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return LLMGateway(
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providers=providers,
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router=SceneRouter(
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build_scene_configs(
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primary_provider=settings.llm_primary_provider,
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backup_provider=settings.llm_backup_provider,
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structured_max_retries=settings.llm_structured_max_retries,
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overrides=settings.llm_scene_overrides,
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)
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),
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prompts=PromptRegistry(
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settings.prompts_dir, cache_prefix_mode=settings.llm_cache_prefix_mode
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),
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rates=rates,
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recorder=CompositeAICallRecorder(
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SqlAlchemyAICallRecorder(get_session_factory()),
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PrometheusAICallRecorder(),
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),
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budget=DailyBudgetGuard(
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RedisCostCounter(get_redis()),
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daily_budget_cents=Decimal(settings.llm_daily_budget_cents),
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enabled=settings.llm_daily_budget_enabled,
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tz_offset_hours=settings.llm_budget_timezone_offset_hours,
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tiers=list(settings.llm_budget_tiers),
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),
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breakers=CircuitBreakerRegistry(
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failure_threshold=settings.llm_circuit_failure_threshold,
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cooldown_seconds=settings.llm_circuit_cooldown_seconds,
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),
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)
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async def _aggregate_cost(session: AsyncSession, report_id: int) -> tuple[Decimal, int]:
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"""聚合该报告的 AI 成本与调用次数（口径见模块 docstring 的归因约定）。"""
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result = await session.execute(
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select(func.coalesce(func.sum(AiCall.cost_cents), 0), func.count()).where(
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AiCall.ref_type == "report", AiCall.ref_id == str(report_id)
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)
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)
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row = result.one()
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return Decimal(row[0]), int(row[1])
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async def _settle_success(
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session: AsyncSession,
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task: Task,
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report: RpReport,
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settings: Settings,
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stage_names: list[str],
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) -> None:
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"""成功结案：commit 配额（幂等）+ succeeded + completed_at + 成本聚合。"""
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cost_cents, ai_calls = await _aggregate_cost(session, report.report_id)
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report.status = "succeeded"
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report.completed_at = datetime.now(UTC)
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report.cost_cents = cost_cents
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report.model_info = {
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"stages": stage_names,
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"vision_provider": settings.report_vision_provider,
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"ai_calls": ai_calls,
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# Decimal 不能直接进 JSONB；字符串保留精度，展示层再格式化。
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"cost_cents": str(cost_cents),
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}
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reservation = await load_reservation(session, task.task_id)
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if reservation is not None:
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await BillingService(session).commit(reservation)
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# 任务中心视图同步收口（前端轮询的就是 tk_task，不是 rp_report）。
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await TaskService(session).transition(
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task_id=task.task_id,
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target=TaskStatus.SUCCEEDED,
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stage_text="已完成",
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result={"report_id": str(report.report_id), "version": report.version},
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)
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await session.commit()
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logger.info(
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"report_succeeded",
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report_id=report.report_id,
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task_id=task.task_id,
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cost_cents=str(cost_cents),
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ai_calls=ai_calls,
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)
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async def _generate_report(task_id: int) -> dict[str, Any]:
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"""执行一条报告流水线（celery 包装层的内芯；集成测试直调的就是它）。"""
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settings = get_settings()
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factory = get_session_factory()
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async with factory() as session:
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task = await task_repo.get_for_update(session, task_id)
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if task is None:
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raise AppError(ErrorCode.NOT_FOUND, message=f"任务不存在：{task_id}")
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current = TaskStatus(task.status)
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if current in TERMINAL_STATUSES:
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# 重复投递/幂等重放的守卫：已结案的任务不再执行，防重复扣配额。
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logger.info("report_task_replay_skipped", task_id=task_id, status=task.status)
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return {"task_id": str(task_id), "status": task.status, "skipped": True}
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report_id_raw = task.payload.get("report_id")
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if not isinstance(report_id_raw, str | int):
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raise AppError(ErrorCode.STATE_CONFLICT, message="任务缺少 report_id")
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report_id = int(report_id_raw)
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report = await report_repo.get_report(session, report_id)
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report_input = await report_repo.get_input(session, report_id)
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if report is None or report_input is None:
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raise AppError(ErrorCode.STATE_CONFLICT, message="报告数据不完整")
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service = TaskService(session)
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# 首跑是 PENDING；重试入站可能是 RUNNING（worker 崩溃重投）或 FAILED
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# （上一轮失败后重试），先归一到 QUEUED（状态机允许，且会维护
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# retry_count）再进 RUNNING。
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if current is not TaskStatus.QUEUED:
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await service.transition(task_id=task_id, target=TaskStatus.QUEUED, stage_text="排队中")
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await service.transition(task_id=task_id, target=TaskStatus.RUNNING, stage_text="分析中")
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report.status = "running"
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await session.commit() # RUNNING 先落库：前端进度与崩溃恢复都读它
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gateway = build_llm_gateway(settings)
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try:
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stages = assemble_stages(settings)
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ctx = ReportContext(
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report=report,
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report_input=report_input,
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session=session,
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settings=settings,
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gateway=gateway,
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task_id=task_id,
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)
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await run_pipeline(ctx, stages)
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await _settle_success(session, task, report, settings, [s.name for s in stages])
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finally:
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await gateway.aclose()
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return {"task_id": str(task_id), "report_id": str(report_id), "status": "succeeded"}
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async def _fail_report(task_id: int, message: str) -> None:
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"""基础设施异常重试耗尽后的兜底结案：failed + 退款（尽力而为）。
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与 run_pipeline 的失败结案不同，这里没有阶段名——异常发生在流水线之外
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（装配、DB 连接等），错误摘要以 worker 为责任方落库。结案失败只记日志：
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此时额度停在 reserved，靠流水对账兜底。
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"""
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factory = get_session_factory()
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try:
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async with factory() as session:
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task = await task_repo.get_for_update(session, task_id)
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if task is None or TaskStatus(task.status) in TERMINAL_STATUSES:
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return
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report_id_raw = task.payload.get("report_id")
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if isinstance(report_id_raw, str | int):
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report = await report_repo.get_report(session, int(report_id_raw))
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if report is not None and report.status != "succeeded":
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report.status = "failed"
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report.result["error"] = {
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"stage": "worker",
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"type": "infrastructure",
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"message": message[:200],
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}
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# JSONB 深变更要显式标脏，否则 flush 按值比较会跳过 UPDATE。
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flag_modified(report, "result")
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await TaskService(session).transition(
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task_id=task_id,
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target=TaskStatus.FAILED,
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stage_text="执行失败",
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error_message=message,
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)
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reservation = await load_reservation(session, task_id)
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if reservation is not None:
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await BillingService(session).refund(reservation, reason="report_worker_failed")
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await session.commit()
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except Exception:
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logger.exception("report_fail_settle_failed", task_id=task_id)
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# Celery 的 task 装饰器没有类型标注，会把被装饰函数擦成 untyped
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@celery_app.task(name="meida.report.generate", bind=True, max_retries=1) # type: ignore[untyped-decorator]
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def generate_report(self: Any, task_id: int) -> dict[str, Any]:
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"""cpu 队列的报告生成入口。
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重试语义：网络/基础设施类异常重试一次——重跑时 ``derived_features``
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已落库，视觉阶段自然跳过（T-P3-09）；阶段业务失败（StageFailureError）
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已在流水线内结案（退款已提交），重跑也不会好，不再重试。
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"""
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bind_context(task_id=task_id)
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try:
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return cast("dict[str, Any]", worker_loop.run(_generate_report(task_id)))
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except StageFailureError as exc:
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logger.warning(
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"report_stage_failed",
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task_id=task_id,
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stage=exc.stage_name,
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error=f"{type(exc.original).__name__}: {exc.original}",
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)
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raise
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except Exception as exc:
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if self.request.retries < self.max_retries:
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logger.warning("report_generate_retry", task_id=task_id, error=str(exc))
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raise self.retry(exc=exc, countdown=10) from exc
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logger.exception("report_generate_failed_after_retry", task_id=task_id)
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worker_loop.run(_fail_report(task_id, f"{type(exc).__name__}: {exc}"))
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raise
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