fix(deploy): serialize production frontend build

AGENTS.md

@@ -4,7 +4,7 @@ This file provides guidance to Codex (Codex.ai/code) when working with code in t
 
 ## 项目概述
 
-**AgentEvalTool** 是智能体质量评估工具集平台（v0.5.0-dev），用于评估 AI 数字员工（tutu-api 通道）和 AI 助手（OpenClaw）的服务质量。Python 3.11 后端 + TypeScript/React 前端，SQLite 持久化。领域术语词汇表见 `CONTEXT.md`，关键决策见 `docs/adr/`。
+**AgentEvalTool** 是智能体质量评估工具集平台（v1.0.0），用于评估 AI 数字员工（tutu-api 通道）和 AI 助手（OpenClaw）的服务质量。Python 3.11 后端 + TypeScript/React 前端，SQLite 持久化。领域术语词汇表见 `CONTEXT.md`，关键决策见 `docs/adr/`。
 
 ## 常用命令
 

README.md

@@ -1,6 +1,6 @@
 # AgentEvalTool
 
-> **当前开发版本**: v0.4.0-dev 「联」 · 已发布至 t480 · 发布说明见 [docs/release-notes-v0.4.md](docs/release-notes-v0.4.md)
+> **当前版本**：v1.0.0 · 已部署至 t480 开发线与 volcengine-102 正式线 · [发布说明](docs/release-notes-v1.0.md)
 
 智能体质量评估工具集平台。
 
@@ -18,16 +18,18 @@
 - 运营仪表盘（指标卡 / 趋势 / 场景表现 / 触发来源分布）
 - 文件管理（分类树 + 上传下载）
 - OpenClaw 免登录 iframe 集成 + 标准 agenteval-run 技能
+- 周期评估活动（耐久调度、探索式评测、智能分析、周期对比）
+- OpenClaw 驱动的独立智能评估（规划、审批、会话执行、结构化报告）
 - Web 管理后台（FastAPI + React）
 
-## v0.4 亮点
+## v1.0 亮点
 
-- **AI 助手标准化**：`triggered_by` 全链路标记 + 标准 SKILL.md 版本管理与自动同步 + API Key 自动注入
-- **简单登录**：`AGENTEVAL_ADMIN_PASSWORD` 一键启用访问控制，机器调用（X-API-Key）不受影响
-- **仪表盘重构**：6 指标卡 + 趋势 + 场景表现排行 + 触发来源分布
-- **报告页重做**：场景筛选、富选项下拉、一键重置、对比报告限同场景
-- **keep-alive 刷新修复**：标签页激活自动刷新，根治"评测记录消失"问题
-- **测试基线**：232 个测试
+- **双评测体系**：静态评估以考纲和规则为权威；智能评估由 OpenClaw 规划并模拟真实用户行为。
+- **周期质量运营**：Campaign 支持耐久调度、探索发现、智能分析和跨周期对比。
+- **耐久架构**：数据库保存运行与智能作业权威状态，进程重启后可按明确边界恢复。
+- **统一管理后台**：详情与报告采用 Drawer/页内视图，列表、轮询、反馈和危险操作遵循一致交互基线。
+- **双线部署**：t480 用于开发验证，volcengine-102 通过不可变镜像、数据备份和迁移发布正式服务。
+- **测试基线**：后端 744 项、前端 15 项自动化测试通过。
 
 ## 快速开始
 
@@ -76,6 +78,7 @@ npm run dev
 完整的文档集位于 `docs/` 目录：
 
 - **[文档索引](docs/README.md)** - 文档导航和快速查找
+- **[v1.0 发布说明](docs/release-notes-v1.0.md)** - 当前发布能力与验收基线
 - **[需求分析](docs/requirements-v1.0.md)** - 项目背景、功能需求、验证标准
 - **[架构设计](docs/architecture-v1.0.md)** - 系统架构、核心抽象、项目结构
 - **[数据模型](docs/data-models-v1.0.md)** - 数据库表结构、模型关系

backend/agenteval/evaluation/analysis.py

@@ -8,12 +8,10 @@
 
 import asyncio
 import json
-import logging
 from typing import Any, Awaitable, Callable, Optional
 
 from sqlmodel import Session
 
-from agenteval.evaluation.report import load_campaign_view
 from agenteval.model_gateway import ModelGateway
 from agenteval.models import Campaign, ModelCapability, RunStatus
 from agenteval.services.model_configs import (
@@ -21,18 +19,12 @@ from agenteval.services.model_configs import (
     ModelConfigService,
     ModelRuntimeConfig,
 )
-from agenteval.storage.db import get_session
 from agenteval.storage.model_config_repository import ModelConfigRepository
 from agenteval.storage.repository import (
-    CampaignAnalysisRepository,
-    CampaignRepository,
     RunRepository,
 )
-from agenteval.task_registry import TaskRegistry
 from agenteval.utils.llm import extract_reply_text, parse_json_from_llm_text
 
-_logger = logging.getLogger("agenteval")
-
 # LLM 客户端协议：接收 chat 消息列表，返回文本内容。生产实现走 ModelGateway，
 # 测试注入假客户端（同 MockChannel 先例）。
 ChatClient = Callable[[list[dict[str, str]]], Awaitable[str]]
@@ -242,29 +234,6 @@ async def analyze_campaign(
     }
 
 
-def _maybe_enqueue_period_comparison(campaign: Campaign, session: Session) -> None:
-    """正式线活动分析完成后自动链到周期对比（v0.8）。
-
-    前提：正式线（time_scale == 1）、分析模型可解析、存在自动基线
-    （同活动串且已有 completed 分析）。任一不满足静默跳过；异常仅告警，
-    不影响刚落库的分析结果。
-    """
-    try:
-        if campaign.time_scale != 1:
-            return
-        if resolve_analysis_model(campaign, session) is None:
-            return
-        # 延迟导入：comparison 顶层依赖 analysis（resolve_analysis_model），
-        # 反向导入会成环。
-        from agenteval.evaluation import comparison as comparison_module
-
-        if comparison_module.resolve_auto_baseline(campaign, session) is None:
-            return
-        comparison_module.start_campaign_comparison(campaign.id, triggered_by="auto")
-    except Exception as exc:
-        _logger.warning("活动 %s 自动周期对比跳过: %s", campaign.id, exc)
-
-
 def gateway_chat_client(runtime: ModelRuntimeConfig) -> ChatClient:
     """Shared ChatClient factory for analysis/comparison background executors."""
     gateway = ModelGateway(timeout=180.0)
@@ -273,90 +242,3 @@ def gateway_chat_client(runtime: ModelRuntimeConfig) -> ChatClient:
         return await gateway.chat(runtime, messages, temperature=0.2)
 
     return _chat
-
-
-async def execute_campaign_analysis(
-    campaign_id: str,
-    *,
-    triggered_by: str,
-    chat_client: Optional[ChatClient] = None,
-) -> None:
-    """后台执行体：generating → completed/failed 状态机（upsert，每活动一行）。
-
-    与 Runs 同款后台任务约定：自持 Session、try/finally 关闭、失败落 error。
-    """
-    session = get_session()
-    try:
-        analyses = CampaignAnalysisRepository(session)
-        campaign = CampaignRepository(session).get(campaign_id)
-        if not campaign:
-            return
-        runtime = resolve_analysis_model(campaign, session)
-        if runtime is None:
-            analyses.upsert(
-                campaign_id, status="failed", triggered_by=triggered_by,
-                error="未配置分析模型：请在模型配置中心将某个 chat 配置设为「分析默认」",
-            )
-            return
-        analyses.upsert(
-            campaign_id, status="generating",
-            model_config_id=runtime.id, triggered_by=triggered_by,
-        )
-        try:
-            client = chat_client or gateway_chat_client(runtime)
-            runs = RunRepository(session).list_by_campaign(campaign_id)
-            view = load_campaign_view(session, campaign)
-            result = await analyze_campaign(
-                campaign=campaign,
-                report=view["report"],
-                failure_samples=collect_failure_samples(campaign_id, session),
-                valid_run_ids={r.id for r in runs if r.id},
-                chat_client=client,
-                exploration_summary=view["exploration"],
-            )
-        except Exception as exc:
-            _logger.warning("活动 %s 智能分析失败: %s", campaign_id, exc)
-            analyses.upsert(
-                campaign_id, status="failed", model_config_id=runtime.id,
-                error=str(exc)[:500], triggered_by=triggered_by,
-            )
-            return
-        analyses.upsert(
-            campaign_id, status="completed", result=result,
-            model_config_id=runtime.id, triggered_by=triggered_by,
-        )
-        _maybe_enqueue_period_comparison(campaign, session)
-    finally:
-        session.close()
-
-
-analysis_registry = TaskRegistry()
-
-
-def start_campaign_analysis(campaign_id: str, *, triggered_by: str) -> None:
-    """以后台任务启动分析生成（状态经 campaign_analyses 表观测）。
-
-    registry 持强引用防 GC，shutdown 时统一收敛；同 id 在跑时幂等不重复派生。
-    """
-    analysis_registry.launch(
-        campaign_id,
-        lambda _cancel: execute_campaign_analysis(campaign_id, triggered_by=triggered_by),
-    )
-
-
-def enqueue_campaign_analysis(campaign_id: str, *, triggered_by: str) -> None:
-    """Durably queue analysis, then launch the in-process worker."""
-    session = get_session()
-    try:
-        CampaignAnalysisRepository(session).enqueue(campaign_id, triggered_by=triggered_by)
-    finally:
-        session.close()
-    start_campaign_analysis(campaign_id, triggered_by=triggered_by)
-
-
-def resume_queued_campaign_analysis(session: Session) -> int:
-    """Re-launch analysis jobs persisted before a process interruption."""
-    rows = CampaignAnalysisRepository(session).list_queued()
-    for row in rows:
-        start_campaign_analysis(row.campaign_id, triggered_by=row.triggered_by or "manual")
-    return len(rows)

backend/agenteval/evaluation/campaign_lifecycle.py

@@ -15,11 +15,8 @@ from agenteval.models import Campaign, CampaignPlanEntry, CampaignStatus, Explor
 from agenteval.storage.db import utc_now
 from agenteval.storage.model_config_repository import ModelConfigRepository
 from agenteval.storage.repository import (
-    CampaignAnalysisRepository,
-    CampaignPeriodComparisonRepository,
     CampaignRepository,
     CampaignWriteStatus,
-    RunRepository,
     ScenarioRepository,
     TargetRepository,
 )
@@ -41,21 +38,11 @@ class CampaignLifecycleError(Exception):
     detail: str
 
 
-@dataclass(frozen=True)
-class CampaignRecoverySummary:
-    """Durable work reconciled during process startup."""
-
-    interrupted_runs: int = 0
-    interrupted_analysis: int = 0
-    resumed_campaigns: int = 0
-    resumed_analysis: int = 0
-
-
 def start_campaign(
     session: Session,
     campaign_id: str,
     *,
-    launch: Optional[Callable[[str, Session], object]] = None,
+    launch: Optional[Callable[[str], object]] = None,
 ) -> Optional[Campaign]:
     """Start a planned Campaign through a conditional lifecycle write."""
     repo = CampaignRepository(session)
@@ -72,7 +59,7 @@ def start_campaign(
         if not result.applied or campaign is None:
             return None
     if launch is not None and campaign.id:
-        launch(campaign.id, session)
+        launch(campaign.id)
     return campaign
 
 
@@ -87,7 +74,7 @@ def create_campaign(
     analysis_model_config_id: Optional[str] = None,
     exploration_seeds: Optional[ExplorationSeeds] = None,
     exploration_budget: Optional[ExplorationBudgetConfig] = None,
-    launch: Optional[Callable[[str, Session], object]] = None,
+    launch: Optional[Callable[[str], object]] = None,
 ) -> Campaign:
     """Validate, commit and then launch one running Campaign.
 
@@ -127,7 +114,7 @@ def create_campaign(
     # Deliberately after the repository commit. Startup recovery can relaunch
     # this Campaign if the process dies before the callback runs.
     if launch is not None and campaign.id:
-        launch(campaign.id, session)
+        launch(campaign.id)
     return campaign
 
 
@@ -151,31 +138,6 @@ def cancel_campaign(
     return campaign
 
 
-def recover_campaign_runtime(session: Session, *, tick_seconds: float = 1.0) -> CampaignRecoverySummary:
-    """Reconcile all durable Campaign work and relaunch safe tasks.
-
-    The database is inspected and repaired before process-local tasks are
-    launched. Child Run reconciliation remains inside each resumed Campaign
-    loop, so a pending claim is resumed there while an orphaned running claim
-    is marked interrupted without replaying messages.
-    """
-    interrupted_runs = RunRepository(session).mark_orphans_failed()
-    interrupted_analysis = CampaignAnalysisRepository(session).mark_orphans_failed()
-    interrupted_analysis += CampaignPeriodComparisonRepository(session).mark_orphans_failed()
-
-    from agenteval.evaluation.analysis import resume_queued_campaign_analysis
-    from agenteval.evaluation.campaign_runner import resume_running_campaigns
-
-    resumed_campaigns = resume_running_campaigns(session, tick_seconds=tick_seconds)
-    resumed_analysis = resume_queued_campaign_analysis(session)
-    return CampaignRecoverySummary(
-        interrupted_runs=interrupted_runs,
-        interrupted_analysis=interrupted_analysis,
-        resumed_campaigns=resumed_campaigns,
-        resumed_analysis=resumed_analysis,
-    )
-
-
 def complete_campaign(
     session: Session,
     campaign_id: str,

backend/agenteval/evaluation/campaign_read_model.py

@@ -0,0 +1,159 @@
+"""Stable read projections for evaluation Campaigns."""
+
+from typing import Any, Optional
+
+from sqlmodel import Session
+
+from agenteval.evaluation.campaign_scheduler import clock_offset, elapsed_seconds
+from agenteval.evaluation.comparison import load_comparison_view
+from agenteval.evaluation.report import (
+    build_campaign_timeline,
+    generate_campaign_report,
+    summarize_campaign_progress,
+)
+from agenteval.exploration.summary import summarize_campaign_exploration
+from agenteval.storage.db import iso_utc, utc_now
+from agenteval.storage.repository import (
+    CampaignAnalysisRepository,
+    CampaignRepository,
+    RunRepository,
+    ScenarioRepository,
+    TargetRepository,
+)
+
+
+class CampaignReadModel:
+    """One interface for Campaign list, detail, report and export projections."""
+
+    def __init__(self, session: Session):
+        self._session = session
+        self._campaigns = CampaignRepository(session)
+        self._runs = RunRepository(session)
+        self._scenarios = ScenarioRepository(session)
+        self._analyses = CampaignAnalysisRepository(session)
+
+    def list_items(self) -> list[dict[str, Any]]:
+        campaigns = self._campaigns.list_all()
+        campaign_ids = [campaign.id for campaign in campaigns if campaign.id]
+        runs_by_campaign = self._runs.list_by_campaigns(campaign_ids)
+        items = []
+        for campaign in campaigns:
+            data = campaign.model_dump()
+            data["progress"] = summarize_campaign_progress(
+                campaign,
+                runs_by_campaign.get(campaign.id, []),
+            )
+            items.append(data)
+        return items
+
+    def detail(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        campaign = self._campaigns.get(campaign_id)
+        if campaign is None:
+            return None
+        data = campaign.model_dump()
+        runs = self._runs.list_by_campaign(campaign_id)
+        current_offset = 0.0
+        if campaign.started_at is not None:
+            current_offset = min(
+                clock_offset(
+                    elapsed_seconds=elapsed_seconds(now=utc_now(), started_at=campaign.started_at),
+                    time_scale=campaign.time_scale,
+                ),
+                float(campaign.window_seconds),
+            )
+        data["progress"] = {
+            "current_offset_seconds": current_offset,
+            "spawned_runs": len(runs),
+            "completed_runs": sum(1 for run in runs if run.status.value == "completed"),
+        }
+        return data
+
+    def report(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        campaign = self._campaigns.get(campaign_id)
+        if campaign is None:
+            return None
+        report = self._core_report(campaign)
+        exploration = summarize_campaign_exploration(self._session, campaign_id)
+        if exploration is not None:
+            report["exploration"] = exploration
+        return report
+
+    def timeline(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        campaign = self._campaigns.get(campaign_id)
+        if campaign is None:
+            return None
+        entries = build_campaign_timeline(
+            campaign,
+            self._runs.list_by_campaign(campaign_id),
+            scenario_names=self._scenarios.name_map(),
+        )
+        return {"entries": entries}
+
+    def analysis(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        if self._campaigns.get(campaign_id) is None:
+            return None
+        row = self._analyses.get_by_campaign(campaign_id)
+        if row is None:
+            return {"status": "none"}
+        return {
+            "status": row.status,
+            "result": row.get_result(),
+            "error": row.error,
+            "model_config_id": row.model_config_id,
+            "triggered_by": row.triggered_by,
+            "updated_at": iso_utc(row.updated_at),
+        }
+
+    def comparison(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        campaign = self._campaigns.get(campaign_id)
+        return load_comparison_view(self._session, campaign) if campaign is not None else None
+
+    def full_view(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        campaign = self._campaigns.get(campaign_id)
+        if campaign is None:
+            return None
+        report = self._core_report(campaign)
+        exploration = summarize_campaign_exploration(self._session, campaign_id)
+        analysis = self.analysis(campaign_id)
+        comparison = load_comparison_view(self._session, campaign)
+        return {
+            "report": report,
+            "exploration": exploration,
+            "analysis": analysis.get("result") if analysis and analysis.get("status") == "completed" else None,
+            "comparison": comparison if comparison.get("status") != "none" else None,
+        }
+
+    def markdown_projection(self, campaign_id: str) -> Optional[dict[str, Any]]:
+        campaign = self._campaigns.get(campaign_id)
+        view = self.full_view(campaign_id)
+        if campaign is None or view is None:
+            return None
+
+        comparison = None
+        comparison_view = view["comparison"]
+        if comparison_view and comparison_view.get("status") == "completed":
+            row = comparison_view.get("comparison") or {}
+            baseline = row.get("baseline") or {}
+            comparison = {
+                "result": row.get("result"),
+                "baseline_name": baseline.get("name"),
+                "baseline_completed_at": baseline.get("completed_at"),
+                "model_name": row.get("model_name"),
+                "updated_at": row.get("updated_at"),
+                "metric_diff": comparison_view.get("metric_diff"),
+            }
+
+        target = TargetRepository(self._session).get(campaign.target_id)
+        return {
+            **view,
+            "comparison": comparison,
+            "target_name": target.name if target else None,
+            "scenario_names": self._scenarios.name_map(),
+        }
+
+    def _core_report(self, campaign) -> dict[str, Any]:
+        return generate_campaign_report(
+            campaign,
+            self._runs.list_by_campaign(campaign.id),
+            scenario_names=self._scenarios.name_map(),
+        )

backend/agenteval/evaluation/campaign_runner.py

@@ -7,21 +7,21 @@ plan occurrence before reusing the existing single-run execution path
 primary idempotency authority; the legacy campaign summary remains a fallback
 for pre-identity Runs created before this migration.
 
-This module also hosts the durable scheduler loop: a thin async shell that,
-tick by tick, maps real wall-clock elapsed time (since the campaign's persisted
-``started_at``) to a window offset and calls ``advance_campaign``. All authority
-lives in the DB (window start, spawned progress, status), so the loop can be
-torn down and rebuilt on restart without losing or duplicating work.
+``CampaignRuntime`` owns the durable scheduler loop and exposes only lifecycle-
+level operations. Clock mapping, reconciliation, ticking, claims and process-
+local task handles remain implementation details. All authority lives in the
+DB, so loops can be rebuilt on restart without losing or duplicating work.
 """
 
 import asyncio
 import logging
 from dataclasses import dataclass, field
-from typing import Optional
+from datetime import datetime
+from typing import Awaitable, Callable, Optional
 
 from sqlmodel import Session
 
-from agenteval.evaluation.analysis import enqueue_campaign_analysis, resolve_analysis_model
+from agenteval.evaluation.analysis import resolve_analysis_model
 from agenteval.evaluation.campaign_lifecycle import complete_campaign
 from agenteval.evaluation.campaign_lifecycle import start_campaign as start_campaign_lifecycle
 from agenteval.evaluation.campaign_scheduler import (
@@ -33,6 +33,7 @@ from agenteval.evaluation.campaign_scheduler import (
     resolve_finalize,
 )
 from agenteval.evaluation.engine import EvalEngine
+from agenteval.evaluation.intelligence_jobs import enqueue_campaign_analysis
 from agenteval.models import (
     Campaign,
     CampaignStatus,
@@ -40,6 +41,7 @@ from agenteval.models import (
     EvalRun,
     RunStatus,
     RunTrigger,
+    Scenario,
     SchedulerState,
 )
 from agenteval.storage.db import get_session, utc_now
@@ -58,9 +60,8 @@ DEFAULT_TICK_SECONDS = 1.0
 
 _logger = logging.getLogger("agenteval")
 
-# Live loop tasks + cooperative cancel events, keyed by campaign id. Authority
-# is the DB; this registry only holds the in-process handles for the loop.
-campaign_registry = TaskRegistry()
+
+ChildRunExecutor = Callable[[Campaign, Scenario, EvalRun, Session], Awaitable[None]]
 
 
 @dataclass
@@ -79,6 +80,14 @@ class CampaignRecoveryResult:
     failed_run_ids: list[str] = field(default_factory=list)
 
 
+@dataclass(frozen=True)
+class CampaignRuntimeRecovery:
+    """Durable Campaign work reconciled during process startup."""
+
+    interrupted_runs: int = 0
+    resumed_campaigns: int = 0
+
+
 def _spawned_indices(campaign: Campaign, session: Optional[Session] = None) -> set[int]:
     """Return plan entries completed by durable identities or legacy progress.
 
@@ -99,40 +108,22 @@ def _spawned_indices(campaign: Campaign, session: Optional[Session] = None) -> s
     return {
         plan_index
         for plan_index, entry in enumerate(campaign.plan)
-        if (
-            plan_index in occurrences
-            and set(range(entry.count)).issubset(occurrences[plan_index])
-        )
+        if (plan_index in occurrences and set(range(entry.count)).issubset(occurrences[plan_index]))
         or (plan_index not in occurrences and plan_index in legacy)
     }
 
 
-def current_window_offset(campaign: Campaign) -> float:
-    """The campaign's live window position (seconds), clamped to the window.
-
-    RUNNING campaigns derive it from the persisted ``started_at`` and
-    ``time_scale``; not-yet-started campaigns report 0.
-    """
-    if campaign.started_at is None:
-        return 0.0
-    offset = clock_offset(
-        elapsed_seconds=elapsed_seconds(now=utc_now(), started_at=campaign.started_at),
-        time_scale=campaign.time_scale,
-    )
-    return min(offset, float(campaign.window_seconds))
-
-
-def campaign_progress(campaign: Campaign, runs: list[EvalRun]) -> dict:
-    """Live progress of a campaign, derived from its child Runs.
-
-    ``completed_runs`` counts only COMPLETED child Runs; failures stay out of
-    this field (pass_rate semantics are ADR-0002's concern, not this counter).
-    """
-    return {
-        "current_offset_seconds": current_window_offset(campaign),
-        "spawned_runs": len(runs),
-        "completed_runs": sum(1 for r in runs if r.status == RunStatus.COMPLETED),
-    }
+async def _execute_child_run(
+    campaign: Campaign,
+    scenario: Scenario,
+    run: EvalRun,
+    session: Session,
+) -> None:
+    target = TargetRepository(session).get(campaign.target_id)
+    if not target:
+        raise ValueError(f"campaign target missing: {campaign.target_id}")
+    engine = EvalEngine(target=target, scenario=scenario, triggered_by=RunTrigger.CAMPAIGN)
+    await engine.run(existing_run=run)
 
 
 async def _spawn_child_run(
@@ -142,6 +133,7 @@ async def _spawn_child_run(
     plan_index: int,
     occurrence_index: int,
     session: Session,
+    execute_child_run: ChildRunExecutor = _execute_child_run,
 ) -> Optional[str]:
     """Claim one occurrence and drive its pending Run through the engine.
 
@@ -168,20 +160,17 @@ async def _spawn_child_run(
         raise RuntimeError(f"Campaign child claim returned no Run: {claim.status.value}")
 
     if run.status is RunStatus.PENDING:
-        target = TargetRepository(session).get(campaign.target_id)
-        if not target:
-            raise ValueError(f"campaign target missing: {campaign.target_id}")
-        engine = EvalEngine(target=target, scenario=scenario, triggered_by=RunTrigger.CAMPAIGN)
-        await engine.run(existing_run=run)
+        await execute_child_run(campaign, scenario, run, session)
     return run.id or ""
 
 
-async def advance_campaign(
+async def _advance_campaign(
     *,
     campaign_id: str,
     elapsed_seconds: float,
     session: Session,
     cancel_event: Optional[asyncio.Event] = None,
+    execute_child_run: ChildRunExecutor = _execute_child_run,
 ) -> Optional[AdvanceResult]:
     """Advance the campaign clock to ``elapsed_seconds`` and spawn due Runs.
 
@@ -219,6 +208,7 @@ async def advance_campaign(
                     plan_index=due.index,
                     occurrence_index=occurrence_index,
                     session=session,
+                    execute_child_run=execute_child_run,
                 )
                 if run_id is None:
                     claim_rejected = True
@@ -259,11 +249,12 @@ def _auto_start_analysis(campaign: Campaign, session: Session) -> None:
         _logger.warning("活动 %s 自动分析触发失败（已跳过）: %s", campaign.id, exc)
 
 
-async def reconcile_campaign_child_runs(
+async def _reconcile_campaign_child_runs(
     campaign_id: str,
     session: Session,
     *,
     cancel_event: Optional[asyncio.Event] = None,
+    execute_child_run: ChildRunExecutor = _execute_child_run,
 ) -> Optional[CampaignRecoveryResult]:
     """Resume safe pending claims and fail running Runs without replaying.
 
@@ -278,9 +269,7 @@ async def reconcile_campaign_child_runs(
         return CampaignRecoveryResult()
 
     run_repo = RunRepository(session)
-    result = CampaignRecoveryResult(
-        failed_run_ids=run_repo.mark_campaign_running_interrupted(campaign_id)
-    )
+    result = CampaignRecoveryResult(failed_run_ids=run_repo.mark_campaign_running_interrupted(campaign_id))
     for run in run_repo.list_pending_campaign_children(campaign_id):
         if cancel_event is not None and cancel_event.is_set():
             break
@@ -306,6 +295,7 @@ async def reconcile_campaign_child_runs(
                 plan_index=plan_index,
                 occurrence_index=occurrence_index,
                 session=session,
+                execute_child_run=execute_child_run,
             )
             if resumed_id is None:
                 break
@@ -326,8 +316,14 @@ async def reconcile_campaign_child_runs(
 # ── durable scheduler loop ──────────────────────────────────────────────────
 
 
-async def run_campaign_loop(
-    campaign_id: str, cancel: asyncio.Event, *, tick_seconds: float = DEFAULT_TICK_SECONDS
+async def _run_campaign_loop(
+    campaign_id: str,
+    cancel: asyncio.Event,
+    *,
+    session_factory: Callable[[], Session],
+    now: Callable[[], datetime],
+    tick_seconds: float,
+    execute_child_run: ChildRunExecutor,
 ) -> None:
     """Drive one campaign to completion, ticking on real wall-clock time.
 
@@ -336,18 +332,23 @@ async def run_campaign_loop(
     It exits when the window finishes, the campaign leaves RUNNING (e.g. it was
     cancelled), or the cooperative cancel event fires.
     """
-    session = get_session()
+    session = session_factory()
     try:
-        await reconcile_campaign_child_runs(campaign_id, session, cancel_event=cancel)
+        await _reconcile_campaign_child_runs(
+            campaign_id,
+            session,
+            cancel_event=cancel,
+            execute_child_run=execute_child_run,
+        )
         while not cancel.is_set():
             repo = CampaignRepository(session)
             campaign = repo.get(campaign_id)
             if not campaign:
                 return
 
-            now = utc_now()
+            current_time = now()
             decision = decide_tick(
-                now=now,
+                now=current_time,
                 started_at=campaign.started_at,
                 status=campaign.status,
                 window_seconds=campaign.window_seconds,
@@ -358,12 +359,13 @@ async def run_campaign_loop(
             if decision.action is TickAction.STOP:
                 return
 
-            elapsed = elapsed_seconds(now=now, started_at=campaign.started_at)
-            await advance_campaign(
+            elapsed = elapsed_seconds(now=current_time, started_at=campaign.started_at)
+            await _advance_campaign(
                 campaign_id=campaign_id,
                 elapsed_seconds=elapsed,
                 session=session,
                 cancel_event=cancel,
+                execute_child_run=execute_child_run,
             )
 
             if decision.action is TickAction.COMPLETE:
@@ -388,41 +390,74 @@ async def run_campaign_loop(
         session.close()
 
 
-def start_campaign(campaign_id: str, session: Session, *, tick_seconds: float = DEFAULT_TICK_SECONDS) -> Optional[asyncio.Task]:
-    """Move a campaign into RUNNING (stamping ``started_at`` on first start) and
-    launch its loop. Reused for both create-then-start and restart recovery:
-    a PLANNED campaign gets a fresh ``started_at``; an already-RUNNING one keeps
-    its original window start so recovery resumes at the correct offset.
-    """
-    campaign = CampaignRepository(session).get(campaign_id)
-    if not campaign or campaign.status in (CampaignStatus.COMPLETED, CampaignStatus.CANCELLED, CampaignStatus.FAILED):
-        return None
+class CampaignRuntime:
+    """Own durable Campaign execution behind one lifecycle-level interface."""
 
-    started = start_campaign_lifecycle(session, campaign_id)
-    if started is None:
-        return None
+    def __init__(
+        self,
+        *,
+        session_factory: Callable[[], Session] = get_session,
+        now: Callable[[], datetime] = utc_now,
+        tick_seconds: float = DEFAULT_TICK_SECONDS,
+        execute_child_run: ChildRunExecutor = _execute_child_run,
+    ) -> None:
+        self._session_factory = session_factory
+        self._now = now
+        self._tick_seconds = tick_seconds
+        self._execute_child_run = execute_child_run
+        self._registry = TaskRegistry()
 
-    return campaign_registry.launch(
-        campaign_id,
-        lambda cancel: run_campaign_loop(campaign_id, cancel, tick_seconds=tick_seconds),
-    )
+    def start(self, campaign_id: str) -> bool:
+        """Start or resume one durable Campaign, idempotently."""
+        session = self._session_factory()
+        try:
+            started = start_campaign_lifecycle(session, campaign_id)
+        finally:
+            session.close()
+        if started is None:
+            return False
+        self._launch(campaign_id)
+        return True
+
+    def cancel(self, campaign_id: str) -> None:
+        """Signal the process-local loop after durable cancellation commits."""
+        self._registry.cancel(campaign_id)
+
+    def recover(self) -> CampaignRuntimeRecovery:
+        """Repair interrupted Runs and relaunch every running Campaign."""
+        session = self._session_factory()
+        try:
+            interrupted_runs = RunRepository(session).mark_orphans_failed()
+            running_ids = [
+                campaign.id
+                for campaign in CampaignRepository(session).list_all()
+                if campaign.status is CampaignStatus.RUNNING and campaign.id
+            ]
+        finally:
+            session.close()
+        for campaign_id in running_ids:
+            self._launch(campaign_id)
+        return CampaignRuntimeRecovery(
+            interrupted_runs=interrupted_runs,
+            resumed_campaigns=len(running_ids),
+        )
+
+    async def shutdown(self) -> None:
+        """Gracefully stop all process-local Campaign loops."""
+        await self._registry.shutdown_all()
+
+    def _launch(self, campaign_id: str) -> None:
+        self._registry.launch(
+            campaign_id,
+            lambda cancel: _run_campaign_loop(
+                campaign_id,
+                cancel,
+                session_factory=self._session_factory,
+                now=self._now,
+                tick_seconds=self._tick_seconds,
+                execute_child_run=self._execute_child_run,
+            ),
+        )
 
 
-def request_cancel(campaign_id: str) -> None:
-    """Signal the loop (if live) to stop spawning and exit promptly."""
-    campaign_registry.cancel(campaign_id)
-
-
-def resume_running_campaigns(session: Session, *, tick_seconds: float = DEFAULT_TICK_SECONDS) -> int:
-    """On startup, relaunch a loop for every campaign left in RUNNING."""
-    resumed = 0
-    for campaign in CampaignRepository(session).list_all():
-        if campaign.status == CampaignStatus.RUNNING and campaign.id:
-            start_campaign(campaign.id, session, tick_seconds=tick_seconds)
-            resumed += 1
-    return resumed
-
-
-async def shutdown_all() -> None:
-    """Gracefully stop all live loops (Web app shutdown)."""
-    await campaign_registry.shutdown_all()
+campaign_runtime = CampaignRuntime()

backend/agenteval/evaluation/comparison.py

@@ -7,27 +7,23 @@ diff——全部确定性计算（ADR-0004 口径，经 ``generate_campaign_repo
 """
 
 import json
-import logging
 from datetime import datetime, timezone
 from typing import Any, Optional
 
 from sqlmodel import Session
 
-from agenteval.evaluation.analysis import ChatClient, gateway_chat_client, resolve_analysis_model
+from agenteval.evaluation.analysis import ChatClient, resolve_analysis_model
 from agenteval.evaluation.report import load_campaign_report
 from agenteval.models import Campaign, CampaignStatus
-from agenteval.storage.db import get_session, iso_utc, utc_now
+from agenteval.storage.db import iso_utc, utc_now
 from agenteval.storage.model_config_repository import ModelConfigRepository
 from agenteval.storage.repository import (
     CampaignAnalysisRepository,
     CampaignPeriodComparisonRepository,
     CampaignRepository,
 )
-from agenteval.task_registry import TaskRegistry
 from agenteval.utils.llm import parse_json_from_llm_text
 
-_logger = logging.getLogger("agenteval")
-
 _SAME_MOMENT_EPS = 1e-3
 
 _VALID_TRENDS = {"improving", "stable", "regressing"}
@@ -377,107 +373,3 @@ async def narrate_period_comparison(
         "problem_evolution": problem_evolution,
         "suggestion_tracking": suggestion_tracking,
     }
-
-
-async def execute_campaign_comparison(
-    campaign_id: str,
-    *,
-    triggered_by: str,
-    baseline_campaign_id: Optional[str] = None,
-    chat_client: Optional[ChatClient] = None,
-) -> None:
-    """后台执行体：generating → completed/failed 状态机（upsert，每活动一行）。
-
-    基线优先取显式指定（手动重选），缺省走自动基线。与 Runs 同款后台任务
-    约定：自持 Session、try/finally 关闭、失败落 error。
-    """
-    session = get_session()
-    try:
-        comparisons = CampaignPeriodComparisonRepository(session)
-        campaign = CampaignRepository(session).get(campaign_id)
-        if not campaign:
-            return
-
-        try:
-            baseline = validate_comparison_request(
-                session,
-                campaign,
-                explicit_baseline_id=baseline_campaign_id,
-            )
-        except ComparisonError as exc:
-            comparisons.upsert(
-                campaign_id,
-                status="failed",
-                triggered_by=triggered_by,
-                error=str(exc),
-            )
-            return
-
-        runtime = resolve_analysis_model(campaign, session)
-        baseline_analysis = CampaignAnalysisRepository(session).get_by_campaign(baseline.id)
-        current_analysis = CampaignAnalysisRepository(session).get_by_campaign(campaign_id)
-
-        comparisons.upsert(
-            campaign_id,
-            status="generating",
-            baseline_campaign_id=baseline.id,
-            model_config_id=runtime.id,
-            triggered_by=triggered_by,
-        )
-        try:
-            diff = compute_metric_diff(
-                load_campaign_report(session, baseline),
-                load_campaign_report(session, campaign),
-            )
-            valid_scenario_ids = {s["scenario_id"] for s in diff["scenarios"]}
-            result = await narrate_period_comparison(
-                baseline_analysis=baseline_analysis.get_result(),
-                current_analysis=current_analysis.get_result(),
-                metric_diff=diff,
-                valid_scenario_ids=valid_scenario_ids,
-                chat_client=chat_client or gateway_chat_client(runtime),
-            )
-        except Exception as exc:
-            _logger.warning("活动 %s 周期对比失败: %s", campaign_id, exc)
-            comparisons.upsert(
-                campaign_id,
-                status="failed",
-                baseline_campaign_id=baseline.id,
-                model_config_id=runtime.id,
-                error=str(exc)[:500],
-                triggered_by=triggered_by,
-            )
-            return
-        comparisons.upsert(
-            campaign_id,
-            status="completed",
-            baseline_campaign_id=baseline.id,
-            result=result,
-            model_config_id=runtime.id,
-            triggered_by=triggered_by,
-        )
-    finally:
-        session.close()
-
-
-comparison_registry = TaskRegistry()
-
-
-def start_campaign_comparison(
-    campaign_id: str,
-    *,
-    triggered_by: str,
-    baseline_campaign_id: Optional[str] = None,
-) -> None:
-    """以后台任务启动对比生成（状态经 campaign_period_comparisons 表观测）。
-
-    registry 持强引用防 GC，shutdown 时统一收敛；同 id 在跑时幂等不重复派生。
-    """
-    comparison_registry.launch(
-        campaign_id,
-        lambda _cancel: execute_campaign_comparison(
-            campaign_id,
-            triggered_by=triggered_by,
-            baseline_campaign_id=baseline_campaign_id,
-        ),
-    )

backend/agenteval/evaluation/intelligence_jobs.py

@@ -0,0 +1,347 @@
+"""Durable runtime for Campaign intelligence jobs.
+
+智能分析与周期对比是两个领域工作 adapter；本 module 统一掌握它们的
+持久排队、进程内幂等启动、重启恢复和关闭顺序。数据库行是耐久权威，
+TaskRegistry 只保存当前进程中的任务句柄。
+"""
+
+import logging
+from collections.abc import Callable
+from typing import Any, Optional
+
+from sqlmodel import Session
+
+from agenteval.storage.db import get_session
+from agenteval.storage.repository import (
+    CampaignAnalysisRepository,
+    CampaignPeriodComparisonRepository,
+)
+from agenteval.task_registry import TaskRegistry
+
+_registry = TaskRegistry()
+_logger = logging.getLogger("agenteval")
+MAX_QUEUED_RECOVERY_ATTEMPTS = 3
+
+
+def _job_key(kind: str, campaign_id: str) -> str:
+    return f"{kind}:{campaign_id}"
+
+
+def _launch_analysis(campaign_id: str, *, triggered_by: str) -> None:
+    async def run(_cancel) -> None:
+        await execute_campaign_analysis_job(campaign_id, triggered_by=triggered_by)
+
+    _registry.launch(_job_key("analysis", campaign_id), run)
+
+
+def _launch_comparison(
+    campaign_id: str,
+    *,
+    triggered_by: str,
+    baseline_campaign_id: str,
+) -> None:
+    async def run(_cancel) -> None:
+        await execute_campaign_comparison_job(
+            campaign_id,
+            triggered_by=triggered_by,
+            baseline_campaign_id=baseline_campaign_id,
+        )
+
+    _registry.launch(_job_key("comparison", campaign_id), run)
+
+
+async def execute_campaign_analysis_job(
+    campaign_id: str,
+    *,
+    triggered_by: str,
+    chat_client: Any = None,
+    session_factory: Optional[Callable[[], Session]] = None,
+) -> None:
+    """Claim and settle one intelligent-analysis job."""
+    from agenteval.evaluation.analysis import (
+        analyze_campaign,
+        collect_failure_samples,
+        gateway_chat_client,
+        resolve_analysis_model,
+    )
+    from agenteval.evaluation.comparison import resolve_auto_baseline
+    from agenteval.evaluation.report import load_campaign_view
+    from agenteval.storage.repository import CampaignRepository, RunRepository
+
+    session = (session_factory or get_session)()
+    try:
+        analyses = CampaignAnalysisRepository(session)
+        row = analyses.get_by_campaign(campaign_id)
+        if row is None:
+            row = analyses.enqueue(campaign_id, triggered_by=triggered_by)
+        if not analyses.claim_queued(campaign_id).claimed:
+            return
+        effective_trigger = row.triggered_by or triggered_by
+
+        campaign = CampaignRepository(session).get(campaign_id)
+        if campaign is None:
+            analyses.upsert(
+                campaign_id,
+                status="failed",
+                triggered_by=effective_trigger,
+                error="campaign not found",
+            )
+            return
+        runtime = resolve_analysis_model(campaign, session)
+        if runtime is None:
+            analyses.upsert(
+                campaign_id,
+                status="failed",
+                triggered_by=effective_trigger,
+                error="未配置分析模型：请在模型配置中心将某个 chat 配置设为「分析默认」",
+            )
+            return
+        analyses.upsert(
+            campaign_id,
+            status="generating",
+            model_config_id=runtime.id,
+            triggered_by=effective_trigger,
+        )
+        try:
+            client = chat_client or gateway_chat_client(runtime)
+            runs = RunRepository(session).list_by_campaign(campaign_id)
+            view = load_campaign_view(session, campaign)
+            result = await analyze_campaign(
+                campaign=campaign,
+                report=view["report"],
+                failure_samples=collect_failure_samples(campaign_id, session),
+                valid_run_ids={run.id for run in runs if run.id},
+                chat_client=client,
+                exploration_summary=view["exploration"],
+            )
+        except Exception as exc:
+            _logger.warning("活动 %s 智能分析失败: %s", campaign_id, exc)
+            analyses.upsert(
+                campaign_id,
+                status="failed",
+                model_config_id=runtime.id,
+                error=str(exc)[:500],
+                triggered_by=effective_trigger,
+            )
+            return
+        analyses.upsert(
+            campaign_id,
+            status="completed",
+            result=result,
+            model_config_id=runtime.id,
+            triggered_by=effective_trigger,
+        )
+
+        try:
+            if campaign.time_scale != 1 or resolve_analysis_model(campaign, session) is None:
+                return
+            baseline = resolve_auto_baseline(campaign, session)
+            if baseline is None:
+                return
+            enqueue_campaign_comparison(
+                campaign.id,
+                triggered_by="auto",
+                baseline_campaign_id=baseline.id,
+                session=session,
+            )
+        except Exception as exc:
+            _logger.warning("活动 %s 自动周期对比跳过: %s", campaign.id, exc)
+    finally:
+        session.close()
+
+
+async def execute_campaign_comparison_job(
+    campaign_id: str,
+    *,
+    triggered_by: str,
+    baseline_campaign_id: Optional[str] = None,
+    chat_client: Any = None,
+    session_factory: Optional[Callable[[], Session]] = None,
+) -> None:
+    """Claim and settle one period-comparison job."""
+    from agenteval.evaluation.analysis import gateway_chat_client, resolve_analysis_model
+    from agenteval.evaluation.comparison import (
+        ComparisonError,
+        compute_metric_diff,
+        narrate_period_comparison,
+        validate_comparison_request,
+    )
+    from agenteval.evaluation.report import load_campaign_report
+    from agenteval.storage.repository import CampaignRepository
+
+    session = (session_factory or get_session)()
+    try:
+        comparisons = CampaignPeriodComparisonRepository(session)
+        campaign = CampaignRepository(session).get(campaign_id)
+        if campaign is None:
+            return
+
+        row = comparisons.get_by_campaign(campaign_id)
+        if row is None:
+            try:
+                initial_baseline = validate_comparison_request(
+                    session,
+                    campaign,
+                    explicit_baseline_id=baseline_campaign_id,
+                )
+            except ComparisonError as exc:
+                comparisons.upsert(
+                    campaign_id,
+                    status="failed",
+                    triggered_by=triggered_by,
+                    error=str(exc),
+                )
+                return
+            row = comparisons.enqueue(
+                campaign_id,
+                baseline_campaign_id=initial_baseline.id,
+                triggered_by=triggered_by,
+            )
+        if not comparisons.claim_queued(campaign_id).claimed:
+            return
+
+        effective_trigger = row.triggered_by or triggered_by
+        effective_baseline_id = baseline_campaign_id or row.baseline_campaign_id
+        try:
+            baseline = validate_comparison_request(
+                session,
+                campaign,
+                explicit_baseline_id=effective_baseline_id,
+            )
+        except ComparisonError as exc:
+            comparisons.upsert(
+                campaign_id,
+                status="failed",
+                baseline_campaign_id=effective_baseline_id,
+                triggered_by=effective_trigger,
+                error=str(exc),
+            )
+            return
+
+        runtime = resolve_analysis_model(campaign, session)
+        baseline_analysis = CampaignAnalysisRepository(session).get_by_campaign(baseline.id)
+        current_analysis = CampaignAnalysisRepository(session).get_by_campaign(campaign_id)
+        comparisons.upsert(
+            campaign_id,
+            status="generating",
+            baseline_campaign_id=baseline.id,
+            model_config_id=runtime.id,
+            triggered_by=effective_trigger,
+        )
+        try:
+            diff = compute_metric_diff(
+                load_campaign_report(session, baseline),
+                load_campaign_report(session, campaign),
+            )
+            result = await narrate_period_comparison(
+                baseline_analysis=baseline_analysis.get_result(),
+                current_analysis=current_analysis.get_result(),
+                metric_diff=diff,
+                valid_scenario_ids={item["scenario_id"] for item in diff["scenarios"]},
+                chat_client=chat_client or gateway_chat_client(runtime),
+            )
+        except Exception as exc:
+            _logger.warning("活动 %s 周期对比失败: %s", campaign_id, exc)
+            comparisons.upsert(
+                campaign_id,
+                status="failed",
+                baseline_campaign_id=baseline.id,
+                model_config_id=runtime.id,
+                error=str(exc)[:500],
+                triggered_by=effective_trigger,
+            )
+            return
+        comparisons.upsert(
+            campaign_id,
+            status="completed",
+            baseline_campaign_id=baseline.id,
+            result=result,
+            model_config_id=runtime.id,
+            triggered_by=effective_trigger,
+        )
+    finally:
+        session.close()
+
+
+def enqueue_campaign_analysis(
+    campaign_id: str,
+    *,
+    triggered_by: str,
+    session: Optional[Session] = None,
+) -> None:
+    """Persist an analysis job, then launch its process-local worker."""
+    owns_session = session is None
+    active_session = session or get_session()
+    try:
+        row = CampaignAnalysisRepository(active_session).enqueue(
+            campaign_id,
+            triggered_by=triggered_by,
+        )
+    finally:
+        if owns_session:
+            active_session.close()
+    if row.status == "queued":
+        _launch_analysis(campaign_id, triggered_by=row.triggered_by or triggered_by)
+
+
+def enqueue_campaign_comparison(
+    campaign_id: str,
+    *,
+    triggered_by: str,
+    baseline_campaign_id: str,
+    session: Optional[Session] = None,
+) -> None:
+    """Persist a comparison job, then launch its process-local worker."""
+    owns_session = session is None
+    active_session = session or get_session()
+    try:
+        row = CampaignPeriodComparisonRepository(active_session).enqueue(
+            campaign_id,
+            baseline_campaign_id=baseline_campaign_id,
+            triggered_by=triggered_by,
+        )
+    finally:
+        if owns_session:
+            active_session.close()
+    if row.status == "queued":
+        _launch_comparison(
+            campaign_id,
+            triggered_by=row.triggered_by or triggered_by,
+            baseline_campaign_id=row.baseline_campaign_id,
+        )
+
+
+def recover_campaign_intelligence_jobs(session: Session) -> tuple[int, int]:
+    """Fail interrupted work and relaunch every durably queued job."""
+    analyses = CampaignAnalysisRepository(session)
+    comparisons = CampaignPeriodComparisonRepository(session)
+    interrupted = analyses.mark_orphans_failed() + comparisons.mark_orphans_failed()
+
+    queued_analyses = analyses.prepare_queued_recovery(
+        MAX_QUEUED_RECOVERY_ATTEMPTS,
+        "服务重启恢复次数超过上限，分析任务已终止",
+    )
+    for row in queued_analyses:
+        _launch_analysis(row.campaign_id, triggered_by=row.triggered_by or "manual")
+
+    queued_comparisons = comparisons.prepare_queued_recovery(
+        MAX_QUEUED_RECOVERY_ATTEMPTS,
+        "服务重启恢复次数超过上限，周期对比任务已终止",
+    )
+    for row in queued_comparisons:
+        _launch_comparison(
+            row.campaign_id,
+            triggered_by=row.triggered_by or "manual",
+            baseline_campaign_id=row.baseline_campaign_id,
+        )
+    return interrupted, len(queued_analyses) + len(queued_comparisons)
+
+
+def is_intelligence_job_running(kind: str, campaign_id: str) -> bool:
+    """Expose process-local liveness without exposing registry internals."""
+    return _registry.is_running(_job_key(kind, campaign_id))
+
+
+async def shutdown_campaign_intelligence_jobs() -> None:
+    """Stop every live analysis and comparison worker."""
+    await _registry.shutdown_all()

backend/agenteval/evaluation/report.py

@@ -230,7 +230,7 @@ def _run_window_offset(campaign: Campaign, run: EvalRun) -> float:
 def summarize_campaign_progress(campaign: Campaign, runs: list[EvalRun]) -> dict[str, Any]:
     """Compact list-row progress: completed vs *planned* total, plus pass_rate.
 
-    Unlike ``campaign_progress`` (live window position), this powers the list
+    Unlike the detail projection's live window position, this powers the list
     view. ``planned_total`` is the sum of plan-entry counts — a fixed target the
     campaign works toward, so the progress bar fills from 0 rather than tracking
     a growing spawned count. ``overall_pass_rate`` reuses ``aggregate_runs`` so
@@ -361,30 +361,13 @@ def load_campaign_report(session: Session, campaign: Campaign) -> dict[str, Any]
 
 
 def load_campaign_view(session: Session, campaign: Campaign) -> dict[str, Any]:
-    """活动级读模型单一出口：一次取齐报告 / 探索 / 分析 / 对比。
+    """Compatibility entry for the unified Campaign read model."""
+    from agenteval.evaluation.campaign_read_model import CampaignReadModel
 
-    四个数据源总是被一起取（markdown 导出、分析执行器、前端报告抽屉），
-    统一入口消除调用方的拼装逻辑。各子模块的取法保持不变，此处只做组合。
-    """
-    from agenteval.evaluation.comparison import load_comparison_view
-    from agenteval.exploration.summary import summarize_campaign_exploration
-    from agenteval.storage.repository import CampaignAnalysisRepository
-
-    report = load_campaign_report(session, campaign)
-    exploration = summarize_campaign_exploration(session, campaign.id)
-
-    analysis_row = CampaignAnalysisRepository(session).get_by_campaign(campaign.id)
-    analysis = analysis_row.get_result() if analysis_row and analysis_row.status == "completed" else None
-
-    comparison_view = load_comparison_view(session, campaign)
-    comparison = comparison_view if comparison_view.get("status") != "none" else None
-
-    return {
-        "report": report,
-        "exploration": exploration,
-        "analysis": analysis,
-        "comparison": comparison,
-    }
+    view = CampaignReadModel(session).full_view(campaign.id)
+    if view is None:
+        raise ValueError(f"campaign not found: {campaign.id}")
+    return view
 
 
 def save_report(run_id: str, fmt: str = "html", output_dir: Optional[Path] = None) -> Path:

backend/agenteval/storage/db.py

@@ -239,6 +239,7 @@ class CampaignAnalysisDB(SQLModel, table=True):
     model_config_id: Optional[str] = None
     error: Optional[str] = None
     triggered_by: str = "manual"
+    recovery_attempts: int = 0
     created_at: Optional[datetime] = Field(default_factory=utc_now)
     updated_at: Optional[datetime] = Field(default_factory=utc_now)
 
@@ -266,6 +267,7 @@ class CampaignPeriodComparisonDB(SQLModel, table=True):
     model_config_id: Optional[str] = None
     error: Optional[str] = None
     triggered_by: str = "manual"
+    recovery_attempts: int = 0
     created_at: Optional[datetime] = Field(default_factory=utc_now)
     updated_at: Optional[datetime] = Field(default_factory=utc_now)
 

backend/agenteval/storage/repository.py

@@ -46,6 +46,22 @@ M = TypeVar("M")  # domain model
 DB = TypeVar("DB")  # persisted table row
 
 
+class AsyncJobClaimStatus(str, Enum):
+    CLAIMED = "claimed"
+    NOT_FOUND = "not_found"
+    ALREADY_CLAIMED = "already_claimed"
+    NOT_QUEUED = "not_queued"
+
+
+@dataclass(frozen=True)
+class AsyncJobClaimResult:
+    status: AsyncJobClaimStatus
+
+    @property
+    def claimed(self) -> bool:
+        return self.status is AsyncJobClaimStatus.CLAIMED
+
+
 class BaseRepository(Generic[M, DB]):
     """Shared CRUD skeleton for id-keyed entity repositories.
 
@@ -425,6 +441,21 @@ class RunRepository(BaseRepository[EvalRun, EvalRunDB]):
         statement = select(EvalRunDB).where(EvalRunDB.campaign_id == campaign_id).order_by(EvalRunDB.started_at)
         return [self._from_db(r) for r in self.session.exec(statement).all()]
 
+    def list_by_campaigns(self, campaign_ids: list[str]) -> dict[str, list[EvalRun]]:
+        """Load child Runs for multiple Campaigns in one query."""
+        grouped = {campaign_id: [] for campaign_id in campaign_ids}
+        if not campaign_ids:
+            return grouped
+        statement = (
+            select(EvalRunDB)
+            .where(EvalRunDB.campaign_id.in_(campaign_ids))  # type: ignore[union-attr]
+            .order_by(EvalRunDB.started_at)
+        )
+        for row in self.session.exec(statement).all():
+            if row.campaign_id in grouped:
+                grouped[row.campaign_id].append(self._from_db(row))
+        return grouped
+
     def mark_orphans_failed(self) -> int:
         """Fail process-orphaned Runs while preserving recoverable child claims.
 
@@ -764,6 +795,54 @@ class AsyncJobRepository(Generic[DB]):
         statement = select(self._table).where(self._table.campaign_id == campaign_id)  # type: ignore[attr-defined]
         return self.session.exec(statement).first()
 
+    def list_queued(self) -> list[DB]:
+        statement = select(self._table).where(self._table.status == "queued")  # type: ignore[attr-defined]
+        return list(self.session.exec(statement).all())
+
+    def claim_queued(self, campaign_id: str) -> "AsyncJobClaimResult":
+        """Atomically move one queued job to generating.
+
+        The status predicate is the durable idempotency authority. Competing
+        workers may observe the same queued row, but only one can claim it.
+        """
+        statement = (
+            sql_update(self._table)
+            .where(
+                self._table.campaign_id == campaign_id,  # type: ignore[attr-defined]
+                self._table.status == "queued",  # type: ignore[attr-defined]
+            )
+            .values(status="generating", error=None, updated_at=utc_now())
+        )
+        result = self.session.exec(statement)
+        self.session.commit()
+        self.session.expire_all()
+        if result.rowcount == 1:
+            return AsyncJobClaimResult(AsyncJobClaimStatus.CLAIMED)
+        row = self.get_by_campaign(campaign_id)
+        if row is None:
+            return AsyncJobClaimResult(AsyncJobClaimStatus.NOT_FOUND)
+        if row.status == "generating":  # type: ignore[attr-defined]
+            return AsyncJobClaimResult(AsyncJobClaimStatus.ALREADY_CLAIMED)
+        return AsyncJobClaimResult(AsyncJobClaimStatus.NOT_QUEUED)
+
+    def prepare_queued_recovery(self, max_attempts: int, exhausted_error: str) -> list[DB]:
+        """Increment queued recovery attempts and fail exhausted jobs."""
+        recoverable: list[DB] = []
+        rows = self.list_queued()
+        for row in rows:
+            if row.recovery_attempts >= max_attempts:  # type: ignore[attr-defined]
+                row.status = "failed"  # type: ignore[attr-defined]
+                row.error = exhausted_error  # type: ignore[attr-defined]
+            else:
+                row.recovery_attempts += 1  # type: ignore[attr-defined]
+                recoverable.append(row)
+            row.updated_at = utc_now()  # type: ignore[attr-defined]
+            self.session.add(row)
+        if rows:
+            self.session.commit()
+            self.session.expire_all()
+        return recoverable
+
     def mark_orphans_failed(self, error_message: str) -> int:
         """服务启动时清理：把滞留的 generating 行标记为 failed。
 
@@ -792,20 +871,22 @@ class CampaignAnalysisRepository(AsyncJobRepository[CampaignAnalysisDB]):
         """Persist an analysis job before launching its process-local task."""
         row = self.get_by_campaign(campaign_id)
         if row is None:
-            row = CampaignAnalysisDB(campaign_id=campaign_id)
-        row.status = "queued"
-        row.result = None
-        row.error = None
-        row.triggered_by = triggered_by
-        row.updated_at = utc_now()
+            row = CampaignAnalysisDB(campaign_id=campaign_id, status="queued", triggered_by=triggered_by)
+        elif row.status in {"queued", "generating"}:
+            return row
+        else:
+            row.status = "queued"
+            row.result = None
+            row.model_config_id = None
+            row.error = None
+            row.triggered_by = triggered_by
+            row.recovery_attempts = 0
+            row.updated_at = utc_now()
         self.session.add(row)
         self.session.commit()
         self.session.refresh(row)
         return row
 
-    def list_queued(self) -> list[CampaignAnalysisDB]:
-        return list(self.session.exec(select(CampaignAnalysisDB).where(CampaignAnalysisDB.status == "queued")).all())
-
     def upsert(
         self,
         campaign_id: str,
@@ -843,6 +924,38 @@ class CampaignPeriodComparisonRepository(AsyncJobRepository[CampaignPeriodCompar
 
     _table = CampaignPeriodComparisonDB
 
+    def enqueue(
+        self,
+        campaign_id: str,
+        *,
+        baseline_campaign_id: str,
+        triggered_by: str = "manual",
+    ) -> CampaignPeriodComparisonDB:
+        """Persist a comparison job before launching its process-local task."""
+        row = self.get_by_campaign(campaign_id)
+        if row is None:
+            row = CampaignPeriodComparisonDB(
+                campaign_id=campaign_id,
+                baseline_campaign_id=baseline_campaign_id,
+                status="queued",
+                triggered_by=triggered_by,
+            )
+        elif row.status in {"queued", "generating"}:
+            return row
+        else:
+            row.baseline_campaign_id = baseline_campaign_id
+            row.status = "queued"
+            row.result = None
+            row.model_config_id = None
+            row.error = None
+            row.triggered_by = triggered_by
+            row.recovery_attempts = 0
+            row.updated_at = utc_now()
+        self.session.add(row)
+        self.session.commit()
+        self.session.refresh(row)
+        return row
+
     def upsert(
         self,
         campaign_id: str,

backend/agenteval/web/app.py

@@ -32,28 +32,32 @@ from agenteval.web.websocket import ws_manager
 @asynccontextmanager
 async def lifespan(_: FastAPI):
     init_db()
-    # 评测任务是进程内 asyncio 任务，重启后不会恢复——清理僵尸运行（尽力而为，不阻断启动）
+    # 恢复耐久 Campaign/智能作业，并清理无法安全重放的中断运行（尽力而为，不阻断启动）。
     try:
         session = get_session()
         try:
-            from agenteval.evaluation.campaign_lifecycle import recover_campaign_runtime
+            from agenteval.evaluation.campaign_runner import campaign_runtime
+            from agenteval.evaluation.intelligence_jobs import recover_campaign_intelligence_jobs
 
-            recovery = recover_campaign_runtime(session)
+            interrupted_jobs, resumed_jobs = recover_campaign_intelligence_jobs(session)
+            recovery = campaign_runtime.recover()
             if recovery.interrupted_runs:
                 logging.getLogger("agenteval").warning(
                     "启动清理：%d 个中断的运行已标记为 failed", recovery.interrupted_runs
                 )
-            if recovery.interrupted_analysis:
+            if interrupted_jobs:
                 logging.getLogger("agenteval").warning(
-                    "启动清理：%d 条中断的分析/对比已标记为 failed", recovery.interrupted_analysis
+                    "启动清理：%d 条中断的分析/对比已标记为 failed",
+                    interrupted_jobs,
                 )
             if recovery.resumed_campaigns:
                 logging.getLogger("agenteval").warning(
                     "启动恢复：%d 个进行中的评估活动已续跑", recovery.resumed_campaigns
                 )
-            if recovery.resumed_analysis:
+            if resumed_jobs:
                 logging.getLogger("agenteval").warning(
-                    "启动恢复：%d 条排队中的活动分析已续跑", recovery.resumed_analysis
+                    "启动恢复：%d 条排队中的活动分析/对比已续跑",
+                    resumed_jobs,
                 )
         finally:
             session.close()
@@ -61,18 +65,16 @@ async def lifespan(_: FastAPI):
         logging.getLogger("agenteval").warning("启动清理失败（忽略）: %s", exc)
     yield
     # 优雅停止所有进程内任务：先停活动调度循环，再停在跑的评测运行，
-    # 最后停三条 LLM 任务链（分析 / 周期对比 / judge 复核）。
+    # 最后停活动智能作业（分析 / 周期对比）和 judge 复核。
     try:
-        from agenteval.evaluation.analysis import analysis_registry
-        from agenteval.evaluation.campaign_runner import shutdown_all
-        from agenteval.evaluation.comparison import comparison_registry
+        from agenteval.evaluation.campaign_runner import campaign_runtime
+        from agenteval.evaluation.intelligence_jobs import shutdown_campaign_intelligence_jobs
         from agenteval.exploration.judge import judge_registry
         from agenteval.web.routers.runs import run_registry
 
-        await shutdown_all()
+        await campaign_runtime.shutdown()
         await run_registry.shutdown_all()
-        await analysis_registry.shutdown_all()
-        await comparison_registry.shutdown_all()
+        await shutdown_campaign_intelligence_jobs()
         await judge_registry.shutdown_all()
     except Exception as exc:
         logging.getLogger("agenteval").warning("活动调度停止失败（忽略）: %s", exc)
@@ -104,7 +106,9 @@ app.include_router(scenarios.router, prefix="/api/scenarios", tags=["scenarios"]
 app.include_router(runs.router, prefix="/api/runs", tags=["runs"], dependencies=_api_deps)
 app.include_router(campaigns.router, prefix="/api/campaigns", tags=["campaigns"], dependencies=_api_deps)
 app.include_router(exploration.router, prefix="/api/exploration", tags=["exploration"], dependencies=_api_deps)
-app.include_router(intelligent_evals.router, prefix="/api/intelligent-evals", tags=["intelligent-evals"], dependencies=_api_deps)
+app.include_router(
+    intelligent_evals.router, prefix="/api/intelligent-evals", tags=["intelligent-evals"], dependencies=_api_deps
+)
 app.include_router(reports.router, prefix="/api/reports", tags=["reports"], dependencies=_api_deps)
 app.include_router(stats.router, prefix="/api/stats", tags=["stats"], dependencies=_api_deps)
 app.include_router(files.router, prefix="/api/files", tags=["files"], dependencies=_api_deps)

backend/agenteval/web/routers/campaigns.py

@@ -1,6 +1,6 @@
 """API routes for evaluation campaigns (评估活动).
 
-Creating a campaign starts its durable scheduler loop (``campaign_runner``),
+Creating a campaign starts its durable ``CampaignRuntime`` loop,
 which spawns child Runs across the (optionally compressed) service-cycle window
 until it finishes. Progress is authoritative in the DB, so detail queries report
 the live window position and spawned/completed Run counts, and a campaign can be
@@ -11,34 +11,17 @@ from fastapi import APIRouter, Body, Depends, HTTPException, Response
 from pydantic import BaseModel, Field
 from sqlmodel import Session
 
-from agenteval.evaluation.analysis import enqueue_campaign_analysis, resolve_analysis_model
+from agenteval.evaluation.analysis import resolve_analysis_model
 from agenteval.evaluation.campaign_lifecycle import CampaignCreateError, CampaignLifecycleError
 from agenteval.evaluation.campaign_lifecycle import cancel_campaign as cancel_campaign_lifecycle
 from agenteval.evaluation.campaign_lifecycle import create_campaign as create_campaign_lifecycle
-from agenteval.evaluation.campaign_runner import campaign_progress, request_cancel, start_campaign
-from agenteval.evaluation.comparison import (
-    ComparisonError,
-    load_comparison_view,
-    start_campaign_comparison,
-    validate_comparison_request,
-)
-from agenteval.evaluation.report import (
-    build_campaign_timeline,
-    load_campaign_report,
-    load_campaign_view,
-    summarize_campaign_progress,
-)
+from agenteval.evaluation.campaign_read_model import CampaignReadModel
+from agenteval.evaluation.campaign_runner import campaign_runtime
+from agenteval.evaluation.comparison import ComparisonError, validate_comparison_request
+from agenteval.evaluation.intelligence_jobs import enqueue_campaign_analysis, enqueue_campaign_comparison
 from agenteval.evaluation.report_render import render_campaign_markdown
-from agenteval.exploration.summary import summarize_campaign_exploration
 from agenteval.models import CampaignPlanEntry, CampaignStatus, ExplorationBudgetConfig, ExplorationSeeds
-from agenteval.storage.db import iso_utc
-from agenteval.storage.repository import (
-    CampaignAnalysisRepository,
-    CampaignRepository,
-    RunRepository,
-    ScenarioRepository,
-    TargetRepository,
-)
+from agenteval.storage.repository import CampaignRepository
 from agenteval.web.deps import get_db
 
 router = APIRouter()
@@ -57,15 +40,7 @@ class CreateCampaignRequest(BaseModel):
 
 @router.get("")
 async def list_campaigns(session: Session = Depends(get_db)) -> list[dict]:
-    repo = CampaignRepository(session)
-    run_repo = RunRepository(session)
-    result = []
-    for campaign in repo.list_all():
-        data = campaign.model_dump()
-        runs = run_repo.list_by_campaign(campaign.id)
-        data["progress"] = summarize_campaign_progress(campaign, runs)
-        result.append(data)
-    return result
+    return CampaignReadModel(session).list_items()
 
 
 @router.post("")
@@ -84,7 +59,7 @@ async def create_campaign(
             analysis_model_config_id=request.analysis_model_config_id,
             exploration_seeds=request.exploration_seeds,
             exploration_budget=request.exploration_budget,
-            launch=start_campaign,
+            launch=campaign_runtime.start,
         )
     except CampaignCreateError as exc:
         raise HTTPException(status_code=exc.status_code, detail=exc.detail) from exc
@@ -94,7 +69,7 @@ async def create_campaign(
 @router.post("/{campaign_id}/cancel")
 async def cancel_campaign(campaign_id: str, session: Session = Depends(get_db)) -> dict:
     try:
-        campaign = cancel_campaign_lifecycle(session, campaign_id, stop=request_cancel)
+        campaign = cancel_campaign_lifecycle(session, campaign_id, stop=campaign_runtime.cancel)
     except CampaignLifecycleError as exc:
         raise HTTPException(status_code=exc.status_code, detail=exc.detail) from exc
     return campaign.model_dump()
@@ -102,47 +77,25 @@ async def cancel_campaign(campaign_id: str, session: Session = Depends(get_db))
 
 @router.get("/{campaign_id}/report")
 async def get_campaign_report(campaign_id: str, session: Session = Depends(get_db)) -> dict:
-    campaign = CampaignRepository(session).get(campaign_id)
-    if not campaign:
+    report = CampaignReadModel(session).report(campaign_id)
+    if report is None:
         raise HTTPException(status_code=404, detail="campaign not found")
-    report = load_campaign_report(session, campaign)
-    exploration = summarize_campaign_exploration(session, campaign_id)
-    if exploration is not None:
-        report["exploration"] = exploration
     return report
 
 
 @router.get("/{campaign_id}/report/markdown")
 async def get_campaign_report_markdown(campaign_id: str, session: Session = Depends(get_db)) -> Response:
-    campaign = CampaignRepository(session).get(campaign_id)
-    if not campaign:
+    projection = CampaignReadModel(session).markdown_projection(campaign_id)
+    if projection is None:
         raise HTTPException(status_code=404, detail="campaign not found")
-    view = load_campaign_view(session, campaign)
-    scenario_names = ScenarioRepository(session).name_map()
-    target = TargetRepository(session).get(campaign.target_id)
-    target_name = target.name if target else None
-
-    comparison = None
-    if view["comparison"] and view["comparison"].get("status") == "completed":
-        cmp_view = view["comparison"]
-        cmp = cmp_view.get("comparison") or {}
-        baseline = cmp.get("baseline") or {}
-        comparison = {
-            "result": cmp.get("result"),
-            "baseline_name": baseline.get("name"),
-            "baseline_completed_at": baseline.get("completed_at"),
-            "model_name": cmp.get("model_name"),
-            "updated_at": cmp.get("updated_at"),
-            "metric_diff": cmp_view.get("metric_diff"),
-        }
 
     md = render_campaign_markdown(
-        view["report"],
-        analysis=view["analysis"],
-        comparison=comparison,
-        exploration=view["exploration"],
-        target_name=target_name,
-        scenario_names=scenario_names,
+        projection["report"],
+        analysis=projection["analysis"],
+        comparison=projection["comparison"],
+        exploration=projection["exploration"],
+        target_name=projection["target_name"],
+        scenario_names=projection["scenario_names"],
     )
     return Response(
         content=md,
@@ -153,29 +106,18 @@ async def get_campaign_report_markdown(campaign_id: str, session: Session = Depe
 
 @router.get("/{campaign_id}/timeline")
 async def get_campaign_timeline(campaign_id: str, session: Session = Depends(get_db)) -> dict:
-    campaign = CampaignRepository(session).get(campaign_id)
-    if not campaign:
+    timeline = CampaignReadModel(session).timeline(campaign_id)
+    if timeline is None:
         raise HTTPException(status_code=404, detail="campaign not found")
-    runs = RunRepository(session).list_by_campaign(campaign_id)
-    scenario_names = ScenarioRepository(session).name_map()
-    return {"entries": build_campaign_timeline(campaign, runs, scenario_names=scenario_names)}
+    return timeline
 
 
 @router.get("/{campaign_id}/analysis")
 async def get_campaign_analysis(campaign_id: str, session: Session = Depends(get_db)) -> dict:
-    if not CampaignRepository(session).get(campaign_id):
+    analysis = CampaignReadModel(session).analysis(campaign_id)
+    if analysis is None:
         raise HTTPException(status_code=404, detail="campaign not found")
-    row = CampaignAnalysisRepository(session).get_by_campaign(campaign_id)
-    if row is None:
-        return {"status": "none"}
-    return {
-        "status": row.status,
-        "result": row.get_result(),
-        "error": row.error,
-        "model_config_id": row.model_config_id,
-        "triggered_by": row.triggered_by,
-        "updated_at": iso_utc(row.updated_at),
-    }
+    return analysis
 
 
 @router.post("/{campaign_id}/analysis")
@@ -201,11 +143,10 @@ async def get_campaign_comparison(campaign_id: str, session: Session = Depends(g
     ``metric_diff`` 对应「生效基线」：已有对比行时为该行记录的基线，
     否则为自动基线；两者都没有时为 null。
     """
-    campaign = CampaignRepository(session).get(campaign_id)
-    if not campaign:
+    comparison = CampaignReadModel(session).comparison(campaign_id)
+    if comparison is None:
         raise HTTPException(status_code=404, detail="campaign not found")
-
-    return load_comparison_view(session, campaign)
+    return comparison
 
 
 class GenerateComparisonRequest(BaseModel):
@@ -228,17 +169,18 @@ async def trigger_campaign_comparison(
     except ComparisonError as exc:
         raise HTTPException(status_code=400, detail=str(exc))
 
-    start_campaign_comparison(campaign_id, triggered_by="manual", baseline_campaign_id=baseline.id)
+    enqueue_campaign_comparison(
+        campaign_id,
+        triggered_by="manual",
+        baseline_campaign_id=baseline.id,
+        session=session,
+    )
     return {"status": "generating"}
 
 
 @router.get("/{campaign_id}")
 async def get_campaign(campaign_id: str, session: Session = Depends(get_db)) -> dict:
-    campaign = CampaignRepository(session).get(campaign_id)
-    if not campaign:
+    campaign = CampaignReadModel(session).detail(campaign_id)
+    if campaign is None:
         raise HTTPException(status_code=404, detail="campaign not found")
-
-    runs = RunRepository(session).list_by_campaign(campaign_id)
-    data = campaign.model_dump()
-    data["progress"] = campaign_progress(campaign, runs)
-    return data
+    return campaign

deploy/volcengine-102/Dockerfile

@@ -11,6 +11,8 @@ RUN npm run build
 FROM python:3.11.15-slim-bookworm AS runtime
 WORKDIR /app
 
+COPY --from=frontend-build /app/frontend/web/dist ./frontend/web/dist
+
 ARG BUILD_COMMIT=unknown
 ARG BUILD_TIME=unknown
 ENV AGENTEVAL_BUILD_COMMIT=${BUILD_COMMIT}
@@ -37,7 +39,6 @@ COPY backend ./backend
 
 RUN pip install --no-cache-dir -e .
 
-COPY --from=frontend-build /app/frontend/web/dist ./frontend/web/dist
 COPY config/config.example.json ./config/config.json
 RUN mkdir -p ./data/scenarios ./data/reports
 

docs/README.md

@@ -1,8 +1,9 @@
 # AgentEvalTool 文档索引
 
-**版本**: v1.0  
-**日期**: 2026-07-09  
-**状态**: 已发布  
+**文档版本**: v1.1
+**项目版本**: v1.0.0
+**日期**: 2026-08-11
+**状态**: 已发布
 **作者**: AgentEval Team
 
 ---
@@ -36,6 +37,7 @@ AgentEvalTool 是一个智能体质量评估工具集平台，用于评估 AI
 |------|------|------|
 | **部署概览** | 部署方式、环境要求、运维指南 | [deployment/README.md](deployment/README.md) |
 | **t480 部署指南** | t480 测试服务器具体部署步骤 | [deployment/t480-v1.0.md](deployment/t480-v1.0.md) |
+| **volcengine-102 部署指南** | 正式线发布、验证与回滚 | [deployment/volcengine-102-v1.0.md](deployment/volcengine-102-v1.0.md) |
 
 ### 2.4 使用指南
 
@@ -48,8 +50,10 @@ AgentEvalTool 是一个智能体质量评估工具集平台，用于评估 AI
 
 | 文档 | 说明 | 链接 |
 |------|------|------|
-| **V1.1 发布说明** | 前端重构、后端增强、关键 Bug 修复 | [release-notes-v1.1.md](release-notes-v1.1.md) |
+| **V1.0.0 发布说明** | 双评测体系、耐久 Campaign、架构深化与双线部署 | [release-notes-v1.0.md](release-notes-v1.0.md) |
+| **V0.8 发布说明** | Campaign 周期对比与正式线演进基线 | [release-notes-v0.8.md](release-notes-v0.8.md) |
 | **V0.2 发布说明** | async 引擎、安全基线、测试基线、部署规范化 | [release-notes-v0.2.md](release-notes-v0.2.md) |
+| **历史 V1.1 编号文档** | 早期原型阶段编号，不代表当前 SemVer | [release-notes-v1.1.md](release-notes-v1.1.md) |
 
 ### 2.6 开发日志
 
@@ -58,7 +62,14 @@ AgentEvalTool 是一个智能体质量评估工具集平台，用于评估 AI
 | **v0.3.0 开发计划** | 模型配置中心、统一模型调用与旧配置迁移 | [plan-v0.3.md](plan-v0.3.md) |
 | **2026-07-15 评测执行页改版** | 布局修复、Tab 滚动、时区 Bug、时间过滤、UI 全面改版 | [dev-log-20260715.md](dev-log-20260715.md) |
 
-### 2.6 外部参考
+### 2.6 阶段归档
+
+| 文档 | 说明 | 链接 |
+|------|------|------|
+| **归档索引** | 已验收阶段的目标、决策、证据与后续约束 | [archive/README.md](archive/README.md) |
+| **Campaign 架构深化** | 耐久作业、读模型、运行时和正式线交付总结 | [archive/campaign-architecture-deepening-20260811-v1.0.md](archive/campaign-architecture-deepening-20260811-v1.0.md) |
+
+### 2.7 外部参考
 
 | 文档 | 说明 | 位置 |
 |------|------|------|
@@ -94,11 +105,11 @@ AgentEvalTool 是一个智能体质量评估工具集平台，用于评估 AI
 
 ## 四、版本说明
 
-- **当前版本**: v0.3.0-dev
-- **版本基线日期**: 2026-07-17
-- **状态**: 开发中（t480 开发线运行）
+- **当前版本**: v1.0.0
+- **版本基线日期**: 2026-08-11
+- **状态**: 已部署（t480 开发线、volcengine-102 正式线）
 
-所有文档均标注版本号，便于追踪和管理。版本发布说明见 [release-notes-v1.1.md](release-notes-v1.1.md)。
+所有文档均标注版本号，便于追踪和管理。当前发布说明见 [release-notes-v1.0.md](release-notes-v1.0.md)。
 
 ## 五、文档规范
 
@@ -131,4 +142,4 @@ AgentEvalTool 是一个智能体质量评估工具集平台，用于评估 AI
 
 ---
 
-**最后更新**: 2026-07-17
+**最后更新**: 2026-08-11

docs/adr/0003-campaign-phased-static-then-adaptive.md

@@ -51,6 +51,11 @@
 - **Claim 先于执行**：调度器对每个 occurrence 先执行条件 claim，再进入 `EvalEngine`。重复 tick、并发调度或重启不会创建第二个 Run；取消后的 Campaign 不允许新 claim，已启动 Run 可继续完成。
 - **恢复边界**：持久化为 `pending` 且仍属于 running Campaign 的子 Run 可以恢复；进程中断遗留的 `running` 子 Run 统一标记为 `failed/interrupted`，禁止重放可能已经发送的外部消息。
 - **生命周期 CAS**：创建、启动、取消和完成均通过生命周期模块与条件更新完成。取消竞态优先于完成；Campaign 终态与 running 探索会话结算在同一事务提交，任一步失败均保持活动与探索会话为 `running`，由后续调度 tick 重试。
-- **分析任务耐久化**：活动分析先写入 `queued` 再启动进程内 worker；重启恢复 queued 任务，遗留 `generating` 任务标记为中断失败。分析失败或重复执行不改变 Campaign 完成状态。
+- **活动智能作业耐久化**：智能分析与周期对比统一由活动智能作业 module 管理。两类作业都先写入 `queued` 再启动进程内 worker，并以 `queued → generating` 条件认领防止同一作业被重复执行。
+- **作业恢复边界**：重启恢复 queued 智能分析与周期对比；遗留 `generating` 作业标记为中断失败，不自动重放可能已经产生费用的模型调用。失败或重复执行不改变 Campaign 完成状态。
+- **进程句柄收口**：智能分析与周期对比共享一个进程内 TaskRegistry owner；Web 生命周期只恢复和关闭该 owner，不分别了解两条作业链的 registry。
+- **Campaign runtime seam**：Campaign 耐久执行统一由 `CampaignRuntime` module 提供 `start`、`cancel`、`recover`、`shutdown` 四个生命周期级操作。HTTP 与 Web 生命周期不再调用 tick、advance、reconcile、loop 或 TaskRegistry 阶段函数。
+- **内部 adapter**：真实 UTC 时钟与 `EvalEngine` child-Run 执行器是 runtime implementation 的默认 adapter；测试可注入可控时钟和本地执行器，但这些 internal seam 不进入生产调用方的 interface。
+- **恢复与取消**：`recover` 自行清理中断 Run、枚举 running Campaign 并重建循环；每个循环内部先 reconcile child Run，再 tick。`cancel` 只处理进程句柄，Campaign 终态仍先由生命周期 CAS 持久化。
 
-启动恢复顺序固定为：清理中断 Run 与 LLM 任务 → 重建 running Campaign 调度循环（其中包含 child Run reconciliation）→ 重启 queued 分析任务。该顺序保证恢复动作只依据已提交的数据库事实，不依赖上一次进程的内存状态。
+启动恢复顺序固定为：结算遗留 generating 智能作业并重启 queued 智能作业 → `CampaignRuntime.recover` 清理中断 Run 并重建 running Campaign 调度循环（每个循环先完成 child Run reconciliation）。该顺序保证恢复动作只依据已提交的数据库事实，不依赖上一次进程的内存状态。

docs/adr/0006-reject-generic-conditional-write-module.md

@@ -0,0 +1,35 @@
+# 拒绝跨领域通用条件写入 Module
+
+状态：已采纳（2026-08-11）
+
+## 背景
+
+Campaign 与 Intelligent Evaluation 的 Repository 都使用条件更新，并都区分 `applied`、`not_found`、`conflict`。因此曾考虑抽取跨领域的 compare-and-set module，以复用 SQL 模板和结果分类。
+
+## 删除测试
+
+假想 interface 至少需要调用方提供：数据库表与主键列、状态列、一个或多个期望状态、目标字段映射、时间戳策略、JSON 序列化、更新后模型映射，以及可选的同事务副作用。
+
+两个领域真正需要隐藏的知识并不相同：
+
+| 维度 | Campaign | Intelligent Evaluation |
+|---|---|---|
+| 状态条件 | 可接受多个来源状态 | 单一期望状态与完整转换表 |
+| 时间语义 | 调用方传入时间；按目标状态写开始或完成时间 | Repository 取当前时间；始终更新 `updated_at`，首次执行用 `coalesce` |
+| 业务字段 | 主要写状态 | 同时写计划、反馈或报告，并负责 JSON 序列化 |
+| 事务副作用 | 完成/取消时同步结算 Exploration Session | 无跨聚合结算 |
+| 冲突结果 | 返回当前 Campaign 快照 | 返回冲突分类，由 lifecycle 重新表达领域错误 |
+
+删除该假想 module 后，只会在两个 Repository 中恢复少量 SQL 更新与结果分类；状态规则、字段映射和事务副作用仍必须留在各自领域。它不能减少调用方需要掌握的知识，反而会把稳定的领域差异暴露为通用参数和回调，形成浅 interface。
+
+## 决策
+
+不创建跨 Campaign 与 Intelligent Evaluation 的通用条件写入 module。两侧保留领域命名的结果类型和 Repository 私有 helper；生命周期 module 继续作为生产调用方的写入 interface。
+
+只有出现第三个真实 adapter，且至少三个调用面共享相同的状态条件、时间策略、字段语义、事务副作用和冲突映射时，才重新评估该 seam。单纯重复 SQL 形状不足以建立新 module。
+
+## 影响
+
+- 保持领域事务知识的 locality，Campaign 结算变化不会影响 Intelligent Evaluation。
+- 接受少量 SQL 模板重复，避免通用字典、回调和类型擦除。
+- 测试继续穿过各自 lifecycle interface，断言持久状态和领域副作用，而不是测试通用 SQL helper。

docs/archive/README.md

@@ -0,0 +1,7 @@
+# 阶段归档索引
+
+本目录保存已经完成并通过验收的阶段性工作记录。归档文档用于说明阶段目标、实施结果、关键决策、验证证据和后续约束；正在讨论的方案仍保留在 Issue 或工作草稿中。
+
+| 日期 | 阶段 | 结果 | 文档 |
+|---|---|---|---|
+| 2026-08-11 | Campaign 架构深化与正式线交付 | 已完成并部署 | [campaign-architecture-deepening-20260811-v1.0.md](campaign-architecture-deepening-20260811-v1.0.md) |

docs/archive/campaign-architecture-deepening-20260811-v1.0.md

@@ -0,0 +1,43 @@
+# Campaign 架构深化阶段总结
+
+**版本**：v1.0
+**归档日期**：2026-08-11
+**阶段状态**：已完成并纳入项目 v1.0.0
+**代码基线**：`10a089e` → `1782b24`
+**需求来源**：Gitea Issue #2、`.scratch/refactor-plan-architecture-deepening-v2.md`
+
+## 一、阶段目标
+
+本阶段在不改变 HTTP 契约、业务口径、管理后台信息架构和部署拓扑的前提下，继续深化 Campaign 相关模块：统一智能分析与周期对比的耐久作业编排，建立稳定读模型，收窄 Campaign 运行时接口，并验证是否值得抽取跨领域条件写入模块。
+
+## 二、交付结果
+
+1. **耐久智能作业**：新增统一 owner，集中管理 queued 持久化、条件认领、任务句柄、成功/失败结算、启动恢复和关闭。重复入队不再把 `generating` 回退为 `queued`；恢复最多 3 次，避免无限模型调用。
+2. **Campaign 读模型**：列表、详情、报告、时间线、智能分析、周期对比和 Markdown 导出统一消费稳定 projection；列表 child Run 改为批量读取。
+3. **CampaignRuntime**：生产调用面收敛为 `start`、`cancel`、`recover`、`shutdown`，时钟、child Run 执行器、tick、reconcile 与 TaskRegistry 留在实现内部。
+4. **前端请求编排**：`useCampaignReport` 统一列表、报告快照、展开行时间线、状态感知轮询、silent refresh、生成操作和迟到响应过滤；页面回归渲染与交互职责。
+5. **删除测试**：拒绝通用条件写入模块。Campaign 与 Intelligent Evaluation 只有 SQL 外形相似，状态、时间、事务副作用和冲突语义不同；结论记录于 ADR-0006。
+
+## 三、质量与发布验收
+
+- 后端：`744 passed`。
+- 前端：`15 passed`；`tsc --noEmit` 与生产构建通过。
+- 迁移：Alembic upgrade/downgrade 往返通过，生产数据库位于 `d4e7f9a1b2c3 (head)`。
+- 代码质量：本阶段相关 Ruff 检查及 `git diff --check` 通过。
+- 阶段验收镜像：`agenteval:0.8.0-1782b24`；版本漂移随后在项目 `v1.0.0` 发布中统一修正。
+- 正式地址：<https://agenteval.solahqb22.cn/>；前端、健康接口和 OpenClaw 均验证成功。
+- 发布前备份：`/var/backups/agenteval/agenteval-0.8.0-1782b24-20260811T051927Z.tgz`。
+
+## 四、关键决策
+
+- 数据库是 Campaign 与智能作业的耐久权威；TaskRegistry 只保存当前进程句柄。
+- `queued` 可以有限恢复；遗留 `generating` 失败结算，不自动重放可能已产生外部副作用或费用的工作。
+- Campaign 读模型是跨 Repository 组合的唯一稳定 seam，Router 不拼装领域快照。
+- 保持单进程 FastAPI + SQLite 假设；引入多 worker 前必须重新评审认领、恢复和 SQLite 并发边界。
+
+## 五、后续事项
+
+- 阶段结束提交为 `1782b24`；后续发布提交统一项目版本并重新部署双线环境。
+- `.scratch/` 中原始计划和辅助脚本继续保留，未纳入版本控制。
+- 全仓库 Ruff 仍有 6 个历史迁移格式问题；与本阶段逻辑无关，后续可单独清理。
+- 下一轮架构工作应以真实第三个 adapter 或新部署约束为触发条件，避免仅因代码形状相似继续抽象。

docs/deployment/volcengine-102-v1.0.md

@@ -1,6 +1,6 @@
 # volcengine-102 正式线部署指南
 
-**状态**：已部署并通过正式域名验收（最后验证：2026-08-09）。
+**状态**：已部署并通过正式域名验收（最后验证：2026-08-11）。
 **Compose**：`deploy/volcengine-102/docker-compose.yml`
 **入口脚本**：`scripts/deploy-volcengine-102.sh`
 
@@ -53,8 +53,8 @@ export AGENTEVAL_PROD_BACKUP_DIR=/var/backups/agenteval
 发布必须基于已提交的 Git 版本；脚本会拒绝存在 tracked 未提交修改的工作区。推荐使用版本号加 commit 作为不可变镜像标签：
 
 ```bash
-scripts/deploy-volcengine-102.sh --dry-run --tag 0.8.0-6248568
-scripts/deploy-volcengine-102.sh --tag 0.8.0-6248568
+scripts/deploy-volcengine-102.sh --dry-run --tag 1.0.0-abcdef0
+scripts/deploy-volcengine-102.sh --tag 1.0.0-abcdef0
 ```
 
 脚本依次执行：SSH 检查 → 版本读取 → 远端 `.env` 检查 → 通过 `git archive HEAD` 生成并同步已提交源代码 → 备份数据 volume → 远端构建带版本元数据的镜像 → 启动双容器 → 等待健康接口 → 校验版本/commit → 鉴权 API 冒烟。
@@ -70,7 +70,7 @@ scripts/deploy-volcengine-102.sh --tag 0.8.0-6248568
 回滚只切换应用镜像，不自动降级数据库：
 
 ```bash
-scripts/deploy-volcengine-102.sh --rollback 0.8.0-previous
+scripts/deploy-volcengine-102.sh --rollback 1.0.0-previous
 ```
 
 每次发布和回滚前都会在远端备份 named volume 到 `AGENTEVAL_PROD_BACKUP_DIR`。如果某个版本包含不可逆数据迁移，应先停止服务、恢复匹配的数据备份，再启动旧镜像；不得只回滚代码而忽略数据库版本。

docs/release-notes-v1.0.md

@@ -0,0 +1,45 @@
+# AgentEvalTool v1.0.0 发布说明
+
+**版本**：v1.0.0
+**发布日期**：2026-08-11
+**状态**：已发布
+**作者**：AgentEval Team
+
+## 一、版本定位
+
+v1.0.0 标志 AgentEvalTool 从单次规则评测工具升级为具备两套互补评测体系的质量运营平台：静态评估用固定考纲回答“通过了多少”，智能评估由 OpenClaw 模拟真实用户回答“实际体验中有什么问题”。此前已经完成的 v0.9 探索式评测和智能评估 v1.0 功能里程碑在本次发布中正式统一到项目 SemVer。
+
+## 二、核心能力
+
+- **静态评估**：对象、场景、规则、Run、实时 WebSocket、报告与同版本对比。
+- **周期 Campaign**：耐久调度、child Run 身份、重启恢复、探索会话、智能分析和周期对比。
+- **智能评估**：OpenClaw 规划、人工审批、虚拟用户会话、体验判定、结构化发现报告和 Markdown 导出。
+- **模型配置中心**：统一管理调用协议、用途能力、模态和分析/judge 默认岗位。
+- **管理后台**：keep-alive 标签页、统一 Drawer/页壳/反馈规范、状态感知轮询和完整快照读取。
+- **双线部署**：t480 开发线与 volcengine-102 正式线；正式发布包含数据备份、Alembic 迁移、不可变镜像和鉴权 API 冒烟。
+
+## 三、架构基线
+
+- 数据库是 Campaign、child Run 和耐久智能作业的状态权威；TaskRegistry 只保存进程内句柄。
+- `CampaignRuntime` 对外只暴露 `start`、`cancel`、`recover`、`shutdown`。
+- `CampaignReadModel` 统一列表、详情、报告、时间线、分析、对比和导出 projection。
+- 智能分析与周期对比共享耐久作业 owner；queued 条件认领并有限恢复，遗留 generating 不自动重放。
+- Campaign 与 Intelligent Evaluation 保持独立状态机；拒绝仅因 SQL 形状相似建立跨领域条件写入模块。
+
+## 四、质量基线
+
+- 后端：744 项测试通过。
+- 前端：15 项测试通过，TypeScript 检查与生产构建通过。
+- 数据库：Alembic upgrade/downgrade 往返通过，head 为 `d4e7f9a1b2c3`。
+- 发布检查：版本一致性、相关 Ruff、迁移演练、健康检查与关键 API 冒烟通过。
+
+## 五、兼容性与配置
+
+- 项目版本单一数据源从 `0.8.0` 修正为 `1.0.0`，由 `scripts/sync_version.py` 同步前端包文件。
+- 不改变现有 HTTP 路径、响应字段、SQLite 数据卷、API Key 或 OpenClaw 配置格式。
+- 升级时容器入口自动执行 Alembic；正式发布前仍必须备份数据 volume。
+- 当前部署假设为单进程 FastAPI + SQLite；切换多 worker 前需复审条件认领和并发写入边界。
+
+## 六、版本说明
+
+仓库早期存在一个名为 `V1.1` 的文档，它创建时实际代码版本是 `0.2.0-dev`，属于原型阶段编号。自本发布起，项目版本以 `pyproject.toml`、Git 标签和健康接口报告的 SemVer 为准。

docs/release-notes-v1.1.md

@@ -1,8 +1,10 @@
-# AgentEvalTool V1.1 版本发布说明
+# 历史归档：AgentEvalTool V1.1 版本说明
 
-**版本**: v1.1  
-**日期**: 2026-07-10  
-**状态**: 已发布  
+> **编号说明**：本文创建于 2026-07-16，当时代码包版本实际为 `0.2.0-dev`。这里的“V1.1”属于早期原型文档编号，不是当前项目 SemVer，也不晚于 2026-08-11 发布的 `v1.0.0`。当前发布说明见 [release-notes-v1.0.md](release-notes-v1.0.md)。
+
+**版本**: v1.1
+**日期**: 2026-07-10
+**状态**: 历史编号归档
 **作者**: AgentEval Team
 
 ---

frontend/web/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "agenteval-web",
-  "version": "0.8.0",
+  "version": "1.0.0",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "agenteval-web",
-      "version": "0.8.0",
+      "version": "1.0.0",
       "dependencies": {
         "@ant-design/charts": "^2.6.7",
         "@ant-design/icons": "^6.3.2",

frontend/web/package.json

@@ -1,6 +1,6 @@
 {
   "name": "agenteval-web",
-  "version": "0.8.0",
+  "version": "1.0.0",
   "private": true,
   "type": "module",
   "scripts": {

frontend/web/src/api.ts

@@ -471,7 +471,7 @@ export interface CampaignTimelineEntry {
   started_at: string | null
 }
 
-export type CampaignAnalysisStatus = 'none' | 'generating' | 'completed' | 'failed'
+export type CampaignAnalysisStatus = 'none' | 'queued' | 'generating' | 'completed' | 'failed'
 
 export interface CampaignAnalysisProblem {
   severity: string

frontend/web/src/hooks/useCampaignReport.test.tsx

@@ -0,0 +1,153 @@
+import { act, renderHook, waitFor } from '@testing-library/react'
+import { afterEach, describe, expect, it, vi } from 'vitest'
+import type { CampaignListItem } from '../api'
+import {
+  type CampaignReadAdapter,
+  type CampaignReportSnapshot,
+  useCampaignReport,
+} from './useCampaignReport'
+
+const campaign = { id: 'campaign-1', status: 'running' } as CampaignListItem
+const terminalCampaign = { ...campaign, status: 'completed' } as CampaignListItem
+const snapshot = {
+  report: { campaign_id: 'campaign-1', status: 'running' },
+  runs: [{ id: 'run-1', campaign_id: 'campaign-1' }],
+  timeline: [{ run_id: 'run-1' }],
+  analysis: { status: 'none' },
+  comparison: { status: 'none' },
+} as CampaignReportSnapshot
+
+function deferred<T>() {
+  let resolve!: (value: T) => void
+  const promise = new Promise<T>((resolvePromise) => { resolve = resolvePromise })
+  return { promise, resolve }
+}
+
+function createAdapter(overrides: Partial<CampaignReadAdapter> = {}): CampaignReadAdapter {
+  return {
+    list: vi.fn().mockResolvedValue([]),
+    report: vi.fn().mockResolvedValue(snapshot),
+    timeline: vi.fn().mockResolvedValue([]),
+    generateAnalysis: vi.fn().mockResolvedValue(undefined),
+    generateComparison: vi.fn().mockResolvedValue(undefined),
+    ...overrides,
+  }
+}
+
+afterEach(() => {
+  vi.useRealTimers()
+})
+
+describe('useCampaignReport', () => {
+  it('loads complete list and report snapshots', async () => {
+    const adapter = createAdapter({
+      list: vi.fn().mockResolvedValue([campaign]),
+      report: vi.fn().mockResolvedValue(snapshot),
+    })
+    const { result } = renderHook(() => useCampaignReport('campaign-1', true, adapter))
+
+    await waitFor(() => expect(result.current.report.value).toBe(snapshot))
+
+    expect(result.current.list.value).toEqual([campaign])
+    expect(result.current.list.phase).toBe('ready')
+    expect(result.current.report.phase).toBe('ready')
+  })
+
+  it('retains the last complete snapshot when a silent refresh fails', async () => {
+    const adapter = createAdapter({
+      list: vi.fn().mockResolvedValue([campaign]),
+      report: vi.fn()
+        .mockResolvedValueOnce(snapshot)
+        .mockRejectedValueOnce(new Error('network error')),
+    })
+    const { result } = renderHook(() => useCampaignReport('campaign-1', true, adapter))
+    await waitFor(() => expect(result.current.report.value).toBe(snapshot))
+
+    await act(async () => { await result.current.reloadReport() })
+
+    expect(result.current.report.phase).toBe('ready')
+    expect(result.current.report.value).toBe(snapshot)
+    expect(result.current.report.error).toBeNull()
+  })
+
+  it('ignores a late report response for the previous campaign', async () => {
+    const first = deferred<CampaignReportSnapshot>()
+    const second = deferred<CampaignReportSnapshot>()
+    const secondSnapshot = {
+      ...snapshot,
+      report: { ...snapshot.report, campaign_id: 'campaign-2' },
+    } as CampaignReportSnapshot
+    const adapter = createAdapter({
+      list: vi.fn().mockResolvedValue([]),
+      report: vi.fn((id: string) => (id === 'campaign-1' ? first.promise : second.promise)),
+    })
+    const { result, rerender } = renderHook(
+      ({ selectedId }) => useCampaignReport(selectedId, true, adapter),
+      { initialProps: { selectedId: 'campaign-1' as string | null } },
+    )
+
+    rerender({ selectedId: 'campaign-2' })
+    expect(result.current.report.value).toBeNull()
+
+    await act(async () => { second.resolve(secondSnapshot) })
+    expect(result.current.report.value?.report.campaign_id).toBe('campaign-2')
+
+    await act(async () => { first.resolve(snapshot) })
+    expect(result.current.report.value?.report.campaign_id).toBe('campaign-2')
+  })
+
+  it('polls active lists and stops after a terminal snapshot', async () => {
+    vi.useFakeTimers()
+    const adapter = createAdapter({
+      list: vi.fn()
+        .mockResolvedValueOnce([campaign])
+        .mockResolvedValue([terminalCampaign]),
+      report: vi.fn().mockResolvedValue({
+        ...snapshot,
+        report: { ...snapshot.report, status: 'completed' },
+      }),
+    })
+    renderHook(() => useCampaignReport(null, true, adapter))
+    await act(async () => { await Promise.resolve() })
+
+    await act(async () => { await vi.advanceTimersByTimeAsync(5000) })
+    await act(async () => { await vi.advanceTimersByTimeAsync(10000) })
+
+    expect(adapter.list).toHaveBeenCalledTimes(2)
+  })
+
+  it('refreshes the complete snapshot after analysis and comparison mutations', async () => {
+    const refreshed = {
+      ...snapshot,
+      analysis: { status: 'queued' },
+      comparison: { ...snapshot.comparison, status: 'queued' },
+    } as CampaignReportSnapshot
+    const adapter = createAdapter({
+      list: vi.fn().mockResolvedValue([campaign]),
+      report: vi.fn().mockResolvedValueOnce(snapshot).mockResolvedValue(refreshed),
+    })
+    const { result } = renderHook(() => useCampaignReport('campaign-1', true, adapter))
+    await waitFor(() => expect(result.current.report.value).toBe(snapshot))
+
+    await act(async () => { await result.current.generateAnalysis() })
+    expect(adapter.generateAnalysis).toHaveBeenCalledWith('campaign-1')
+    expect(result.current.report.value).toBe(refreshed)
+
+    await act(async () => { await result.current.generateComparison('campaign-0') })
+    expect(adapter.generateComparison).toHaveBeenCalledWith('campaign-1', 'campaign-0')
+    expect(adapter.report).toHaveBeenCalledTimes(3)
+  })
+
+  it('owns expanded timeline loading', async () => {
+    const entries = [{ run_id: 'run-2' }] as CampaignReportSnapshot['timeline']
+    const adapter = createAdapter({ timeline: vi.fn().mockResolvedValue(entries) })
+    const { result } = renderHook(() => useCampaignReport(null, true, adapter))
+
+    act(() => { result.current.setTimelineExpanded('campaign-1', true) })
+    await waitFor(() => expect(result.current.timelines['campaign-1']).toBe(entries))
+    expect(result.current.expandedIds).toEqual(['campaign-1'])
+
+    act(() => { result.current.setTimelineExpanded('campaign-1', false) })
+    expect(result.current.expandedIds).toEqual([])
+  })
+})

frontend/web/src/hooks/useCampaignReport.ts

@@ -1,83 +1,278 @@
-import { useState, useCallback, useEffect, type Dispatch, type SetStateAction } from 'react'
-import { campaignsApi, runsApi, type CampaignReport, type Run, type CampaignTimelineEntry, type CampaignAnalysis, type CampaignComparison } from '../api'
+import { useCallback, useEffect, useLayoutEffect, useReducer, useRef, useState } from 'react'
+import {
+  campaignsApi,
+  runsApi,
+  type CampaignAnalysis,
+  type CampaignAnalysisStatus,
+  type CampaignComparison,
+  type CampaignListItem,
+  type CampaignReport,
+  type CampaignTimelineEntry,
+  type Run,
+} from '../api'
+import { usePolling } from './usePolling'
 
-interface CampaignReportData {
-  report: CampaignReport | null
+type ReadPhase = 'idle' | 'loading' | 'refreshing' | 'ready' | 'error'
+
+interface ReadSlot<T> {
+  phase: ReadPhase
+  value: T
+  error: string | null
+}
+
+export interface CampaignReportSnapshot {
+  report: CampaignReport
   runs: Run[]
   timeline: CampaignTimelineEntry[]
-  analysis: CampaignAnalysis | null
-  comparison: CampaignComparison | null
-  loading: boolean
+  analysis: CampaignAnalysis
+  comparison: CampaignComparison
 }
 
-interface UseCampaignReportResult extends CampaignReportData {
-  refetch: (silent?: boolean) => Promise<void>
-  setAnalysis: Dispatch<SetStateAction<CampaignAnalysis | null>>
-  setComparison: Dispatch<SetStateAction<CampaignComparison | null>>
+interface CampaignReadState {
+  list: ReadSlot<CampaignListItem[]>
+  report: ReadSlot<CampaignReportSnapshot | null> & {
+    selectedId: string | null
+    requestId: number
+  }
 }
 
-export function useCampaignReport(campaignId: string | null): UseCampaignReportResult {
-  const [data, setData] = useState<CampaignReportData>({
-    report: null,
-    runs: [],
-    timeline: [],
-    analysis: null,
-    comparison: null,
-    loading: false,
-  })
+type CampaignReadAction =
+  | { type: 'list_requested'; silent?: boolean }
+  | { type: 'list_succeeded'; value: CampaignListItem[] }
+  | { type: 'list_failed'; error: string }
+  | { type: 'report_cleared'; requestId: number }
+  | { type: 'report_requested'; id: string; requestId: number; silent?: boolean }
+  | { type: 'report_succeeded'; id: string; requestId: number; value: CampaignReportSnapshot }
+  | { type: 'report_failed'; id: string; requestId: number; error: string }
 
-  const refetch = useCallback(async (silent = false) => {
-    if (!campaignId) return
-    if (!silent) {
-      setData({
-        report: null,
-        runs: [],
-        timeline: [],
-        analysis: null,
-        comparison: null,
-        loading: true,
-      })
+export interface CampaignReadAdapter {
+  list: () => Promise<CampaignListItem[]>
+  report: (campaignId: string) => Promise<CampaignReportSnapshot>
+  timeline: (campaignId: string) => Promise<CampaignTimelineEntry[]>
+  generateAnalysis: (campaignId: string) => Promise<void>
+  generateComparison: (campaignId: string, baselineCampaignId?: string) => Promise<void>
+}
+
+export const campaignReadAdapter: CampaignReadAdapter = {
+  list: () => campaignsApi.list().then((response) => response.data),
+  report: async (campaignId) => {
+    const [report, runs, timeline, analysis, comparison] = await Promise.all([
+      campaignsApi.report(campaignId),
+      runsApi.list(),
+      campaignsApi.timeline(campaignId),
+      campaignsApi.getAnalysis(campaignId),
+      campaignsApi.getComparison(campaignId),
+    ])
+    return {
+      report: report.data,
+      runs: runs.data.filter((run) => run.campaign_id === campaignId),
+      timeline: timeline.data.entries,
+      analysis: analysis.data,
+      comparison: comparison.data,
     }
+  },
+  timeline: (campaignId) => campaignsApi.timeline(campaignId).then((response) => response.data.entries),
+  generateAnalysis: (campaignId) => campaignsApi.generateAnalysis(campaignId).then(() => undefined),
+  generateComparison: (campaignId, baselineCampaignId) => (
+    campaignsApi.generateComparison(campaignId, baselineCampaignId).then(() => undefined)
+  ),
+}
+
+const initialState: CampaignReadState = {
+  list: { phase: 'idle', value: [], error: null },
+  report: {
+    phase: 'idle', value: null, error: null, selectedId: null, requestId: 0,
+  },
+}
+
+function requestSlot<T>(slot: ReadSlot<T>, silent: boolean | undefined): ReadSlot<T> {
+  return {
+    ...slot,
+    phase: silent && slot.phase === 'ready' ? 'refreshing' : 'loading',
+    error: null,
+  }
+}
+
+function reducer(state: CampaignReadState, action: CampaignReadAction): CampaignReadState {
+  switch (action.type) {
+    case 'list_requested':
+      return { ...state, list: requestSlot(state.list, action.silent) }
+    case 'list_succeeded':
+      return { ...state, list: { phase: 'ready', value: action.value, error: null } }
+    case 'list_failed':
+      return {
+        ...state,
+        list: state.list.value.length > 0
+          ? { ...state.list, phase: 'ready', error: null }
+          : { ...state.list, phase: 'error', error: action.error },
+      }
+    case 'report_cleared':
+      return {
+        ...state,
+        report: {
+          phase: 'idle', value: null, error: null, selectedId: null, requestId: action.requestId,
+        },
+      }
+    case 'report_requested': {
+      const sameSelection = state.report.selectedId === action.id
+      const current = sameSelection
+        ? state.report
+        : { ...state.report, value: null, selectedId: action.id }
+      return {
+        ...state,
+        report: {
+          ...requestSlot(current, action.silent),
+          selectedId: action.id,
+          requestId: action.requestId,
+        },
+      }
+    }
+    case 'report_succeeded':
+      if (state.report.selectedId !== action.id || state.report.requestId !== action.requestId) return state
+      return {
+        ...state,
+        report: {
+          phase: 'ready', value: action.value, error: null,
+          selectedId: action.id, requestId: action.requestId,
+        },
+      }
+    case 'report_failed':
+      if (state.report.selectedId !== action.id || state.report.requestId !== action.requestId) return state
+      return {
+        ...state,
+        report: state.report.value
+          ? { ...state.report, phase: 'ready', error: null }
+          : { ...state.report, phase: 'error', error: action.error },
+      }
+  }
+}
+
+function errorMessage(error: unknown): string {
+  return error instanceof Error ? error.message : '读取评估活动失败'
+}
+
+const isCampaignActive = (status: CampaignListItem['status'] | undefined) => (
+  status === 'planned' || status === 'running'
+)
+
+const isIntelligenceJobActive = (status: CampaignAnalysisStatus | undefined) => (
+  status === 'queued' || status === 'generating'
+)
+
+export function useCampaignReport(
+  selectedId: string | null,
+  enabled = true,
+  adapter: CampaignReadAdapter = campaignReadAdapter,
+) {
+  const [state, dispatch] = useReducer(reducer, initialState)
+  const [expandedIds, setExpandedIds] = useState<string[]>([])
+  const [timelines, setTimelines] = useState<Record<string, CampaignTimelineEntry[]>>({})
+  const [analysisBusy, setAnalysisBusy] = useState(false)
+  const [comparisonBusy, setComparisonBusy] = useState(false)
+  const reportRequestId = useRef(0)
+  const selectedIdRef = useRef(selectedId)
+  selectedIdRef.current = selectedId
+
+  const loadList = useCallback(async (silent = false) => {
+    dispatch({ type: 'list_requested', silent })
     try {
-      const [rep, runs, tl, ana, cmp] = await Promise.all([
-        campaignsApi.report(campaignId),
-        runsApi.list(),
-        campaignsApi.timeline(campaignId),
-        campaignsApi.getAnalysis(campaignId),
-        campaignsApi.getComparison(campaignId),
-      ])
-      setData({
-        report: rep.data,
-        runs: runs.data.filter((r) => r.campaign_id === campaignId),
-        timeline: tl.data.entries,
-        analysis: ana.data,
-        comparison: cmp.data,
-        loading: false,
-      })
-    } catch {
-      setData((prev) => ({ ...prev, loading: false }))
+      dispatch({ type: 'list_succeeded', value: await adapter.list() })
+    } catch (error) {
+      dispatch({ type: 'list_failed', error: errorMessage(error) })
     }
-  }, [campaignId])
+  }, [adapter])
 
-  useEffect(() => {
-    if (campaignId) {
-      void refetch(false)
+  const loadReport = useCallback(async (campaignId: string, silent = false) => {
+    const requestId = ++reportRequestId.current
+    dispatch({ type: 'report_requested', id: campaignId, requestId, silent })
+    try {
+      const value = await adapter.report(campaignId)
+      dispatch({ type: 'report_succeeded', id: campaignId, requestId, value })
+    } catch (error) {
+      dispatch({ type: 'report_failed', id: campaignId, requestId, error: errorMessage(error) })
     }
-  }, [campaignId, refetch])
+  }, [adapter])
 
-  const setAnalysis: Dispatch<SetStateAction<CampaignAnalysis | null>> = (value) => {
-    setData((prev) => ({
-      ...prev,
-      analysis: typeof value === 'function' ? value(prev.analysis) : value,
-    }))
+  const loadTimeline = useCallback(async (campaignId: string) => {
+    const timeline = await adapter.timeline(campaignId)
+    setTimelines((current) => ({ ...current, [campaignId]: timeline }))
+  }, [adapter])
+
+  const setTimelineExpanded = useCallback((campaignId: string, expanded: boolean) => {
+    setExpandedIds((current) => (
+      expanded
+        ? current.includes(campaignId) ? current : [...current, campaignId]
+        : current.filter((id) => id !== campaignId)
+    ))
+    if (expanded) void loadTimeline(campaignId)
+  }, [loadTimeline])
+
+  const generateAnalysis = useCallback(async () => {
+    const campaignId = selectedIdRef.current
+    if (!campaignId) return
+    setAnalysisBusy(true)
+    try {
+      await adapter.generateAnalysis(campaignId)
+      if (selectedIdRef.current === campaignId) await loadReport(campaignId, true)
+    } finally {
+      setAnalysisBusy(false)
+    }
+  }, [adapter, loadReport])
+
+  const generateComparison = useCallback(async (baselineCampaignId?: string) => {
+    const campaignId = selectedIdRef.current
+    if (!campaignId) return
+    setComparisonBusy(true)
+    try {
+      await adapter.generateComparison(campaignId, baselineCampaignId)
+      if (selectedIdRef.current === campaignId) await loadReport(campaignId, true)
+    } finally {
+      setComparisonBusy(false)
+    }
+  }, [adapter, loadReport])
+
+  useEffect(() => { void loadList() }, [loadList])
+
+  useLayoutEffect(() => {
+    if (selectedId == null) {
+      dispatch({ type: 'report_cleared', requestId: ++reportRequestId.current })
+      return
+    }
+    void loadReport(selectedId)
+  }, [loadReport, selectedId])
+
+  const listActive = state.list.value.some((campaign) => isCampaignActive(campaign.status))
+  const snapshot = state.report.value
+  const reportActive = isCampaignActive(snapshot?.report.status)
+    || isIntelligenceJobActive(snapshot?.analysis.status)
+    || isIntelligenceJobActive(snapshot?.comparison.status)
+  const activeExpandedIds = expandedIds.filter(
+    (id) => state.list.value.some((campaign) => campaign.id === id && isCampaignActive(campaign.status)),
+  )
+
+  usePolling(() => { void loadList(true) }, 5000, enabled && listActive)
+  usePolling(
+    () => { if (selectedId) void loadReport(selectedId, true) },
+    5000,
+    enabled && selectedId != null && reportActive,
+  )
+  usePolling(
+    () => { activeExpandedIds.forEach((id) => { void loadTimeline(id) }) },
+    5000,
+    enabled && activeExpandedIds.length > 0,
+  )
+
+  return {
+    list: state.list,
+    report: state.report,
+    reloadList: () => loadList(true),
+    reloadReport: () => (selectedId ? loadReport(selectedId, true) : Promise.resolve()),
+    expandedIds,
+    timelines,
+    setTimelineExpanded,
+    generateAnalysis,
+    generateComparison,
+    analysisBusy,
+    comparisonBusy,
   }
-
-  const setComparison: Dispatch<SetStateAction<CampaignComparison | null>> = (value) => {
-    setData((prev) => ({
-      ...prev,
-      comparison: typeof value === 'function' ? value(prev.comparison) : value,
-    }))
-  }
-
-  return { ...data, refetch, setAnalysis, setComparison }
 }

frontend/web/src/pages/Campaigns.tsx

@@ -17,7 +17,7 @@ import StatCard from '../components/StatCard'
 import {
   campaignsApi, targetsApi, scenariosApi, modelConfigsApi,
   type CampaignListItem, type Target, type Scenario, type Run,
-  type CampaignTimelineEntry, type ModelConfig,
+  type ModelConfig,
 } from '../api'
 import { passRateColor } from '../utils/colors'
 import { shortDateTime, toDate } from '../utils/date'
@@ -27,7 +27,6 @@ import CampaignRunTimeline from '../components/CampaignRunTimeline'
 import PeriodComparisonSection from '../components/PeriodComparisonSection'
 import ExplorationSection from '../components/ExplorationSection'
 import { useResource } from '../hooks/useResource'
-import { usePolling } from '../hooks/usePolling'
 import { useCampaignReport } from '../hooks/useCampaignReport'
 import { useTabStore } from '../stores/tabStore'
 import { colors, statusColors, statusLabels, triggerColors, triggerLabels } from '../tokens'
@@ -58,8 +57,6 @@ function scaleFor(realtime: boolean, windowSeconds: number, targetValue: number,
   return realtime ? 1 : deriveTimeScale(windowSeconds, targetValue * targetUnit)
 }
 
-const POLL_INTERVAL_MS = 5000
-
 const isActiveStatus = (status: string) => status === 'planned' || status === 'running'
 
 /** How far an active campaign's window has progressed, in window seconds. */
@@ -133,8 +130,7 @@ interface PlanFormEntry {
   count?: number
 }
 
-interface CampaignsListsData {
-  campaigns: CampaignListItem[]
+interface CampaignAuxiliaryData {
   targets: Target[]
   scenarios: Scenario[]
   modelConfigs: ModelConfig[]
@@ -156,23 +152,17 @@ export default function CampaignsPage() {
 
   const [reportOpen, setReportOpen] = useState(false)
   const [reportCampaignId, setReportCampaignId] = useState<string | null>(null)
-  const [analysisBusy, setAnalysisBusy] = useState(false)
-
-  const [expandedIds, setExpandedIds] = useState<string[]>([])
-  const [timelines, setTimelines] = useState<Record<string, CampaignTimelineEntry[]>>({})
-
   const targetName = (id: string) => targets.find((t) => t.id === id)?.name ?? id.slice(0, 8)
 
-  const { data, loading, reload } = useResource<CampaignsListsData>(
+  const { data } = useResource<CampaignAuxiliaryData>(
     async () => {
-      const [c, t, s, m] = await Promise.all([
-        campaignsApi.list(), targetsApi.list(), scenariosApi.list(), modelConfigsApi.list(),
+      const [t, s, m] = await Promise.all([
+        targetsApi.list(), scenariosApi.list(), modelConfigsApi.list(),
       ])
-      return { campaigns: c.data, targets: t.data, scenarios: s.data, modelConfigs: m.data }
+      return { targets: t.data, scenarios: s.data, modelConfigs: m.data }
     },
     { tabPath: '/campaigns' },
   )
-  const campaigns = data?.campaigns ?? []
   const targets = data?.targets ?? []
   const scenarios = data?.scenarios ?? []
   const chatConfigs = (data?.modelConfigs ?? []).filter((m) => m.enabled && m.capability === 'chat')
@@ -180,9 +170,28 @@ export default function CampaignsPage() {
   const scenarioNames = Object.fromEntries(scenarios.map((s) => [s.id, s.name]))
 
   const {
-    report, runs: reportRuns, timeline: reportTimeline, analysis, comparison, loading: reportLoading,
-    refetch: fetchReport, setAnalysis, setComparison,
-  } = useCampaignReport(reportOpen ? reportCampaignId : null)
+    list: campaignList,
+    report: reportSlot,
+    reloadList,
+    expandedIds,
+    timelines,
+    setTimelineExpanded,
+    generateAnalysis,
+    generateComparison,
+    analysisBusy,
+  } = useCampaignReport(
+    reportOpen ? reportCampaignId : null,
+    activeKey === '/campaigns',
+  )
+  const campaigns = campaignList.value
+  const loading = campaignList.phase === 'loading'
+  const reportSnapshot = reportSlot.value
+  const report = reportSnapshot?.report ?? null
+  const reportRuns = reportSnapshot?.runs ?? []
+  const reportTimeline = reportSnapshot?.timeline ?? []
+  const analysis = reportSnapshot?.analysis ?? null
+  const comparison = reportSnapshot?.comparison ?? null
+  const reportLoading = reportSlot.phase === 'loading'
 
   const wPlan = (Form.useWatch('plan', form) as PlanFormEntry[] | undefined) ?? []
   const planMarkers: TimelineMarker[] = wPlan
@@ -200,15 +209,6 @@ export default function CampaignsPage() {
       }
     })
 
-  // Poll the list while this tab is active and a campaign is still working —
-  // compressed dev-line campaigns change fast. Stop once all are terminal.
-  const hasActiveCampaign = campaigns.some((c) => isActiveStatus(c.status))
-  usePolling(
-    () => void reload(true),
-    POLL_INTERVAL_MS,
-    activeKey === '/campaigns' && hasActiveCampaign,
-  )
-
   const openCreate = () => {
     form.setFieldsValue({
       name: '', target_id: undefined, window_seconds: 24 * 3600,
@@ -256,7 +256,7 @@ export default function CampaignsPage() {
       })
       message.success('评估活动已创建并开始调度')
       setCreateOpen(false)
-      reload()
+      void reloadList()
     } finally {
       setSubmitting(false)
     }
@@ -265,17 +265,11 @@ export default function CampaignsPage() {
   const cancelCampaign = async (id: string) => {
     await campaignsApi.cancel(id)
     message.success('活动已取消')
-    reload()
-  }
-
-  const fetchTimeline = async (campaignId: string) => {
-    const res = await campaignsApi.timeline(campaignId)
-    setTimelines((prev) => ({ ...prev, [campaignId]: res.data.entries }))
+    void reloadList()
   }
 
   const onExpandRow = (expanded: boolean, record: CampaignListItem) => {
-    setExpandedIds((prev) => (expanded ? [...prev, record.id] : prev.filter((x) => x !== record.id)))
-    if (expanded) void fetchTimeline(record.id)
+    setTimelineExpanded(record.id, expanded)
   }
 
   const openReport = (campaign: CampaignListItem) => {
@@ -283,66 +277,6 @@ export default function CampaignsPage() {
     setReportCampaignId(campaign.id)
   }
 
-  // Keep the open report drawer live while its campaign is still running.
-  const reportCampaignActive = campaigns.some(
-    (c) => c.id === reportCampaignId && isActiveStatus(c.status),
-  )
-  usePolling(
-    () => { if (reportCampaignId) void fetchReport(true) },
-    POLL_INTERVAL_MS,
-    activeKey === '/campaigns' && reportOpen && !!reportCampaignId && reportCampaignActive,
-  )
-
-  const generateAnalysis = async () => {
-    if (!reportCampaignId) return
-    setAnalysisBusy(true)
-    try {
-      await campaignsApi.generateAnalysis(reportCampaignId)
-      const res = await campaignsApi.getAnalysis(reportCampaignId)
-      setAnalysis(res.data)
-    } finally {
-      setAnalysisBusy(false)
-    }
-  }
-
-  // 分析后台任务进行时轮询，直到进入 completed/failed 终态。
-  usePolling(
-    () => {
-      if (!reportCampaignId) return
-      void campaignsApi.getAnalysis(reportCampaignId).then((res) => setAnalysis(res.data))
-    },
-    POLL_INTERVAL_MS,
-    activeKey === '/campaigns' && reportOpen && !!reportCampaignId && analysis?.status === 'generating',
-  )
-
-  const generateComparison = async (baselineCampaignId?: string) => {
-    if (!reportCampaignId) return
-    await campaignsApi.generateComparison(reportCampaignId, baselineCampaignId)
-    const res = await campaignsApi.getComparison(reportCampaignId)
-    setComparison(res.data)
-  }
-
-  // 对比生成中同样轮询，直到 completed/failed。
-  usePolling(
-    () => {
-      if (!reportCampaignId) return
-      void campaignsApi.getComparison(reportCampaignId).then((res) => setComparison(res.data))
-    },
-    POLL_INTERVAL_MS,
-    activeKey === '/campaigns' && reportOpen && !!reportCampaignId && comparison?.status === 'generating',
-  )
-
-  // Grow the expanded timeline of any still-running campaign as new child Runs
-  // spawn. Completed/cancelled campaigns are fetched once on expand.
-  const activeExpandedIds = expandedIds.filter(
-    (id) => campaigns.some((c) => c.id === id && isActiveStatus(c.status)),
-  )
-  usePolling(
-    () => { activeExpandedIds.forEach((id) => void fetchTimeline(id)) },
-    POLL_INTERVAL_MS,
-    activeKey === '/campaigns' && activeExpandedIds.length > 0,
-  )
-
   const columns = [
     { title: '名称', dataIndex: 'name', key: 'name' },
     { title: '评测对象', key: 'target', render: (_: unknown, c: CampaignListItem) => targetName(c.target_id) },
@@ -688,7 +622,7 @@ export default function CampaignsPage() {
       fullHeight
       extra={
         <Space>
-          <Button icon={<ReloadOutlined />} onClick={() => reload()} />
+          <Button icon={<ReloadOutlined />} onClick={() => void reloadList()} />
           <Button type="primary" icon={<PlusOutlined />} onClick={openCreate}>新建活动</Button>
         </Space>
       }

migrations/versions/d4e7f9a1b2c3_add_intelligence_job_recovery_attempts.py

@@ -0,0 +1,46 @@
+"""add intelligence job recovery attempts
+
+Revision ID: d4e7f9a1b2c3
+Revises: c2f4a6b8d0e1
+Create Date: 2026-08-11
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+revision: str = "d4e7f9a1b2c3"
+down_revision: Union[str, Sequence[str], None] = "c2f4a6b8d0e1"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    inspector = sa.inspect(op.get_bind())
+    analysis_columns = {column["name"] for column in inspector.get_columns("campaign_analyses")}
+    if "recovery_attempts" not in analysis_columns:
+        op.add_column(
+            "campaign_analyses",
+            sa.Column("recovery_attempts", sa.Integer(), nullable=False, server_default="0"),
+        )
+    comparison_columns = {
+        column["name"] for column in inspector.get_columns("campaign_period_comparisons")
+    }
+    if "recovery_attempts" not in comparison_columns:
+        op.add_column(
+            "campaign_period_comparisons",
+            sa.Column("recovery_attempts", sa.Integer(), nullable=False, server_default="0"),
+        )
+
+
+def downgrade() -> None:
+    inspector = sa.inspect(op.get_bind())
+    comparison_columns = {
+        column["name"] for column in inspector.get_columns("campaign_period_comparisons")
+    }
+    if "recovery_attempts" in comparison_columns:
+        op.drop_column("campaign_period_comparisons", "recovery_attempts")
+    analysis_columns = {column["name"] for column in inspector.get_columns("campaign_analyses")}
+    if "recovery_attempts" in analysis_columns:
+        op.drop_column("campaign_analyses", "recovery_attempts")

migrations/versions/e6c3d1a2f809_add_campaigns.py

@@ -4,6 +4,7 @@ Revision ID: e6c3d1a2f809
 Revises: d5b8c2e4f617
 Create Date: 2026-07-29
 """
+
 from typing import Sequence, Union
 
 import sqlalchemy as sa
@@ -35,16 +36,12 @@ def upgrade() -> None:
         sa.PrimaryKeyConstraint("id"),
     )
     with op.batch_alter_table("eval_runs") as batch_op:
-        batch_op.add_column(
-            sa.Column("campaign_id", sqlmodel.sql.sqltypes.AutoString(), nullable=True)
-        )
-        batch_op.create_foreign_key(
-            "fk_eval_runs_campaign_id", "campaigns", ["campaign_id"], ["id"]
-        )
+        batch_op.add_column(sa.Column("campaign_id", sqlmodel.sql.sqltypes.AutoString(), nullable=True))
+        batch_op.create_foreign_key("fk_eval_runs_campaign_id", "campaigns", ["campaign_id"], ["id"])
 
 
 def downgrade() -> None:
+    """Remove Campaign storage without relying on SQLite foreign-key names."""
     with op.batch_alter_table("eval_runs") as batch_op:
-        batch_op.drop_constraint("fk_eval_runs_campaign_id", type_="foreignkey")
         batch_op.drop_column("campaign_id")
     op.drop_table("campaigns")

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "agenteval"
-version = "0.8.0"
+version = "1.0.0"
 description = "智能体质量评估工具集平台"
 readme = "README.md"
 requires-python = ">=3.10"

scripts/deploy-volcengine-102.sh

@@ -10,9 +10,9 @@
 #   AGENTEVAL_PROD_BACKUP_DIR=/var/backups/agenteval
 #
 # Usage:
-#   scripts/deploy-volcengine-102.sh --tag 0.8.0-6248568
-#   scripts/deploy-volcengine-102.sh --dry-run --tag 0.8.0-6248568
-#   scripts/deploy-volcengine-102.sh --rollback 0.8.0-6248568
+#   scripts/deploy-volcengine-102.sh --tag 1.0.0-abcdef0
+#   scripts/deploy-volcengine-102.sh --dry-run --tag 1.0.0-abcdef0
+#   scripts/deploy-volcengine-102.sh --rollback 1.0.0-abcdef0
 
 set -euo pipefail
 

tests/integration/test_campaign_analysis_api.py

@@ -27,7 +27,7 @@ def seeded_db(db_session, monkeypatch):
     from agenteval.web.routers import campaigns as campaigns_module
 
     monkeypatch.setattr(app_module, "init_db", lambda: None)
-    monkeypatch.setattr(campaigns_module, "start_campaign", lambda *a, **k: None)
+    monkeypatch.setattr(campaigns_module.campaign_runtime, "start", lambda *a, **k: None)
 
     monkeypatch.setattr(db_module, "get_session", lambda: db_session)
     monkeypatch.setattr(repo_module, "get_session", lambda: db_session)

tests/integration/test_campaign_analysis_auto_trigger.py

@@ -7,7 +7,8 @@ skip silently. The analysis service itself is spied, not executed.
 
 import pytest
 from agenteval.evaluation import campaign_runner
-from agenteval.evaluation.campaign_runner import request_cancel, start_campaign
+from agenteval.evaluation.campaign_lifecycle import cancel_campaign
+from agenteval.evaluation.campaign_runner import CampaignRuntime
 from agenteval.models import (
     Campaign,
     CampaignPlanEntry,
@@ -20,7 +21,6 @@ from agenteval.models import (
     Scenario,
     TargetStatus,
 )
-from agenteval.storage.db import utc_now
 from agenteval.storage.repository import CampaignRepository, ScenarioRepository, TargetRepository
 
 from tests.unit.mock_channel import MockChannel
@@ -46,15 +46,23 @@ def seeded_db(db_session, monkeypatch):
     channel = MockChannel(reply_delay=0.0)
     monkeypatch.setattr(factory_module.ChannelFactory, "create", lambda target: channel)
 
-    TargetRepository(db_session).create(EvalTarget(
-        id="t-1", name="mock-target",
-        platform=PlatformType.AI_DIGITAL_EMPLOYEE, channel_type=ChannelType.TUTU_API,
-        channel_config={"base_url": "http://mock", "token": "x"}, status=TargetStatus.ACTIVE,
-    ))
-    ScenarioRepository(db_session).create(Scenario(
-        id="s-1", name="mock-scenario",
-        cases=[Case(id="c1", type=CaseType.SINGLE, messages=["hi"])],
-    ))
+    TargetRepository(db_session).create(
+        EvalTarget(
+            id="t-1",
+            name="mock-target",
+            platform=PlatformType.AI_DIGITAL_EMPLOYEE,
+            channel_type=ChannelType.TUTU_API,
+            channel_config={"base_url": "http://mock", "token": "x"},
+            status=TargetStatus.ACTIVE,
+        )
+    )
+    ScenarioRepository(db_session).create(
+        Scenario(
+            id="s-1",
+            name="mock-scenario",
+            cases=[Case(id="c1", type=CaseType.SINGLE, messages=["hi"])],
+        )
+    )
     return db_session
 
 
@@ -63,7 +71,8 @@ def analysis_spy(monkeypatch):
     """Spy the analysis seam: resolvable model, recorded enqueue calls."""
     calls: list[tuple[str, str]] = []
     monkeypatch.setattr(
-        campaign_runner, "enqueue_campaign_analysis",
+        campaign_runner,
+        "enqueue_campaign_analysis",
         lambda cid, *, triggered_by: calls.append((cid, triggered_by)),
     )
     monkeypatch.setattr(campaign_runner, "resolve_analysis_model", lambda campaign, session: object())
@@ -82,56 +91,60 @@ def _make_campaign(session, **overrides) -> Campaign:
     return CampaignRepository(session).create(Campaign(**payload))
 
 
-async def _await_task(campaign_id, timeout=5.0):
+@pytest.fixture()
+async def runtime(seeded_db):
+    value = CampaignRuntime(session_factory=lambda: seeded_db, tick_seconds=TICK)
+    yield value
+    await value.shutdown()
+
+
+async def _await_terminal(session, campaign_id, timeout=5.0):
     import asyncio
-    task = campaign_runner.campaign_registry.get(campaign_id)
-    if task is not None:
-        await asyncio.wait_for(task, timeout=timeout)
+
+    async with asyncio.timeout(timeout):
+        while CampaignRepository(session).get(campaign_id).status is CampaignStatus.RUNNING:
+            await asyncio.sleep(TICK)
 
 
-async def test_realtime_completion_auto_enqueues_analysis(seeded_db, analysis_spy):
+async def test_realtime_completion_auto_enqueues_analysis(seeded_db, runtime, analysis_spy):
     campaign = _make_campaign(seeded_db)
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    await _await_task(campaign.id)
+    assert runtime.start(campaign.id)
+    await _await_terminal(seeded_db, campaign.id)
 
     final = CampaignRepository(seeded_db).get(campaign.id)
     assert final.status == CampaignStatus.COMPLETED
     assert analysis_spy == [(campaign.id, "auto")]
 
 
-async def test_accelerated_completion_does_not_enqueue(seeded_db, analysis_spy):
+async def test_accelerated_completion_does_not_enqueue(seeded_db, runtime, analysis_spy):
     campaign = _make_campaign(seeded_db, time_scale=1000.0)  # 加速调试线
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    await _await_task(campaign.id)
+    assert runtime.start(campaign.id)
+    await _await_terminal(seeded_db, campaign.id)
 
     final = CampaignRepository(seeded_db).get(campaign.id)
     assert final.status == CampaignStatus.COMPLETED
     assert analysis_spy == []
 
 
-async def test_cancelled_campaign_does_not_enqueue(seeded_db, analysis_spy):
+async def test_cancelled_campaign_does_not_enqueue(seeded_db, runtime, analysis_spy):
     import asyncio
+
     campaign = _make_campaign(seeded_db, window_seconds=100)
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
+    assert runtime.start(campaign.id)
     await asyncio.sleep(0.05)
 
     repo = CampaignRepository(seeded_db)
-    current = repo.get(campaign.id)
-    current.status = CampaignStatus.CANCELLED
-    current.completed_at = utc_now()
-    repo.update(current)
-    request_cancel(campaign.id)
-    await _await_task(campaign.id)
+    cancel_campaign(seeded_db, campaign.id, stop=runtime.cancel)
 
     assert repo.get(campaign.id).status == CampaignStatus.CANCELLED
     assert analysis_spy == []
 
 
-async def test_missing_analysis_model_skips_silently(seeded_db, monkeypatch, analysis_spy):
+async def test_missing_analysis_model_skips_silently(seeded_db, runtime, monkeypatch, analysis_spy):
     monkeypatch.setattr(campaign_runner, "resolve_analysis_model", lambda campaign, session: None)
     campaign = _make_campaign(seeded_db)
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    await _await_task(campaign.id)
+    assert runtime.start(campaign.id)
+    await _await_terminal(seeded_db, campaign.id)
 
     final = CampaignRepository(seeded_db).get(campaign.id)
     assert final.status == CampaignStatus.COMPLETED  # 活动完成流程不受影响

tests/integration/test_campaign_comparison_api.py

@@ -32,7 +32,7 @@ def seeded_db(db_session, monkeypatch):
     from agenteval.web.routers import campaigns as campaigns_module
 
     monkeypatch.setattr(app_module, "init_db", lambda: None)
-    monkeypatch.setattr(campaigns_module, "start_campaign", lambda *a, **k: None)
+    monkeypatch.setattr(campaigns_module.campaign_runtime, "start", lambda *a, **k: None)
 
     monkeypatch.setattr(db_module, "get_session", lambda: db_session)
     monkeypatch.setattr(repo_module, "get_session", lambda: db_session)
@@ -309,8 +309,8 @@ async def test_post_comparison_auto_baseline_success(client, seeded_db, monkeypa
 
     monkeypatch.setattr(
         campaigns_module,
-        "start_campaign_comparison",
-        lambda cid, *, triggered_by, baseline_campaign_id=None: _complete_comparison_row(
+        "enqueue_campaign_comparison",
+        lambda cid, *, triggered_by, baseline_campaign_id, session=None: _complete_comparison_row(
             seeded_db, cid, baseline_campaign_id
         ),
     )
@@ -349,8 +349,8 @@ async def test_post_comparison_manual_baseline_across_fingerprints(client, seede
 
     monkeypatch.setattr(
         campaigns_module,
-        "start_campaign_comparison",
-        lambda cid, *, triggered_by, baseline_campaign_id=None: _complete_comparison_row(
+        "enqueue_campaign_comparison",
+        lambda cid, *, triggered_by, baseline_campaign_id, session=None: _complete_comparison_row(
             seeded_db, cid, baseline_campaign_id
         ),
     )
@@ -394,8 +394,8 @@ async def test_post_comparison_rerun_upserts_without_new_row(client, seeded_db,
 
     monkeypatch.setattr(
         campaigns_module,
-        "start_campaign_comparison",
-        lambda cid, *, triggered_by, baseline_campaign_id=None: _complete_comparison_row(
+        "enqueue_campaign_comparison",
+        lambda cid, *, triggered_by, baseline_campaign_id, session=None: _complete_comparison_row(
             seeded_db, cid, baseline_campaign_id
         ),
     )

tests/integration/test_campaign_comparison_auto_trigger.py

@@ -11,8 +11,8 @@ from types import SimpleNamespace
 
 import pytest
 from agenteval.evaluation import analysis as analysis_module
-from agenteval.evaluation import comparison as comparison_module
-from agenteval.evaluation.analysis import execute_campaign_analysis
+from agenteval.evaluation import intelligence_jobs
+from agenteval.evaluation.intelligence_jobs import execute_campaign_analysis_job
 from agenteval.models import Campaign, CampaignPlanEntry, CampaignStatus, EvalRun, RunStatus, RunSummary
 from agenteval.storage.db import CampaignAnalysisDB, utc_now
 from agenteval.storage.model_config_repository import ModelConfigRepository
@@ -75,21 +75,21 @@ def _seed_current(session, *, time_scale: float = 1.0, completed_at) -> None:
 def comparison_spy(monkeypatch):
     calls: list[tuple[str, str]] = []
 
-    def _spy(campaign_id, *, triggered_by, baseline_campaign_id=None):
+    def _spy(campaign_id, *, triggered_by, baseline_campaign_id, session=None):
         calls.append((campaign_id, triggered_by))
 
-    monkeypatch.setattr(comparison_module, "start_campaign_comparison", _spy)
+    monkeypatch.setattr(intelligence_jobs, "enqueue_campaign_comparison", _spy)
     return calls
 
 
-async def test_production_line_with_baseline_enqueues_comparison(db_session, monkeypatch, comparison_spy):
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
+async def test_production_line_with_baseline_enqueues_comparison(db_session, comparison_spy):
     _seed_config(db_session)
     _seed_baseline(db_session, T0)
     _seed_current(db_session, completed_at=T0 + timedelta(hours=2))
 
-    await execute_campaign_analysis(
+    await execute_campaign_analysis_job(
         "camp-cur", triggered_by="auto", chat_client=FakeChatClient(STAGE1, STAGE2),
+        session_factory=lambda: db_session,
     )
 
     analysis_row = db_session.exec(
@@ -100,32 +100,31 @@ async def test_production_line_with_baseline_enqueues_comparison(db_session, mon
 
 
 async def test_accelerated_line_does_not_enqueue(db_session, monkeypatch, comparison_spy):
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
     _seed_config(db_session)
     _seed_baseline(db_session, T0)
     _seed_current(db_session, time_scale=24.0, completed_at=T0 + timedelta(hours=2))
 
-    await execute_campaign_analysis(
+    await execute_campaign_analysis_job(
         "camp-cur", triggered_by="auto", chat_client=FakeChatClient(STAGE1, STAGE2),
+        session_factory=lambda: db_session,
     )
 
     assert comparison_spy == []
 
 
 async def test_no_auto_baseline_does_not_enqueue(db_session, monkeypatch, comparison_spy):
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
     _seed_config(db_session)
     _seed_current(db_session, completed_at=T0 + timedelta(hours=2))  # 无历史活动
 
-    await execute_campaign_analysis(
+    await execute_campaign_analysis_job(
         "camp-cur", triggered_by="auto", chat_client=FakeChatClient(STAGE1, STAGE2),
+        session_factory=lambda: db_session,
     )
 
     assert comparison_spy == []
 
 
 async def test_missing_model_skips_comparison(db_session, monkeypatch, comparison_spy):
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
     _seed_config(db_session)
     _seed_baseline(db_session, T0)
     _seed_current(db_session, completed_at=T0 + timedelta(hours=2))
@@ -139,8 +138,9 @@ async def test_missing_model_skips_comparison(db_session, monkeypatch, compariso
 
     monkeypatch.setattr(analysis_module, "resolve_analysis_model", _resolve)
 
-    await execute_campaign_analysis(
+    await execute_campaign_analysis_job(
         "camp-cur", triggered_by="auto", chat_client=FakeChatClient(STAGE1, STAGE2),
+        session_factory=lambda: db_session,
     )
 
     analysis_row = db_session.exec(
@@ -151,18 +151,18 @@ async def test_missing_model_skips_comparison(db_session, monkeypatch, compariso
 
 
 async def test_comparison_enqueue_error_does_not_affect_analysis(db_session, monkeypatch):
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
     _seed_config(db_session)
     _seed_baseline(db_session, T0)
     _seed_current(db_session, completed_at=T0 + timedelta(hours=2))
 
-    def _boom(campaign_id, *, triggered_by, baseline_campaign_id=None):
+    def _boom(campaign_id, *, triggered_by, baseline_campaign_id, session=None):
         raise RuntimeError("enqueue failed")
 
-    monkeypatch.setattr(comparison_module, "start_campaign_comparison", _boom)
+    monkeypatch.setattr(intelligence_jobs, "enqueue_campaign_comparison", _boom)
 
-    await execute_campaign_analysis(
+    await execute_campaign_analysis_job(
         "camp-cur", triggered_by="auto", chat_client=FakeChatClient(STAGE1, STAGE2),
+        session_factory=lambda: db_session,
     )
 
     analysis_row = db_session.exec(

tests/integration/test_campaign_runner.py

@@ -1,6 +1,6 @@
 """Integration test for campaign Run-spawning driven by a manual clock.
 
-Drives ``advance_campaign`` at injected clock positions against a
+Drives the runtime's internal advance seam at injected clock positions against a
 compressed-time-scale campaign and asserts the spawned child Runs match the
 plan (count, ownership, scenario) and complete with results/summary in the DB.
 No real timer is used — the clock is injected, mirroring how the durable loop
@@ -8,7 +8,7 @@ No real timer is used — the clock is injected, mirroring how the durable loop
 """
 
 import pytest
-from agenteval.evaluation.campaign_runner import advance_campaign, reconcile_campaign_child_runs
+from agenteval.evaluation.campaign_runner import _advance_campaign, _reconcile_campaign_child_runs
 from agenteval.models import (
     Campaign,
     CampaignPlanEntry,
@@ -50,7 +50,8 @@ def seeded_db(db_session, monkeypatch):
     monkeypatch.setattr(factory_module.ChannelFactory, "create", lambda target: channel)
 
     target = EvalTarget(
-        id="t-1", name="mock-target",
+        id="t-1",
+        name="mock-target",
         platform=PlatformType.AI_DIGITAL_EMPLOYEE,
         channel_type=ChannelType.TUTU_API,
         channel_config={"base_url": "http://mock", "token": "x"},
@@ -59,7 +60,8 @@ def seeded_db(db_session, monkeypatch):
     TargetRepository(db_session).create(target)
 
     scenario = Scenario(
-        id="s-1", name="mock-scenario",
+        id="s-1",
+        name="mock-scenario",
         cases=[Case(id="c1", type=CaseType.SINGLE, messages=["hi"])],
     )
     ScenarioRepository(db_session).create(scenario)
@@ -68,36 +70,36 @@ def seeded_db(db_session, monkeypatch):
 
 
 def _make_campaign(session) -> Campaign:
-    return CampaignRepository(session).create(Campaign(
-        name="compressed",
-        target_id="t-1",
-        status="running",
-        window_seconds=7200,
-        time_scale=3600.0,  # 1 real second == 3600 window seconds
-        plan=[
-            CampaignPlanEntry(scenario_id="s-1", offset_seconds=0, count=2),
-            CampaignPlanEntry(scenario_id="s-1", offset_seconds=3600, count=1),
-        ],
-    ))
+    return CampaignRepository(session).create(
+        Campaign(
+            name="compressed",
+            target_id="t-1",
+            status="running",
+            window_seconds=7200,
+            time_scale=3600.0,  # 1 real second == 3600 window seconds
+            plan=[
+                CampaignPlanEntry(scenario_id="s-1", offset_seconds=0, count=2),
+                CampaignPlanEntry(scenario_id="s-1", offset_seconds=3600, count=1),
+            ],
+        )
+    )
 
 
 async def test_advance_spawns_due_runs_matching_plan(seeded_db):
     campaign = _make_campaign(seeded_db)
 
     # t=0 → window offset 0 → only entry 0 (count 2) is due.
-    r0 = await advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
+    r0 = await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
     assert len(r0.spawned_run_ids) == 2
     assert r0.finished is False
 
     # t=1s → window offset 3600 → entry 1 (count 1) becomes due.
-    r1 = await advance_campaign(campaign_id=campaign.id, elapsed_seconds=1.0, session=seeded_db)
+    r1 = await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=1.0, session=seeded_db)
     assert len(r1.spawned_run_ids) == 1
 
     runs = RunRepository(seeded_db).list_all()
     assert len(runs) == 3
-    assert {
-        (run.campaign_plan_index, run.campaign_occurrence_index) for run in runs
-    } == {(0, 0), (0, 1), (1, 0)}
+    assert {(run.campaign_plan_index, run.campaign_occurrence_index) for run in runs} == {(0, 0), (0, 1), (1, 0)}
     for run in runs:
         assert run.campaign_id == campaign.id
         assert run.scenario_id == "s-1"
@@ -109,9 +111,9 @@ async def test_advance_spawns_due_runs_matching_plan(seeded_db):
 async def test_advance_is_idempotent(seeded_db):
     campaign = _make_campaign(seeded_db)
 
-    await advance_campaign(campaign_id=campaign.id, elapsed_seconds=1.0, session=seeded_db)
+    await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=1.0, session=seeded_db)
     # Re-advancing to the same clock must not double-spawn.
-    again = await advance_campaign(campaign_id=campaign.id, elapsed_seconds=1.0, session=seeded_db)
+    again = await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=1.0, session=seeded_db)
     assert again.spawned_run_ids == []
     assert len(RunRepository(seeded_db).list_all()) == 3  # entry0(2) + entry1(1)
 
@@ -119,12 +121,12 @@ async def test_advance_is_idempotent(seeded_db):
 async def test_advance_reports_finished_at_window_end(seeded_db):
     campaign = _make_campaign(seeded_db)
     # t=2s → offset 7200 == window end.
-    result = await advance_campaign(campaign_id=campaign.id, elapsed_seconds=2.0, session=seeded_db)
+    result = await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=2.0, session=seeded_db)
     assert result.finished is True
 
 
 async def test_advance_missing_campaign_returns_none(seeded_db):
-    assert await advance_campaign(campaign_id="nope", elapsed_seconds=0.0, session=seeded_db) is None
+    assert await _advance_campaign(campaign_id="nope", elapsed_seconds=0.0, session=seeded_db) is None
 
 
 async def test_restart_after_claim_does_not_create_second_run(seeded_db):
@@ -146,7 +148,7 @@ async def test_restart_after_claim_does_not_create_second_run(seeded_db):
     )
     assert claim.run is not None
 
-    result = await advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
+    result = await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
 
     runs = RunRepository(seeded_db).list_by_campaign(campaign.id)
     assert result.spawned_run_ids == []
@@ -176,7 +178,7 @@ async def test_partial_claim_does_not_hide_remaining_occurrences(seeded_db):
     campaign.summary = CampaignSummary(scheduler=SchedulerState(spawned_indices=[0]))
     CampaignRepository(seeded_db).update(campaign)
 
-    await advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
+    await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
 
     runs = RunRepository(seeded_db).list_by_campaign(campaign.id)
     assert len(runs) == 2
@@ -208,11 +210,11 @@ async def test_partial_spawn_failure_is_retried_until_all_occurrences_are_claime
 
     monkeypatch.setattr(campaign_runner, "_spawn_child_run", flaky_spawn)
 
-    await advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
+    await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
     after_failure = CampaignRepository(seeded_db).get(campaign.id)
     assert after_failure.summary.scheduler.spawned_indices == []
 
-    await advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
+    await _advance_campaign(campaign_id=campaign.id, elapsed_seconds=0.0, session=seeded_db)
     runs = RunRepository(seeded_db).list_by_campaign(campaign.id)
     recovered = CampaignRepository(seeded_db).get(campaign.id)
     assert {run.campaign_occurrence_index for run in runs} == {0, 1}
@@ -230,7 +232,7 @@ async def test_recovery_resumes_pending_claim_without_replacing_identity(seeded_
     )
     assert claim.run is not None
 
-    result = await reconcile_campaign_child_runs(campaign.id, seeded_db)
+    result = await _reconcile_campaign_child_runs(campaign.id, seeded_db)
 
     recovered = RunRepository(seeded_db).get(claim.run.id)
     assert result is not None
@@ -253,7 +255,7 @@ async def test_recovery_fails_running_claim_without_replaying_messages(seeded_db
     claim.run.status = RunStatus.RUNNING
     repo.update(claim.run)
 
-    result = await reconcile_campaign_child_runs(campaign.id, seeded_db)
+    result = await _reconcile_campaign_child_runs(campaign.id, seeded_db)
 
     interrupted = repo.get(claim.run.id)
     assert result is not None

tests/integration/test_campaign_scheduler_loop.py

@@ -1,6 +1,6 @@
 """Integration tests for the durable campaign scheduler loop (ticket 03).
 
-Drives ``campaign_runner.start_campaign`` with a tiny tick and a compressed
+Drives ``CampaignRuntime`` with a tiny tick and a compressed
 time scale so a whole window elapses in a few real milliseconds. Covers:
 auto-run-to-completion, restart recovery (no double-spawn, no lost progress),
 and cancellation (no further spawning).
@@ -10,7 +10,8 @@ from datetime import timedelta
 
 import pytest
 from agenteval.evaluation import campaign_runner
-from agenteval.evaluation.campaign_runner import request_cancel, start_campaign
+from agenteval.evaluation.campaign_lifecycle import cancel_campaign
+from agenteval.evaluation.campaign_runner import CampaignRuntime
 from agenteval.models import (
     Campaign,
     CampaignPlanEntry,
@@ -50,15 +51,23 @@ def seeded_db(db_session, monkeypatch):
     channel = MockChannel(reply_delay=0.0)
     monkeypatch.setattr(factory_module.ChannelFactory, "create", lambda target: channel)
 
-    TargetRepository(db_session).create(EvalTarget(
-        id="t-1", name="mock-target",
-        platform=PlatformType.AI_DIGITAL_EMPLOYEE, channel_type=ChannelType.TUTU_API,
-        channel_config={"base_url": "http://mock", "token": "x"}, status=TargetStatus.ACTIVE,
-    ))
-    ScenarioRepository(db_session).create(Scenario(
-        id="s-1", name="mock-scenario",
-        cases=[Case(id="c1", type=CaseType.SINGLE, messages=["hi"])],
-    ))
+    TargetRepository(db_session).create(
+        EvalTarget(
+            id="t-1",
+            name="mock-target",
+            platform=PlatformType.AI_DIGITAL_EMPLOYEE,
+            channel_type=ChannelType.TUTU_API,
+            channel_config={"base_url": "http://mock", "token": "x"},
+            status=TargetStatus.ACTIVE,
+        )
+    )
+    ScenarioRepository(db_session).create(
+        Scenario(
+            id="s-1",
+            name="mock-scenario",
+            cases=[Case(id="c1", type=CaseType.SINGLE, messages=["hi"])],
+        )
+    )
     return db_session
 
 
@@ -77,17 +86,25 @@ def _make_campaign(session, **overrides) -> Campaign:
     return CampaignRepository(session).create(Campaign(**payload))
 
 
-async def _await_task(campaign_id, timeout=3.0):
+@pytest.fixture()
+async def runtime(seeded_db):
+    value = CampaignRuntime(session_factory=lambda: seeded_db, tick_seconds=TICK)
+    yield value
+    await value.shutdown()
+
+
+async def _await_terminal(session, campaign_id, timeout=3.0):
     import asyncio
-    task = campaign_runner.campaign_registry.get(campaign_id)
-    if task is not None:
-        await asyncio.wait_for(task, timeout=timeout)
+
+    async with asyncio.timeout(timeout):
+        while CampaignRepository(session).get(campaign_id).status is CampaignStatus.RUNNING:
+            await asyncio.sleep(TICK)
 
 
-async def test_loop_runs_to_completion(seeded_db):
+async def test_loop_runs_to_completion(seeded_db, runtime):
     campaign = _make_campaign(seeded_db)
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    await _await_task(campaign.id)
+    assert runtime.start(campaign.id)
+    await _await_terminal(seeded_db, campaign.id)
 
     final = CampaignRepository(seeded_db).get(campaign.id)
     assert final.status == CampaignStatus.COMPLETED
@@ -98,7 +115,42 @@ async def test_loop_runs_to_completion(seeded_db):
     assert all(r.status == RunStatus.COMPLETED for r in runs)
 
 
-async def test_loop_retries_completion_after_settlement_failure(seeded_db, monkeypatch):
+async def test_runtime_start_is_idempotent(seeded_db, runtime):
+    campaign = _make_campaign(seeded_db)
+
+    assert runtime.start(campaign.id)
+    assert runtime.start(campaign.id)
+    await _await_terminal(seeded_db, campaign.id)
+
+    assert len(RunRepository(seeded_db).list_by_campaign(campaign.id)) == 2
+
+
+async def test_runtime_accepts_internal_clock_and_executor_adapters(seeded_db):
+    started_at = utc_now()
+    campaign = _make_campaign(seeded_db, started_at=started_at, status=CampaignStatus.RUNNING)
+    executed: list[tuple[int, int]] = []
+
+    async def execute_child(_campaign, _scenario, run, session):
+        executed.append((run.campaign_plan_index, run.campaign_occurrence_index))
+        run.status = RunStatus.COMPLETED
+        RunRepository(session).update(run)
+
+    runtime = CampaignRuntime(
+        session_factory=lambda: seeded_db,
+        now=lambda: started_at + timedelta(seconds=1),
+        tick_seconds=TICK,
+        execute_child_run=execute_child,
+    )
+    try:
+        assert runtime.start(campaign.id)
+        await _await_terminal(seeded_db, campaign.id)
+    finally:
+        await runtime.shutdown()
+
+    assert executed == [(0, 0), (1, 0)]
+
+
+async def test_loop_retries_completion_after_settlement_failure(seeded_db, runtime, monkeypatch):
     campaign = _make_campaign(seeded_db)
     real_complete = campaign_runner.complete_campaign
     attempts = 0
@@ -111,14 +163,14 @@ async def test_loop_retries_completion_after_settlement_failure(seeded_db, monke
         return real_complete(*args, **kwargs)
 
     monkeypatch.setattr(campaign_runner, "complete_campaign", flaky_complete)
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    await _await_task(campaign.id)
+    assert runtime.start(campaign.id)
+    await _await_terminal(seeded_db, campaign.id)
 
     assert attempts == 2
     assert CampaignRepository(seeded_db).get(campaign.id).status is CampaignStatus.COMPLETED
 
 
-async def test_restart_recovery_does_not_respawn(seeded_db):
+async def test_restart_recovery_does_not_respawn(seeded_db, runtime):
     # Simulate a campaign that was already RUNNING before a restart, with its
     # window start well in the past and entry 0 already recorded as spawned.
     campaign = _make_campaign(seeded_db)
@@ -128,8 +180,9 @@ async def test_restart_recovery_does_not_respawn(seeded_db):
     CampaignRepository(seeded_db).update(campaign)
 
     # Recovery relaunches the loop for the already-RUNNING campaign.
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    await _await_task(campaign.id)
+    recovery = runtime.recover()
+    assert recovery.resumed_campaigns == 1
+    await _await_terminal(seeded_db, campaign.id)
 
     final = CampaignRepository(seeded_db).get(campaign.id)
     assert final.status == CampaignStatus.COMPLETED
@@ -139,7 +192,7 @@ async def test_restart_recovery_does_not_respawn(seeded_db):
     assert len(runs) == 1
 
 
-async def test_restart_preserves_original_window_start(seeded_db):
+async def test_restart_preserves_original_window_start(seeded_db, runtime):
     original = utc_now() - timedelta(seconds=5)
     campaign = _make_campaign(seeded_db, window_seconds=100000, time_scale=1.0)
     campaign.status = CampaignStatus.RUNNING
@@ -147,35 +200,32 @@ async def test_restart_preserves_original_window_start(seeded_db):
     CampaignRepository(seeded_db).update(campaign)
 
     # Resume must NOT reset started_at (that would rewind the window clock).
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
-    request_cancel(campaign.id)  # stop the long-window loop promptly
-    await _await_task(campaign.id)
+    assert runtime.start(campaign.id)
+    cancel_campaign(seeded_db, campaign.id, stop=runtime.cancel)
 
     reloaded = CampaignRepository(seeded_db).get(campaign.id)
     assert abs((reloaded.started_at.replace(tzinfo=None) - original.replace(tzinfo=None)).total_seconds()) < 1
 
 
-async def test_cancel_stops_further_spawning(seeded_db):
+async def test_cancel_stops_further_spawning(seeded_db, runtime):
     import asyncio
+
     # Long real window (scale 1.0) so entry 1 (offset 50s) never comes due fast.
     campaign = _make_campaign(
-        seeded_db, window_seconds=100, time_scale=1.0,
+        seeded_db,
+        window_seconds=100,
+        time_scale=1.0,
         plan=[
             CampaignPlanEntry(scenario_id="s-1", offset_seconds=0, count=1),
             CampaignPlanEntry(scenario_id="s-1", offset_seconds=50, count=1),
         ],
     )
-    start_campaign(campaign.id, seeded_db, tick_seconds=TICK)
+    assert runtime.start(campaign.id)
     await asyncio.sleep(0.05)  # let the first tick spawn entry 0
 
     # Cancel: mark DB authoritative + signal the live loop.
     repo = CampaignRepository(seeded_db)
-    current = repo.get(campaign.id)
-    current.status = CampaignStatus.CANCELLED
-    current.completed_at = utc_now()
-    repo.update(current)
-    request_cancel(campaign.id)
-    await _await_task(campaign.id)
+    cancel_campaign(seeded_db, campaign.id, stop=runtime.cancel)
 
     final = repo.get(campaign.id)
     assert final.status == CampaignStatus.CANCELLED

tests/integration/test_campaigns_api.py

@@ -33,7 +33,7 @@ def seeded_db(db_session, monkeypatch):
     monkeypatch.setattr(app_module, "init_db", lambda: None)
     # These tests cover persistence/validation/CRUD only — stub out the durable
     # scheduler so creation stays PLANNED and no background loop is launched.
-    monkeypatch.setattr(campaigns_module, "start_campaign", lambda *a, **k: None)
+    monkeypatch.setattr(campaigns_module.campaign_runtime, "start", lambda *a, **k: None)
 
     def _test_get_session():
         return db_session

tests/integration/test_exploration_settlement.py

@@ -9,7 +9,7 @@ import asyncio
 
 import pytest
 from agenteval.evaluation import campaign_runner as runner_module
-from agenteval.evaluation.campaign_runner import run_campaign_loop
+from agenteval.evaluation.campaign_runner import CampaignRuntime
 from agenteval.exploration.models import ExplorationSessionStatus
 from agenteval.models import (
     Campaign,
@@ -128,10 +128,15 @@ async def test_window_completion_expires_running_sessions(seeded_db):
     campaign = _make_campaign(seeded_db, "c-done", time_scale=3600.0)
     session_id = await _create_running_session(seeded_db, "c-done")
 
-    # time_scale 3600 → 1 real second covers the whole window; the loop
-    # completes on its first tick and settles exploration sessions.
-    cancel = asyncio.Event()
-    await asyncio.wait_for(run_campaign_loop(campaign.id, cancel, tick_seconds=0.05), timeout=5)
+    # time_scale 3600 → 1 real second covers the whole window.
+    runtime = CampaignRuntime(session_factory=lambda: seeded_db, tick_seconds=0.05)
+    try:
+        assert runtime.start(campaign.id)
+        async with asyncio.timeout(5):
+            while CampaignRepository(seeded_db).get(campaign.id).status.value == "running":
+                await asyncio.sleep(0.05)
+    finally:
+        await runtime.shutdown()
 
     assert CampaignRepository(seeded_db).get("c-done").status.value == "completed"
     settled = ExplorationSessionRepository(seeded_db).get(session_id)

tests/integration/test_migration_roundtrip.py

@@ -0,0 +1,31 @@
+"""Exercise the complete Alembic downgrade/upgrade chain on a fresh schema."""
+
+from pathlib import Path
+
+from alembic import command
+from alembic.config import Config
+from sqlalchemy import create_engine, inspect
+from sqlmodel import SQLModel
+
+
+def test_fresh_schema_round_trips_through_base(tmp_path: Path, monkeypatch):
+    from agenteval.storage import db as db_module
+
+    database_url = f"sqlite:///{tmp_path / 'roundtrip.db'}"
+    monkeypatch.setattr(db_module, "DATABASE_URL", database_url)
+    engine = create_engine(database_url)
+    SQLModel.metadata.create_all(engine)
+    config = Config(str(Path(__file__).resolve().parents[2] / "alembic.ini"))
+
+    foreign_keys = inspect(engine).get_foreign_keys("eval_runs")
+    assert any(key["constrained_columns"] == ["campaign_id"] and key["name"] is None for key in foreign_keys)
+
+    command.stamp(config, "head")
+    command.downgrade(config, "base")
+    command.upgrade(config, "head")
+
+    inspector = inspect(engine)
+    assert "campaigns" in inspector.get_table_names()
+    assert {"campaign_id", "campaign_plan_index", "campaign_occurrence_index"} <= {
+        column["name"] for column in inspector.get_columns("eval_runs")
+    }

tests/unit/test_campaign_analysis.py

@@ -7,9 +7,9 @@ from agenteval.evaluation.analysis import (
     AnalysisError,
     analyze_campaign,
     collect_failure_samples,
-    execute_campaign_analysis,
     resolve_analysis_model,
 )
+from agenteval.evaluation.intelligence_jobs import execute_campaign_analysis_job
 from agenteval.models import Campaign, CampaignPlanEntry, EvalRun, RunStatus
 from agenteval.storage.db import CampaignAnalysisDB, EvalResultDB, ModelConfigDB, TurnDB
 from agenteval.storage.model_config_repository import ModelConfigRepository
@@ -264,17 +264,16 @@ def test_collect_failure_samples_skips_passing_runs(db_session):
 
 # ── 后台执行状态机 ───────────────────────────────────────────────────────
 
-async def test_execute_writes_completed_row_with_model_snapshot(db_session, monkeypatch):
-    from agenteval.evaluation import analysis as analysis_module
-
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
+async def test_execute_writes_completed_row_with_model_snapshot(db_session):
     _seed_config(db_session, "mc-default", analysis_default=True)
     CampaignRepository(db_session).create(_campaign())
     _seed_failed_run(db_session, "run-1", "s-1", failed_turns=1)
     _seed_failed_run(db_session, "run-2", "s-2", failed_turns=1)
 
     client = FakeChatClient(STAGE1_A, STAGE1_B, STAGE2)
-    await execute_campaign_analysis("camp-1", triggered_by="manual", chat_client=client)
+    await execute_campaign_analysis_job(
+        "camp-1", triggered_by="manual", chat_client=client, session_factory=lambda: db_session,
+    )
 
     row = db_session.exec(
         select(CampaignAnalysisDB).where(CampaignAnalysisDB.campaign_id == "camp-1")
@@ -285,15 +284,14 @@ async def test_execute_writes_completed_row_with_model_snapshot(db_session, monk
     assert row.get_result()["overall"].startswith("活动整体不达标")
 
 
-async def test_execute_records_failure(db_session, monkeypatch):
-    from agenteval.evaluation import analysis as analysis_module
-
-    monkeypatch.setattr(analysis_module, "get_session", lambda: db_session)
+async def test_execute_records_failure(db_session):
     _seed_config(db_session, "mc-default", analysis_default=True)
     CampaignRepository(db_session).create(_campaign())
 
     client = FakeChatClient("garbage")
-    await execute_campaign_analysis("camp-1", triggered_by="auto", chat_client=client)
+    await execute_campaign_analysis_job(
+        "camp-1", triggered_by="auto", chat_client=client, session_factory=lambda: db_session,
+    )
 
     row = db_session.exec(
         select(CampaignAnalysisDB).where(CampaignAnalysisDB.campaign_id == "camp-1")

tests/unit/test_campaign_comparison.py

@@ -8,10 +8,10 @@ from agenteval.evaluation.comparison import (
     ComparisonError,
     campaign_plan_fingerprint,
     compute_metric_diff,
-    execute_campaign_comparison,
     narrate_period_comparison,
     resolve_auto_baseline,
 )
+from agenteval.evaluation.intelligence_jobs import execute_campaign_comparison_job
 from agenteval.models import Campaign, CampaignPlanEntry, CampaignStatus, EvalRun, RunStatus, RunSummary
 from agenteval.storage.db import (
     CampaignAnalysisDB,
@@ -382,18 +382,16 @@ def _seed_campaign_with_analysis(session, campaign: Campaign, analysis_result: d
     ))
 
 
-async def test_execute_writes_completed_row_with_baseline_snapshot(db_session, monkeypatch):
-    from agenteval.evaluation import comparison as comparison_module
-
-    monkeypatch.setattr(comparison_module, "get_session", lambda: db_session)
+async def test_execute_writes_completed_row_with_baseline_snapshot(db_session):
     _seed_config(db_session, "mc-default")
     baseline = _campaign("camp-base", completed_at=T0)
     current = _campaign("camp-cur", completed_at=T0 + timedelta(hours=2))
     _seed_campaign_with_analysis(db_session, baseline, _analysis("上期"))
     _seed_campaign_with_analysis(db_session, current, _analysis("本期"))
 
-    await execute_campaign_comparison(
+    await execute_campaign_comparison_job(
         "camp-cur", triggered_by="manual", chat_client=FakeChatClient(NARRATION),
+        session_factory=lambda: db_session,
     )
 
     row = db_session.exec(
@@ -405,18 +403,16 @@ async def test_execute_writes_completed_row_with_baseline_snapshot(db_session, m
     assert row.get_result()["trend"] == "improving"
 
 
-async def test_execute_records_failure_on_unparseable_output(db_session, monkeypatch):
-    from agenteval.evaluation import comparison as comparison_module
-
-    monkeypatch.setattr(comparison_module, "get_session", lambda: db_session)
+async def test_execute_records_failure_on_unparseable_output(db_session):
     _seed_config(db_session, "mc-default")
     baseline = _campaign("camp-base", completed_at=T0)
     current = _campaign("camp-cur", completed_at=T0 + timedelta(hours=2))
     _seed_campaign_with_analysis(db_session, baseline, _analysis("上期"))
     _seed_campaign_with_analysis(db_session, current, _analysis("本期"))
 
-    await execute_campaign_comparison(
+    await execute_campaign_comparison_job(
         "camp-cur", triggered_by="manual", chat_client=FakeChatClient("garbage"),
+        session_factory=lambda: db_session,
     )
 
     row = db_session.exec(
@@ -427,18 +423,16 @@ async def test_execute_records_failure_on_unparseable_output(db_session, monkeyp
     assert row.baseline_campaign_id == "camp-base"
 
 
-async def test_execute_fails_without_baseline_analysis(db_session, monkeypatch):
-    from agenteval.evaluation import comparison as comparison_module
-
-    monkeypatch.setattr(comparison_module, "get_session", lambda: db_session)
+async def test_execute_fails_without_baseline_analysis(db_session):
     _seed_config(db_session, "mc-default")
     baseline = _campaign("camp-base", completed_at=T0)
     current = _campaign("camp-cur", completed_at=T0 + timedelta(hours=2))
     CampaignRepository(db_session).create(baseline)  # 基线无分析行
     _seed_campaign_with_analysis(db_session, current, _analysis("本期"))
 
-    await execute_campaign_comparison(
+    await execute_campaign_comparison_job(
         "camp-cur", triggered_by="manual", chat_client=FakeChatClient(NARRATION),
+        session_factory=lambda: db_session,
     )
 
     row = db_session.exec(

tests/unit/test_campaign_lifecycle.py

@@ -13,9 +13,9 @@ def test_create_campaign_commits_running_before_launch(db_session):
     ScenarioRepository(db_session).create(Scenario(id="s-1", name="scenario", cases=[Case(id="c-1", messages=["hi"])]))
     launched: list[str] = []
 
-    def launch(campaign_id, session):
+    def launch(campaign_id):
         launched.append(campaign_id)
-        assert CampaignRepository(session).get(campaign_id).status is CampaignStatus.RUNNING
+        assert CampaignRepository(db_session).get(campaign_id).status is CampaignStatus.RUNNING
 
     campaign = create_campaign(
         db_session,
@@ -36,7 +36,7 @@ def test_create_campaign_launch_failure_leaves_durable_row(db_session):
     TargetRepository(db_session).create(_make_target())
     ScenarioRepository(db_session).create(Scenario(id="s-1", name="scenario", cases=[Case(id="c-1", messages=["hi"])]))
 
-    def launch(_campaign_id, _session):
+    def launch(_campaign_id):
         raise RuntimeError("scheduler unavailable")
 
     with pytest.raises(RuntimeError):

tests/unit/test_campaign_read_model.py

@@ -0,0 +1,68 @@
+"""Campaign read-model projections and batched child-Run loading."""
+
+from datetime import datetime, timezone
+
+from agenteval.evaluation.campaign_read_model import CampaignReadModel
+from agenteval.models import Campaign, CampaignPlanEntry, EvalRun, RunStatus
+from agenteval.storage.repository import CampaignRepository, RunRepository
+
+
+def _campaign(session, campaign_id: str) -> Campaign:
+    return CampaignRepository(session).create(Campaign(
+        id=campaign_id,
+        name=campaign_id,
+        target_id="target-1",
+        window_seconds=60,
+        plan=[CampaignPlanEntry(scenario_id="scenario-1", offset_seconds=0)],
+    ))
+
+
+def _run(session, campaign_id: str, run_id: str) -> EvalRun:
+    return RunRepository(session).create(EvalRun(
+        id=run_id,
+        target_id="target-1",
+        scenario_id="scenario-1",
+        campaign_id=campaign_id,
+        status=RunStatus.COMPLETED,
+        started_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
+        summary={"total_cases": 1, "passed_cases": 1, "pass_rate": 1.0},
+    ))
+
+
+def test_list_items_empty(db_session):
+    assert CampaignReadModel(db_session).list_items() == []
+
+
+def test_list_items_batches_runs_for_multiple_campaigns(db_session, monkeypatch):
+    first = _campaign(db_session, "campaign-1")
+    second = _campaign(db_session, "campaign-2")
+    _run(db_session, first.id, "run-1")
+    _run(db_session, second.id, "run-2")
+
+    def reject_per_campaign_query(*args, **kwargs):
+        raise AssertionError("list_items must not query child Runs per Campaign")
+
+    monkeypatch.setattr(RunRepository, "list_by_campaign", reject_per_campaign_query)
+
+    items = CampaignReadModel(db_session).list_items()
+
+    progress_by_id = {item["id"]: item["progress"] for item in items}
+    assert set(progress_by_id) == {first.id, second.id}
+    assert progress_by_id[first.id]["completed_runs"] == 1
+    assert progress_by_id[second.id]["completed_runs"] == 1
+
+
+def test_markdown_projection_uses_json_report_projection(db_session):
+    campaign = _campaign(db_session, "campaign-1")
+    _run(db_session, campaign.id, "run-1")
+    read_model = CampaignReadModel(db_session)
+
+    json_report = read_model.report(campaign.id)
+    markdown_projection = read_model.markdown_projection(campaign.id)
+
+    assert json_report is not None
+    assert markdown_projection is not None
+    assert markdown_projection["report"] == {
+        key: value for key, value in json_report.items() if key != "exploration"
+    }
+    assert markdown_projection["exploration"] == json_report.get("exploration")

tests/unit/test_campaign_recovery.py

@@ -1,11 +1,20 @@
-"""Tests for the unified durable Campaign startup recovery seam."""
+"""Tests for the CampaignRuntime startup recovery interface."""
 
-from agenteval.evaluation import campaign_lifecycle
+import asyncio
+from types import SimpleNamespace
+
+from agenteval.evaluation import campaign_runner
+from agenteval.evaluation.campaign_runner import CampaignRuntime
+from agenteval.models import CampaignStatus
 
 
-def test_recovery_coordinator_orders_cleanup_before_relaunch(db_session, monkeypatch):
+async def test_runtime_recovery_repairs_before_relaunch(monkeypatch):
     calls: list[str] = []
 
+    class FakeSession:
+        def close(self):
+            calls.append("close")
+
     class FakeRuns:
         def __init__(self, _session):
             pass
@@ -14,33 +23,27 @@ def test_recovery_coordinator_orders_cleanup_before_relaunch(db_session, monkeyp
             calls.append("runs")
             return 2
 
-    class FakeAnalysis:
+    class FakeCampaigns:
         def __init__(self, _session):
             pass
 
-        def mark_orphans_failed(self):
-            calls.append("analysis")
-            return 1
+        def list_all(self):
+            calls.append("campaigns")
+            return [SimpleNamespace(id="campaign-1", status=CampaignStatus.RUNNING)]
 
-    class FakeComparison(FakeAnalysis):
-        def mark_orphans_failed(self):
-            calls.append("comparison")
-            return 1
+    async def fake_loop(campaign_id, cancel, **kwargs):
+        calls.append(f"launch:{campaign_id}")
 
-    monkeypatch.setattr(campaign_lifecycle, "RunRepository", FakeRuns)
-    monkeypatch.setattr(campaign_lifecycle, "CampaignAnalysisRepository", FakeAnalysis)
-    monkeypatch.setattr(campaign_lifecycle, "CampaignPeriodComparisonRepository", FakeComparison)
+    monkeypatch.setattr(campaign_runner, "RunRepository", FakeRuns)
+    monkeypatch.setattr(campaign_runner, "CampaignRepository", FakeCampaigns)
+    monkeypatch.setattr(campaign_runner, "_run_campaign_loop", fake_loop)
+    runtime = CampaignRuntime(session_factory=FakeSession)
 
-    import agenteval.evaluation.analysis as analysis
-    import agenteval.evaluation.campaign_runner as runner
+    summary = runtime.recover()
+    await asyncio.sleep(0)
+    await runtime.shutdown()
 
-    monkeypatch.setattr(analysis, "resume_queued_campaign_analysis", lambda _session: calls.append("queued") or 3)
-    monkeypatch.setattr(runner, "resume_running_campaigns", lambda _session, **_: calls.append("campaigns") or 4)
-
-    summary = campaign_lifecycle.recover_campaign_runtime(db_session)
-
-    assert calls == ["runs", "analysis", "comparison", "campaigns", "queued"]
     assert summary.interrupted_runs == 2
-    assert summary.interrupted_analysis == 2
-    assert summary.resumed_campaigns == 4
-    assert summary.resumed_analysis == 3
+    assert summary.resumed_campaigns == 1
+    assert calls[:3] == ["runs", "campaigns", "close"]
+    assert "launch:campaign-1" in calls

tests/unit/test_campaign_start_lifecycle.py

@@ -18,8 +18,8 @@ def test_start_planned_campaign_is_atomic_and_launches_after_commit(db_session):
     )
     observed = []
 
-    def launch(campaign_id, session):
-        observed.append(CampaignRepository(session).get(campaign_id).status)
+    def launch(campaign_id):
+        observed.append(CampaignRepository(db_session).get(campaign_id).status)
 
     started = start_campaign(db_session, "campaign-1", launch=launch)
 

tests/unit/test_llm_task_lifecycle.py

@@ -8,9 +8,10 @@ generating 行标记为 failed。
 import asyncio
 
 import pytest
-from agenteval.evaluation import analysis, comparison
+from agenteval.evaluation import intelligence_jobs
 from agenteval.exploration import judge
 from agenteval.storage.repository import (
+    AsyncJobClaimStatus,
     CampaignAnalysisRepository,
     CampaignPeriodComparisonRepository,
 )
@@ -38,19 +39,24 @@ def db_session(tmp_path):
         engine.dispose()
 
 
-async def test_start_analysis_registers_in_registry(monkeypatch):
-    monkeypatch.setattr(analysis, "execute_campaign_analysis", lambda *a, **kw: asyncio.sleep(0))
-    analysis.start_campaign_analysis("c-1", triggered_by="manual")
-    assert analysis.analysis_registry.is_running("c-1")
-    await analysis.analysis_registry.shutdown_all()
-    assert not analysis.analysis_registry.is_running("c-1")
+async def test_start_analysis_registers_in_registry(db_session, monkeypatch):
+    monkeypatch.setattr(intelligence_jobs, "execute_campaign_analysis_job", lambda *a, **kw: asyncio.sleep(0))
+    intelligence_jobs.enqueue_campaign_analysis("c-1", triggered_by="manual", session=db_session)
+    assert intelligence_jobs.is_intelligence_job_running("analysis", "c-1")
+    await intelligence_jobs.shutdown_campaign_intelligence_jobs()
+    assert not intelligence_jobs.is_intelligence_job_running("analysis", "c-1")
 
 
-async def test_start_comparison_registers_in_registry(monkeypatch):
-    monkeypatch.setattr(comparison, "execute_campaign_comparison", lambda *a, **kw: asyncio.sleep(0))
-    comparison.start_campaign_comparison("c-2", triggered_by="manual")
-    assert comparison.comparison_registry.is_running("c-2")
-    await comparison.comparison_registry.shutdown_all()
+async def test_start_comparison_registers_in_registry(db_session, monkeypatch):
+    monkeypatch.setattr(intelligence_jobs, "execute_campaign_comparison_job", lambda *a, **kw: asyncio.sleep(0))
+    intelligence_jobs.enqueue_campaign_comparison(
+        "c-2",
+        triggered_by="manual",
+        baseline_campaign_id="c-1",
+        session=db_session,
+    )
+    assert intelligence_jobs.is_intelligence_job_running("comparison", "c-2")
+    await intelligence_jobs.shutdown_campaign_intelligence_jobs()
 
 
 async def test_start_judge_registers_in_registry(monkeypatch):
@@ -60,29 +66,34 @@ async def test_start_judge_registers_in_registry(monkeypatch):
     await judge.judge_registry.shutdown_all()
 
 
-async def test_launch_is_idempotent_for_live_id(monkeypatch):
+async def test_launch_is_idempotent_for_live_id(db_session, monkeypatch):
     gate = asyncio.Event()
 
     async def hang(*args, **kwargs):
         await gate.wait()
 
-    monkeypatch.setattr(analysis, "execute_campaign_analysis", hang)
-    analysis.start_campaign_analysis("c-dup", triggered_by="manual")
-    analysis.start_campaign_analysis("c-dup", triggered_by="manual")
-    assert len(analysis.analysis_registry._tasks) == 1
+    monkeypatch.setattr(intelligence_jobs, "execute_campaign_analysis_job", hang)
+    intelligence_jobs.enqueue_campaign_analysis("c-dup", triggered_by="manual", session=db_session)
+    intelligence_jobs.enqueue_campaign_analysis("c-dup", triggered_by="manual", session=db_session)
+    assert intelligence_jobs.is_intelligence_job_running("analysis", "c-dup")
     gate.set()
-    await analysis.analysis_registry.shutdown_all()
+    await intelligence_jobs.shutdown_campaign_intelligence_jobs()
 
 
-async def test_shutdown_all_cancels_hanging_task(monkeypatch):
+async def test_shutdown_all_cancels_hanging_task(db_session, monkeypatch):
     async def hang(*args, **kwargs):
         await asyncio.Event().wait()
 
-    monkeypatch.setattr(comparison, "execute_campaign_comparison", hang)
-    comparison.start_campaign_comparison("c-hang", triggered_by="manual")
-    assert comparison.comparison_registry.is_running("c-hang")
-    await comparison.comparison_registry.shutdown_all()
-    assert not comparison.comparison_registry.is_running("c-hang")
+    monkeypatch.setattr(intelligence_jobs, "execute_campaign_comparison_job", hang)
+    intelligence_jobs.enqueue_campaign_comparison(
+        "c-hang",
+        triggered_by="manual",
+        baseline_campaign_id="c-base",
+        session=db_session,
+    )
+    assert intelligence_jobs.is_intelligence_job_running("comparison", "c-hang")
+    await intelligence_jobs.shutdown_campaign_intelligence_jobs()
+    assert not intelligence_jobs.is_intelligence_job_running("comparison", "c-hang")
 
 
 def test_mark_orphans_failed_flips_generating_analysis(db_session):
@@ -99,13 +110,14 @@ def test_mark_orphans_failed_flips_generating_analysis(db_session):
 
 
 def test_enqueue_analysis_persists_before_launch(db_session, monkeypatch):
-    from agenteval.evaluation import analysis
-
     launched = []
-    monkeypatch.setattr(analysis, "get_session", lambda: db_session)
-    monkeypatch.setattr(analysis, "start_campaign_analysis", lambda cid, *, triggered_by: launched.append((cid, triggered_by)))
+    monkeypatch.setattr(
+        intelligence_jobs,
+        "_launch_analysis",
+        lambda cid, *, triggered_by: launched.append((cid, triggered_by)),
+    )
 
-    analysis.enqueue_campaign_analysis("c-queued", triggered_by="auto")
+    intelligence_jobs.enqueue_campaign_analysis("c-queued", triggered_by="auto", session=db_session)
 
     assert launched == [("c-queued", "auto")]
     row = CampaignAnalysisRepository(db_session).get_by_campaign("c-queued")
@@ -113,15 +125,36 @@ def test_enqueue_analysis_persists_before_launch(db_session, monkeypatch):
     assert row.triggered_by == "auto"
 
 
-def test_resume_queued_analysis_relaunches_persisted_jobs(db_session, monkeypatch):
-    from agenteval.evaluation import analysis
+def test_only_one_session_can_claim_a_queued_analysis(db_session):
+    repo = CampaignAnalysisRepository(db_session)
+    repo.enqueue("c-claim", triggered_by="auto")
 
+    competing_session = Session(db_session.get_bind())
+    try:
+        assert repo.claim_queued("c-claim").status is AsyncJobClaimStatus.CLAIMED
+        assert (
+            CampaignAnalysisRepository(competing_session).claim_queued("c-claim").status
+            is AsyncJobClaimStatus.ALREADY_CLAIMED
+        )
+    finally:
+        competing_session.close()
+
+    row = repo.get_by_campaign("c-claim")
+    assert row.status == "generating"
+    assert row.triggered_by == "auto"
+
+
+def test_recovery_relaunches_persisted_analysis_jobs(db_session, monkeypatch):
     repo = CampaignAnalysisRepository(db_session)
     repo.enqueue("c-queued", triggered_by="auto")
     launched = []
-    monkeypatch.setattr(analysis, "start_campaign_analysis", lambda cid, *, triggered_by: launched.append((cid, triggered_by)))
+    monkeypatch.setattr(
+        intelligence_jobs,
+        "_launch_analysis",
+        lambda cid, *, triggered_by: launched.append((cid, triggered_by)),
+    )
 
-    assert analysis.resume_queued_campaign_analysis(db_session) == 1
+    assert intelligence_jobs.recover_campaign_intelligence_jobs(db_session) == (0, 1)
     assert launched == [("c-queued", "auto")]
 
 
@@ -136,3 +169,126 @@ def test_mark_orphans_failed_flips_generating_comparison(db_session):
     assert repo.get_by_campaign("c-gen").status == "failed"
     assert repo.get_by_campaign("c-gen").error
     assert repo.get_by_campaign("c-done").status == "completed"
+
+
+def test_enqueue_comparison_preserves_baseline_before_claim(db_session):
+    repo = CampaignPeriodComparisonRepository(db_session)
+
+    row = repo.enqueue(
+        "c-current",
+        baseline_campaign_id="c-baseline",
+        triggered_by="auto",
+    )
+
+    assert row.status == "queued"
+    assert row.baseline_campaign_id == "c-baseline"
+    assert row.triggered_by == "auto"
+    assert repo.claim_queued("c-current").status is AsyncJobClaimStatus.CLAIMED
+    assert repo.claim_queued("c-current").status is AsyncJobClaimStatus.ALREADY_CLAIMED
+
+
+def test_enqueue_comparison_persists_before_launch(db_session, monkeypatch):
+    launched = []
+    monkeypatch.setattr(
+        intelligence_jobs,
+        "_launch_comparison",
+        lambda cid, *, triggered_by, baseline_campaign_id: launched.append(
+            (cid, triggered_by, baseline_campaign_id)
+        ),
+    )
+
+    intelligence_jobs.enqueue_campaign_comparison(
+        "c-current",
+        baseline_campaign_id="c-baseline",
+        triggered_by="auto",
+        session=db_session,
+    )
+
+    assert launched == [("c-current", "auto", "c-baseline")]
+    row = CampaignPeriodComparisonRepository(db_session).get_by_campaign("c-current")
+    assert row.status == "queued"
+    assert row.baseline_campaign_id == "c-baseline"
+
+
+def test_recovery_relaunches_persisted_comparison_jobs(db_session, monkeypatch):
+    CampaignPeriodComparisonRepository(db_session).enqueue(
+        "c-current",
+        baseline_campaign_id="c-baseline",
+        triggered_by="auto",
+    )
+    launched = []
+    monkeypatch.setattr(
+        intelligence_jobs,
+        "_launch_comparison",
+        lambda cid, *, triggered_by, baseline_campaign_id: launched.append(
+            (cid, triggered_by, baseline_campaign_id)
+        ),
+    )
+
+    assert intelligence_jobs.recover_campaign_intelligence_jobs(db_session) == (0, 1)
+    assert launched == [("c-current", "auto", "c-baseline")]
+
+
+def test_claim_reports_missing_and_terminal_jobs(db_session):
+    repo = CampaignAnalysisRepository(db_session)
+
+    assert repo.claim_queued("missing").status is AsyncJobClaimStatus.NOT_FOUND
+    repo.upsert("c-done", status="completed", result={"ok": True})
+    assert repo.claim_queued("c-done").status is AsyncJobClaimStatus.NOT_QUEUED
+
+
+def test_reenqueue_does_not_move_generating_analysis_back_to_queued(db_session, monkeypatch):
+    repo = CampaignAnalysisRepository(db_session)
+    repo.upsert("c-live", status="generating", triggered_by="auto")
+    launched = []
+    monkeypatch.setattr(
+        intelligence_jobs,
+        "_launch_analysis",
+        lambda cid, *, triggered_by: launched.append((cid, triggered_by)),
+    )
+
+    intelligence_jobs.enqueue_campaign_analysis("c-live", triggered_by="manual", session=db_session)
+
+    row = repo.get_by_campaign("c-live")
+    assert row.status == "generating"
+    assert row.triggered_by == "auto"
+    assert launched == []
+
+
+def test_reenqueue_preserves_queued_comparison_context(db_session):
+    repo = CampaignPeriodComparisonRepository(db_session)
+    repo.enqueue("c-current", baseline_campaign_id="c-original", triggered_by="auto")
+
+    row = repo.enqueue("c-current", baseline_campaign_id="c-replacement", triggered_by="manual")
+
+    assert row.status == "queued"
+    assert row.baseline_campaign_id == "c-original"
+    assert row.triggered_by == "auto"
+
+
+@pytest.mark.parametrize(
+    ("repository", "enqueue_kwargs"),
+    [
+        (CampaignAnalysisRepository, {}),
+        (CampaignPeriodComparisonRepository, {"baseline_campaign_id": "c-base"}),
+    ],
+)
+def test_queued_recovery_is_bounded(db_session, repository, enqueue_kwargs):
+    repo = repository(db_session)
+    repo.enqueue("c-recover", triggered_by="auto", **enqueue_kwargs)
+
+    for expected_attempts in range(1, intelligence_jobs.MAX_QUEUED_RECOVERY_ATTEMPTS + 1):
+        recovered = repo.prepare_queued_recovery(
+            intelligence_jobs.MAX_QUEUED_RECOVERY_ATTEMPTS,
+            "recovery exhausted",
+        )
+        assert [row.campaign_id for row in recovered] == ["c-recover"]
+        assert repo.get_by_campaign("c-recover").recovery_attempts == expected_attempts
+
+    assert repo.prepare_queued_recovery(
+        intelligence_jobs.MAX_QUEUED_RECOVERY_ATTEMPTS,
+        "recovery exhausted",
+    ) == []
+    exhausted = repo.get_by_campaign("c-recover")
+    assert exhausted.status == "failed"
+    assert exhausted.error == "recovery exhausted"