feat(server): 重构知识库服务和路由配置，优化LLM维基知识管理接口，增强知识检索能力

server/src/app/api/v1/endpoints/knowledge.py

@@ -16,18 +16,19 @@ from app.schemas.knowledge import (
     KnowledgeActionResponse,
     KnowledgeDocumentDetailRead,
     KnowledgeLibraryRead,
-    LlmWikiDocumentDetailRead,
-    LlmWikiIndexRead,
-    LlmWikiSummaryUpdateWrite,
     KnowledgeOnlyOfficeCallbackRead,
     KnowledgeOnlyOfficeCallbackWrite,
     KnowledgeOnlyOfficeConfigRead,
-    LlmWikiSyncRead,
+    LlmWikiDocumentDetailRead,
+    LlmWikiIndexRead,
+    LlmWikiSyncTaskRead,
     LlmWikiSyncWrite,
+    LlmWikiSummaryUpdateWrite,
 )
 from app.services.agent_runs import AgentRunService
-from app.services.knowledge import KnowledgeService
+from app.services.knowledge import KNOWLEDGE_INGEST_STATUS_SYNCING, KnowledgeService
 from app.services.llm_wiki import LlmWikiService
+from app.services.llm_wiki_tasks import llm_wiki_task_manager
 
 router = APIRouter(prefix="/knowledge")
 
@@ -46,8 +47,9 @@ router = APIRouter(prefix="/knowledge")
 )
 def get_knowledge_library(
     _: Annotated[CurrentUserContext, Depends(get_current_user)],
+    db: Annotated[Session, Depends(get_db)],
 ) -> KnowledgeLibraryRead:
-    return KnowledgeService().list_library()
+    return KnowledgeService(db=db).list_library()
 
 
 @router.get(
@@ -140,9 +142,9 @@ def update_llm_wiki_document_summary(
 
 @router.post(
     "/llm-wiki/sync",
-    response_model=LlmWikiSyncRead,
+    response_model=LlmWikiSyncTaskRead,
-    summary="触发 Hermes 形成 LLM Wiki 与规则草稿",
+    summary="异步触发 Hermes 形成 LLM Wiki 与规则草稿",
-    description="按知识库文档变化情况增量触发系统 Hermes，形成知识候选和规则草稿。",
+    description="按知识库文档变化情况将系统 Hermes 归纳任务放入后台执行，并返回可追踪的 AgentRun 编号。",
     responses={
         status.HTTP_401_UNAUTHORIZED: {
             "model": ErrorResponse,
@@ -158,8 +160,15 @@ def sync_llm_wiki(
     payload: LlmWikiSyncWrite,
     current_user: Annotated[CurrentUserContext, Depends(require_admin_user)],
     db: Annotated[Session, Depends(get_db)],
-) -> LlmWikiSyncRead:
+) -> LlmWikiSyncTaskRead:
     run_service = AgentRunService(db)
+    knowledge_service = KnowledgeService(db=db)
+    requested_ids = {str(item).strip() for item in payload.document_ids if str(item).strip()}
+    target_document_ids = [
+        str(item.get("id") or "").strip()
+        for item in knowledge_service.list_folder_documents(folder=payload.folder)
+        if str(item.get("id") or "").strip() and (not requested_ids or str(item.get("id") or "").strip() in requested_ids)
+    ]
     task_asset = db.scalar(
         select(AgentAsset).where(AgentAsset.code == "task.hermes.llm_wiki_rule_formation")
     )
@@ -170,47 +179,52 @@ def sync_llm_wiki(
         task_id=task_asset.id if task_asset is not None else None,
         permission_level=AgentPermissionLevel.READ.value,
         status=AgentRunStatus.RUNNING.value,
-        result_summary="Hermes 正在形成 LLM Wiki 与规则草稿。",
+        result_summary="Hermes 归纳任务已入队，等待后台执行。",
+        route_json={
+            "job_type": "llm_wiki_sync",
+            "phase": "queued",
+            "folder": payload.folder,
+            "force": payload.force,
+            "requested_document_ids": target_document_ids,
+            "progress": {
+                "total_documents": len(target_document_ids),
+                "completed_documents": 0,
+                "failed_documents": 0,
+                "skipped_documents": 0,
+                "percent": 0,
+            },
+        },
     )
 
     try:
-        result = LlmWikiService(db).sync_folder(
+        if target_document_ids:
+            knowledge_service.set_document_ingest_statuses(
+                target_document_ids,
+                status_code=KNOWLEDGE_INGEST_STATUS_SYNCING,
+                agent_run_id=run.run_id,
+            )
+        llm_wiki_task_manager.submit_sync(
+            agent_run_id=run.run_id,
             folder=payload.folder,
             current_user=current_user,
-            document_ids=payload.document_ids,
+            document_ids=target_document_ids,
             force=payload.force,
         )
-        run_service.record_tool_call(
+        return LlmWikiSyncTaskRead(
-            run_id=run.run_id,
+            ok=True,
-            tool_type="llm",
+            agent_run_id=run.run_id,
-            tool_name="system_hermes_llm_wiki_sync",
+            folder=payload.folder,
-            request_json=payload.model_dump(),
+            document_ids=target_document_ids,
-            response_json=result.model_dump(),
+            queued_at=run.started_at,
-            status="succeeded",
+            status=run.status,
-            duration_ms=0,
+            summary="Hermes 已进入后台归纳，可在日志管理查看进度。",
         )
-        run_service.update_run(
-            run.run_id,
-            status=AgentRunStatus.SUCCEEDED.value,
-            result_summary=result.summary,
-            finished_at=datetime.now(UTC),
-        )
-        return result
     except Exception as exc:
-        run_service.record_tool_call(
-            run_id=run.run_id,
-            tool_type="llm",
-            tool_name="system_hermes_llm_wiki_sync",
-            request_json=payload.model_dump(),
-            response_json={"error": str(exc)},
-            status="failed",
-            duration_ms=0,
-            error_message=str(exc),
-        )
         run_service.update_run(
             run.run_id,
             status=AgentRunStatus.FAILED.value,
             error_message=str(exc),
+            result_summary=str(exc),
             finished_at=datetime.now(UTC),
         )
         if isinstance(exc, ValueError):
@@ -239,9 +253,10 @@ def sync_llm_wiki(
 def get_knowledge_document(
     document_id: str,
     _: Annotated[CurrentUserContext, Depends(get_current_user)],
+    db: Annotated[Session, Depends(get_db)],
 ) -> KnowledgeDocumentDetailRead:
     try:
-        return KnowledgeService().get_document_detail(document_id)
+        return KnowledgeService(db=db).get_document_detail(document_id)
     except FileNotFoundError as exc:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND,

server/src/app/api/v1/router.py

@@ -13,6 +13,7 @@ from app.api.v1.endpoints.ontology import router as ontology_router
 from app.api.v1.endpoints.orchestrator import router as orchestrator_router
 from app.api.v1.endpoints.reimbursements import router as reimbursements_router
 from app.api.v1.endpoints.settings import router as settings_router
+from app.api.v1.endpoints.system_logs import router as system_logs_router
 
 router = APIRouter()
 router.include_router(health_router, tags=["health"])
@@ -28,3 +29,4 @@ router.include_router(orchestrator_router, tags=["orchestrator"])
 router.include_router(employees_router, prefix="/employees", tags=["employees"])
 router.include_router(reimbursements_router, prefix="/reimbursements", tags=["reimbursements"])
 router.include_router(settings_router, tags=["settings"])
+router.include_router(system_logs_router, tags=["system-logs"])

server/src/app/main.py

@@ -15,6 +15,7 @@ from app.schemas.common import RootStatusRead
 from app.services.agent_foundation import prepare_agent_foundation
 from app.services.employee import prepare_employee_directory
 from app.services.knowledge import prepare_knowledge_library
+from app.services.llm_wiki_tasks import llm_wiki_task_manager
 
 
 @asynccontextmanager
@@ -32,6 +33,7 @@ async def lifespan(_: FastAPI) -> AsyncIterator[None]:
         settings.api_v1_prefix,
     )
     yield
+    llm_wiki_task_manager.shutdown()
 
 
 def create_app() -> FastAPI:

server/src/app/schemas/knowledge.py

@@ -193,5 +193,15 @@ class LlmWikiSyncRead(BaseModel):
     summary: str = ""
 
 
+class LlmWikiSyncTaskRead(BaseModel):
+    ok: bool = True
+    agent_run_id: str
+    folder: str
+    document_ids: list[str] = Field(default_factory=list)
+    queued_at: datetime
+    status: str = "running"
+    summary: str = ""
+
+
 class LlmWikiSummaryUpdateWrite(BaseModel):
     knowledge_summary_markdown: str = Field(min_length=1)

server/src/app/services/knowledge.py

@@ -16,10 +16,14 @@ from xml.etree import ElementTree
 from zipfile import BadZipFile, ZipFile
 
 import jwt
+from sqlalchemy import select
+from sqlalchemy.orm import Session
 
 from app.api.deps import CurrentUserContext
+from app.core.agent_enums import AgentRunStatus
 from app.core.config import get_settings
 from app.core.logging import get_logger
+from app.models.agent_run import AgentRun
 from app.schemas.knowledge import (
     KnowledgeDocumentDetailRead,
     KnowledgeDocumentRead,
@@ -94,8 +98,9 @@ def prepare_knowledge_library() -> None:
 
 
 class KnowledgeService:
-    def __init__(self, storage_root: Path | None = None) -> None:
+    def __init__(self, storage_root: Path | None = None, db: Session | None = None) -> None:
         settings = get_settings()
+        self.db = db
         self.storage_root = Path(storage_root or settings.resolved_storage_root_dir)
         self.library_root = self.storage_root / "knowledge"
         self.index_path = self.library_root / ".index.json"
@@ -147,7 +152,8 @@ class KnowledgeService:
             self._save_index(index)
         entry = self._require_entry(index, document_id)
         preview_kind, preview_pages = self._build_preview(entry)
-        document = self._serialize_document(entry)
+        wiki_document = self._build_wiki_document_map().get(str(document_id).strip())
+        document = self._serialize_document(entry, wiki_document=wiki_document)
         return KnowledgeDocumentDetailRead(
             **document.model_dump(),
             previewKind=preview_kind,
@@ -210,6 +216,7 @@ class KnowledgeService:
                 "uploaded_by": current_user.name,
                 "version_number": 1,
                 "ingest_status": KNOWLEDGE_INGEST_STATUS_PUBLISHED,
+                "ingest_agent_run_id": "",
             }
             index["documents"].append(entry)
             logger.info(
@@ -231,6 +238,7 @@ class KnowledgeService:
                     "uploaded_by": current_user.name,
                     "version_number": int(existing_entry.get("version_number", 1)) + 1,
                     "ingest_status": KNOWLEDGE_INGEST_STATUS_PUBLISHED,
+                    "ingest_agent_run_id": "",
                 }
             )
             entry = existing_entry
@@ -286,7 +294,13 @@ class KnowledgeService:
             self._save_index(index)
         return dict(self._require_entry(index, document_id))
 
-    def set_document_ingest_statuses(self, document_ids: list[str], status_code: int) -> None:
+    def set_document_ingest_statuses(
+        self,
+        document_ids: list[str],
+        status_code: int,
+        *,
+        agent_run_id: str | None = None,
+    ) -> None:
         self.ensure_library_ready()
         normalized_ids = {str(item).strip() for item in document_ids if str(item).strip()}
         if not normalized_ids:
@@ -299,9 +313,15 @@ class KnowledgeService:
             if str(entry.get("id") or "").strip() not in normalized_ids:
                 continue
             if self._normalize_ingest_status_code(entry.get("ingest_status")) == status_code:
+                if agent_run_id is not None and entry.get("ingest_agent_run_id") != agent_run_id:
+                    entry["ingest_agent_run_id"] = agent_run_id
+                    entry["ingest_status_updated_at"] = updated_at
+                    changed = True
                 continue
             entry["ingest_status"] = status_code
             entry["ingest_status_updated_at"] = updated_at
+            if agent_run_id is not None:
+                entry["ingest_agent_run_id"] = agent_run_id
             changed = True
 
         if changed:
@@ -703,6 +723,9 @@ class KnowledgeService:
                 if item.get("ingest_status") != normalized_status:
                     item["ingest_status"] = normalized_status
                     changed = True
+                if "ingest_agent_run_id" not in item:
+                    item["ingest_agent_run_id"] = ""
+                    changed = True
                 existing_items.append(item)
             else:
                 changed = True
@@ -735,6 +758,7 @@ class KnowledgeService:
                         "uploaded_by": "系统导入",
                         "version_number": 1,
                         "ingest_status": KNOWLEDGE_INGEST_STATUS_PUBLISHED,
+                        "ingest_agent_run_id": "",
                     }
                 )
                 changed = True
@@ -773,7 +797,7 @@ class KnowledgeService:
             if (
                 current_status == KNOWLEDGE_INGEST_STATUS_SYNCING
                 and preserve_syncing
-                and not self._is_syncing_status_stale(entry)
+                and self._should_preserve_syncing_status(entry)
             ):
                 continue
 
@@ -881,6 +905,24 @@ class KnowledgeService:
         age_seconds = (datetime.now(UTC) - updated_at.astimezone(UTC)).total_seconds()
         return age_seconds >= KNOWLEDGE_INGEST_SYNC_STALE_SECONDS
 
+    def _should_preserve_syncing_status(self, entry: dict[str, Any]) -> bool:
+        agent_run_id = str(entry.get("ingest_agent_run_id") or "").strip()
+        if not agent_run_id or self.db is None:
+            return not self._is_syncing_status_stale(entry)
+
+        run = self.db.scalar(select(AgentRun).where(AgentRun.run_id == agent_run_id))
+        if run is None:
+            return not self._is_syncing_status_stale(entry)
+        if run.status != AgentRunStatus.RUNNING.value:
+            return False
+
+        heartbeat_at = str((run.route_json or {}).get("heartbeat_at") or "").strip()
+        if heartbeat_at:
+            probe_entry = {"ingest_status_updated_at": heartbeat_at}
+            return not self._is_syncing_status_stale(probe_entry)
+
+        return not self._is_syncing_status_stale(entry)
+
     def _require_entry(self, index: dict[str, Any], document_id: str) -> dict[str, Any]:
         for entry in index["documents"]:
             if entry["id"] == document_id:

server/src/app/services/llm_wiki.py

@@ -8,7 +8,7 @@ from dataclasses import dataclass
 from datetime import UTC, datetime
 from decimal import Decimal
 from pathlib import Path
-from typing import Any, Literal
+from typing import Any, Callable, Literal
 from uuid import uuid4
 
 from pydantic import BaseModel, ConfigDict, Field, ValidationError, model_validator
@@ -47,7 +47,8 @@ from app.services.system_hermes import SystemHermesService
 logger = get_logger("app.services.llm_wiki")
 
 HERMES_CANDIDATE_MODEL_TIMEOUT_SECONDS = 10
-HERMES_CANDIDATE_GROUP_SIZE = 3
+HERMES_CANDIDATE_GROUP_SIZE = 2
+HERMES_CANDIDATE_CONTENT_LIMIT = 520
 LOW_SIGNAL_DOTTED_LINE_PATTERN = re.compile(r"[.．。·•]{6,}\s*[0-9]{0,3}$")
 PAGE_FOOTER_PATTERN = re.compile(r"^第\s*\d+\s*页\s*共\s*\d+\s*页$")
 POLICY_SUBSTANCE_KEYWORDS = (
@@ -412,6 +413,8 @@ class LlmWikiService:
         current_user: CurrentUserContext,
         document_ids: list[str] | None = None,
         force: bool = False,
+        agent_run_id: str | None = None,
+        progress_callback: Callable[[dict[str, Any], str], None] | None = None,
     ) -> LlmWikiSyncRead:
         self.knowledge_service.ensure_library_ready()
         documents = self.knowledge_service.list_folder_documents(folder=folder)
@@ -427,6 +430,7 @@ class LlmWikiService:
             self.knowledge_service.set_document_ingest_statuses(
                 target_document_ids,
                 status_code=KNOWLEDGE_INGEST_STATUS_SYNCING,
+                agent_run_id=agent_run_id,
             )
 
         try:
@@ -441,9 +445,27 @@ class LlmWikiService:
             rule_candidate_count = 0
             generated_rule_asset_ids: list[str] = []
             changed_document_count = 0
+            skipped_document_count = 0
             sync_summaries: list[str] = []
+            failed_document_ids: list[str] = []
+            total_documents = len(documents)
 
-            for entry in documents:
+            self._emit_progress(
+                progress_callback,
+                {
+                    "phase": "running",
+                    "progress": {
+                        "total_documents": total_documents,
+                        "completed_documents": 0,
+                        "failed_documents": 0,
+                        "skipped_documents": 0,
+                        "percent": 0,
+                    },
+                },
+                f"Hermes 已开始归纳，待处理文档 {total_documents} 个。",
+            )
+
+            for index_value, entry in enumerate(documents, start=1):
                 document_id = str(entry.get("id") or "").strip()
                 if not document_id:
                     continue
@@ -451,15 +473,85 @@ class LlmWikiService:
                 existing = existing_by_id.get(document_id)
                 sync_reason = self._resolve_sync_reason(entry=entry, existing=existing, force=force)
                 if sync_reason == "unchanged_skipped":
+                    skipped_document_count += 1
                     sync_summaries.append(f"{entry['original_name']}：未变化，跳过。")
+                    self._emit_progress(
+                        progress_callback,
+                        {
+                            "phase": "running",
+                            "progress": {
+                                "total_documents": total_documents,
+                                "completed_documents": changed_document_count,
+                                "failed_documents": len(failed_document_ids),
+                                "skipped_documents": skipped_document_count,
+                                "current_document_index": index_value,
+                                "current_document_id": document_id,
+                                "current_document_name": entry["original_name"],
+                                "current_stage": "skipped",
+                                "percent": self._calculate_progress_percent(
+                                    completed_documents=changed_document_count,
+                                    skipped_documents=skipped_document_count,
+                                    total_documents=total_documents,
+                                ),
+                            },
+                        },
+                        f"《{entry['original_name']}》未变化，跳过本次归纳。",
+                    )
                     continue
 
+                self._emit_progress(
+                    progress_callback,
+                    {
+                        "phase": "running",
+                        "progress": {
+                            "total_documents": total_documents,
+                            "completed_documents": changed_document_count,
+                            "failed_documents": len(failed_document_ids),
+                            "skipped_documents": skipped_document_count,
+                            "current_document_index": index_value,
+                            "current_document_id": document_id,
+                            "current_document_name": entry["original_name"],
+                            "current_stage": "document_started",
+                            "percent": self._calculate_progress_percent(
+                                completed_documents=changed_document_count,
+                                skipped_documents=skipped_document_count,
+                                total_documents=total_documents,
+                            ),
+                        },
+                    },
+                    f"Hermes 正在归纳《{entry['original_name']}》。",
+                )
+
                 changed_document_count += 1
                 document_payload = self._sync_single_document(
                     entry=entry,
                     folder=folder,
                     current_user=current_user,
                     sync_reason=sync_reason,
+                    progress_callback=lambda payload, summary, *, document_id=document_id, document_name=entry["original_name"], document_index=index_value: self._emit_progress(
+                        progress_callback,
+                        {
+                            "phase": "running",
+                            "progress": {
+                                "total_documents": total_documents,
+                                "completed_documents": max(changed_document_count - 1, 0),
+                                "failed_documents": len(failed_document_ids),
+                                "skipped_documents": skipped_document_count,
+                                "current_document_index": document_index,
+                                "current_document_id": document_id,
+                                "current_document_name": document_name,
+                                **payload,
+                                "percent": self._calculate_progress_percent(
+                                    completed_documents=max(changed_document_count - 1, 0),
+                                    skipped_documents=skipped_document_count,
+                                    total_documents=total_documents,
+                                    group_count=int(payload.get("group_count") or 0),
+                                    current_group_index=int(payload.get("current_group_index") or 0),
+                                ),
+                            },
+                        },
+                        summary,
+                    ),
                 )
                 existing_by_id[document_id] = document_payload["document"]
                 knowledge_candidate_count += len(document_payload["knowledge_candidates"])
@@ -471,13 +563,47 @@ class LlmWikiService:
                         if str(item.get("generated_asset_id") or "").strip()
                     ]
                 )
+                if document_payload["document"].get("quality_status") in {"fallback_only", "runtime_only", "failed"}:
+                    failed_document_ids.append(document_id)
                 sync_summaries.append(
                     f"{entry['original_name']}：{sync_reason}，知识候选 {len(document_payload['knowledge_candidates'])} 条，"
-                    f"规则候选 {len(document_payload['rule_candidates'])} 条。"
+                    f"规则候选 {len(document_payload['rule_candidates'])} 条，"
+                    f"归纳质量 {document_payload['document'].get('quality_status') or 'formal'}。"
+                )
+                self._emit_progress(
+                    progress_callback,
+                    {
+                        "phase": "running",
+                        "progress": {
+                            "total_documents": total_documents,
+                            "completed_documents": changed_document_count,
+                            "failed_documents": len(failed_document_ids),
+                            "skipped_documents": skipped_document_count,
+                            "current_document_index": index_value,
+                            "current_document_id": document_id,
+                            "current_document_name": entry["original_name"],
+                            "current_stage": "document_completed",
+                            "knowledge_candidate_count": len(document_payload["knowledge_candidates"]),
+                            "rule_candidate_count": len(document_payload["rule_candidates"]),
+                            "quality_status": document_payload["document"].get("quality_status") or "formal",
+                            "percent": self._calculate_progress_percent(
+                                completed_documents=changed_document_count,
+                                skipped_documents=skipped_document_count,
+                                total_documents=total_documents,
+                            ),
+                        },
+                    },
+                    f"《{entry['original_name']}》归纳完成，质量状态为 {document_payload['document'].get('quality_status') or 'formal'}。",
                 )
 
             index["documents"] = list(existing_by_id.values())
             self._write_json_file(self.knowledge_service.llm_wiki_index_path, index)
+            if failed_document_ids:
+                self.knowledge_service.set_document_ingest_statuses(
+                    failed_document_ids,
+                    status_code=KNOWLEDGE_INGEST_STATUS_FAILED,
+                    agent_run_id=agent_run_id,
+                )
 
             sync_runs.setdefault("runs", [])
             sync_runs["runs"].append(
@@ -502,6 +628,22 @@ class LlmWikiService:
 
             generated_rule_ids = list(dict.fromkeys(generated_rule_asset_ids))
             summary = "；".join(sync_summaries) if sync_summaries else "未发现需要同步的知识文档。"
+            self._emit_progress(
+                progress_callback,
+                {
+                    "phase": "running",
+                    "progress": {
+                        "total_documents": total_documents,
+                        "completed_documents": changed_document_count,
+                        "failed_documents": len(failed_document_ids),
+                        "skipped_documents": skipped_document_count,
+                        "knowledge_candidate_count": knowledge_candidate_count,
+                        "rule_candidate_count": rule_candidate_count,
+                        "percent": 100,
+                    },
+                },
+                summary,
+            )
             return LlmWikiSyncRead(
                 ok=True,
                 run_id=run_id,
@@ -518,6 +660,7 @@ class LlmWikiService:
                 self.knowledge_service.set_document_ingest_statuses(
                     target_document_ids,
                     status_code=KNOWLEDGE_INGEST_STATUS_FAILED,
+                    agent_run_id=agent_run_id,
                 )
             raise
 
@@ -528,6 +671,7 @@ class LlmWikiService:
         folder: str,
         current_user: CurrentUserContext,
         sync_reason: str,
+        progress_callback: Callable[[dict[str, Any], str], None] | None = None,
     ) -> dict[str, Any]:
         document_id = str(entry["id"])
         document_name = str(entry["original_name"])
@@ -539,10 +683,19 @@ class LlmWikiService:
         text_path.write_text(extracted_text, encoding="utf-8")
 
         chunks = self._build_chunks(document_id=document_id, text=extracted_text)
-        knowledge_candidates, rule_candidates = self._extract_candidates(
+        self._emit_progress(
+            progress_callback,
+            {
+                "current_stage": "text_extracted",
+                "chunk_count": len(chunks),
+            },
+            f"《{document_name}》文本提取完成，共形成 {len(chunks)} 个分块。",
+        )
+        knowledge_candidates, rule_candidates, extraction_stats = self._extract_candidates(
             entry=entry,
             chunks=chunks,
             current_user=current_user,
+            progress_callback=progress_callback,
         )
 
         generated_candidates: list[dict[str, Any]] = []
@@ -563,8 +716,17 @@ class LlmWikiService:
             "checksum": str(entry.get("sha256") or ""),
             "extracted_text_path": str(text_path),
             "chunk_count": len(chunks),
+            "candidate_chunk_count": extraction_stats.candidate_chunk_count,
+            "filtered_chunk_count": extraction_stats.filtered_chunk_count,
+            "group_count": extraction_stats.group_count,
+            "successful_group_count": extraction_stats.successful_group_count,
+            "failed_group_count": extraction_stats.failed_group_count,
             "knowledge_candidate_count": len(knowledge_candidates),
+            "formal_knowledge_candidate_count": extraction_stats.formal_knowledge_candidate_count,
+            "fallback_knowledge_candidate_count": extraction_stats.fallback_knowledge_candidate_count,
             "rule_candidate_count": len(generated_candidates),
+            "quality_status": extraction_stats.quality_status,
+            "quality_note": extraction_stats.quality_note,
             "updated_at": datetime.now(UTC).isoformat(),
             "signature": self._build_document_signature(entry),
             "sync_reason": sync_reason,
@@ -593,49 +755,147 @@ class LlmWikiService:
         entry: dict[str, Any],
         chunks: list[dict[str, Any]],
         current_user: CurrentUserContext,
-    ) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
+        progress_callback: Callable[[dict[str, Any], str], None] | None = None,
+    ) -> tuple[list[dict[str, Any]], list[dict[str, Any]], CandidateExtractionStats]:
+        stats = CandidateExtractionStats(raw_chunk_count=len(chunks))
         if not chunks:
-            return [], []
+            stats.quality_status = "failed"
+            stats.quality_note = "文档未提取到可用分块，无法形成 LLM Wiki。"
+            return [], [], stats
+
+        candidate_chunks = self._select_candidate_chunks(chunks)
+        stats.candidate_chunk_count = len(candidate_chunks)
+        stats.filtered_chunk_count = max(0, len(chunks) - len(candidate_chunks))
+        if not candidate_chunks:
+            stats.quality_status = "failed"
+            stats.quality_note = "正文条款分块为空，当前仅识别到封面、目录或低信息量内容，未形成正式归纳。"
+            return [], [], stats
+
+        projected_group_count = len(self._group_chunks(candidate_chunks, size=HERMES_CANDIDATE_GROUP_SIZE))
+        self._emit_progress(
+            progress_callback,
+            {
+                "current_stage": "candidate_chunks_selected",
+                "candidate_chunk_count": stats.candidate_chunk_count,
+                "filtered_chunk_count": stats.filtered_chunk_count,
+                "group_count": projected_group_count,
+                "current_group_index": 0,
+                "successful_group_count": 0,
+                "failed_group_count": 0,
+            },
+            f"《{entry['original_name']}》已筛出 {stats.candidate_chunk_count} 个有效正文分块，准备分 {projected_group_count} 组归纳。",
+        )
 
         knowledge_candidates: list[dict[str, Any]] = []
         rule_candidates: list[dict[str, Any]] = []
         seen_knowledge_keys: set[str] = set()
         seen_rule_keys: set[str] = set()
 
-        for chunk_group in self._group_chunks(chunks, size=4):
+        for chunk_group in self._group_chunks(candidate_chunks, size=HERMES_CANDIDATE_GROUP_SIZE):
-            payload = self._call_candidate_model(entry=entry, chunk_group=chunk_group)
+            stats.group_count += 1
+            attempt = self._call_candidate_model(entry=entry, chunk_group=chunk_group)
+            if isinstance(attempt, dict):
+                attempt = CandidateModelAttempt(payload=attempt, source="hermes", ok=True)
+            if not attempt.ok:
+                stats.failed_group_count += 1
+                self._emit_progress(
+                    progress_callback,
+                    {
+                        "current_stage": "extracting_candidates",
+                        "group_count": projected_group_count,
+                        "current_group_index": stats.group_count,
+                        "successful_group_count": stats.successful_group_count,
+                        "failed_group_count": stats.failed_group_count,
+                    },
+                    f"《{entry['original_name']}》第 {stats.group_count}/{projected_group_count} 组归纳失败，继续处理下一组。",
+                )
+                continue
+
+            stats.successful_group_count += 1
             batch_knowledge = self._normalize_knowledge_candidates(
-                raw_items=list(payload.get("knowledge_candidates") or []),
+                raw_items=list(attempt.payload.get("knowledge_candidates") or []),
                 entry=entry,
                 chunk_group=chunk_group,
                 seen_keys=seen_knowledge_keys,
+                extraction_mode=attempt.source,
             )
-            batch_rules = self._normalize_rule_candidates(
+            batch_rules: list[dict[str, Any]] = []
-                raw_items=list(payload.get("rule_candidates") or []),
+            if attempt.source == "hermes":
-                entry=entry,
+                batch_rules = self._normalize_rule_candidates(
-                chunk_group=chunk_group,
+                    raw_items=list(attempt.payload.get("rule_candidates") or []),
-                current_user=current_user,
+                    entry=entry,
-                seen_keys=seen_rule_keys,
+                    chunk_group=chunk_group,
-            )
+                    current_user=current_user,
+                    seen_keys=seen_rule_keys,
+                )
             knowledge_candidates.extend(batch_knowledge)
             rule_candidates.extend(batch_rules)
+            self._emit_progress(
+                progress_callback,
+                {
+                    "current_stage": "extracting_candidates",
+                    "group_count": projected_group_count,
+                    "current_group_index": stats.group_count,
+                    "successful_group_count": stats.successful_group_count,
+                    "failed_group_count": stats.failed_group_count,
+                    "knowledge_candidate_count": len(knowledge_candidates),
+                    "rule_candidate_count": len(rule_candidates),
+                },
+                f"《{entry['original_name']}》已完成第 {stats.group_count}/{projected_group_count} 组归纳。",
+            )
 
-        if not knowledge_candidates:
+        formal_knowledge_candidate_count = sum(
-            fallback = self._build_fallback_knowledge_candidate(entry=entry, chunks=chunks)
+            1 for item in knowledge_candidates if str(item.get("extraction_mode") or "hermes") == "hermes"
+        )
+        if formal_knowledge_candidate_count <= 0:
+            fallback = self._build_fallback_knowledge_candidate(
+                entry=entry,
+                chunks=candidate_chunks,
+                reason=(
+                    "Hermes 未能从正文条款中形成正式知识候选。当前结果仅为降级兜底预览，不能视为正式归纳。"
+                ),
+            )
             if fallback is not None:
                 knowledge_candidates.append(fallback)
 
-        return knowledge_candidates[:12], rule_candidates[:12]
+        truncated_knowledge_candidates = knowledge_candidates[:12]
+        truncated_rule_candidates = rule_candidates[:12]
+        stats.formal_knowledge_candidate_count = sum(
+            1 for item in truncated_knowledge_candidates if str(item.get("extraction_mode") or "hermes") == "hermes"
+        )
+        stats.fallback_knowledge_candidate_count = max(
+            0,
+            len(truncated_knowledge_candidates) - stats.formal_knowledge_candidate_count,
+        )
+        stats.quality_status, stats.quality_note = self._resolve_quality_status(
+            stats=stats,
+            knowledge_candidates=truncated_knowledge_candidates,
+        )
+        self._emit_progress(
+            progress_callback,
+            {
+                "current_stage": "candidate_extraction_completed",
+                "group_count": projected_group_count,
+                "current_group_index": projected_group_count,
+                "successful_group_count": stats.successful_group_count,
+                "failed_group_count": stats.failed_group_count,
+                "knowledge_candidate_count": len(truncated_knowledge_candidates),
+                "formal_knowledge_candidate_count": stats.formal_knowledge_candidate_count,
+                "fallback_knowledge_candidate_count": stats.fallback_knowledge_candidate_count,
+                "rule_candidate_count": len(truncated_rule_candidates),
+                "quality_status": stats.quality_status,
+            },
+            f"《{entry['original_name']}》候选提炼完成，质量状态为 {stats.quality_status}。",
+        )
+
+        return truncated_knowledge_candidates, truncated_rule_candidates, stats
 
     def _call_candidate_model(
         self,
         *,
         entry: dict[str, Any],
         chunk_group: list[dict[str, Any]],
-    ) -> dict[str, Any]:
+    ) -> CandidateModelAttempt:
-        if self._candidate_model_disabled:
-            return {}
-
         facts = {
             "document_id": entry["id"],
             "document_name": entry["original_name"],
@@ -653,7 +913,7 @@ class LlmWikiService:
                 {
                     "chunk_id": item["chunk_id"],
                     "title": item["title"],
-                    "content": item["content"][:900],
+                    "content": item["content"][:HERMES_CANDIDATE_CONTENT_LIMIT],
                     "source_page": item.get("source_page"),
                     "tags": item.get("tags", []),
                 }
@@ -663,6 +923,8 @@ class LlmWikiService:
         system_prompt = (
             "你是企业财务制度知识库的 Hermes 规则形成器。"
             "你只能基于提供的制度条款生成结构化知识候选和规则候选，不能自由发散。"
+            "封面、目录、通知、页眉页脚、密级说明、印发信息不属于知识候选，必须忽略。"
+            "只提炼具有执行意义、审核意义、报销约束意义的条款。"
             "规则候选必须从允许模板中选 template_key，严禁自创模板。"
             "runtime_rule 必须严格遵守 runtime_rule_contracts 中对应模板的字段结构和允许值。"
             "如果条款不适合自动规则化，可以只返回 knowledge_candidates。"
@@ -675,6 +937,7 @@ class LlmWikiService:
         )
         user_prompt = (
             "请根据以下制度分块生成候选。"
+            "每组最多提炼 3 条高价值 knowledge_candidates，优先保留可直接供报销审核、附件校验、审批判断使用的知识。"
             "只返回 JSON 对象，不要输出解释，不要调用工具，不要追加任何其他文本。\n"
             f"{json.dumps(facts, ensure_ascii=False, indent=2)}"
         )
@@ -693,29 +956,44 @@ class LlmWikiService:
                     timeout_seconds=HERMES_CANDIDATE_MODEL_TIMEOUT_SECONDS,
                 )
                 payload = self._extract_json_payload(cli_result.response_text)
-                if payload:
+                if payload is not None:
-                    return payload
+                    return CandidateModelAttempt(payload=payload, source="hermes", ok=True)
-                self._candidate_model_disabled = True
                 logger.warning(
-                    "System Hermes returned no parseable JSON for LLM Wiki doc=%s; using fallback candidates.",
+                    "System Hermes returned no parseable JSON for LLM Wiki doc=%s chunk_group=%s.",
                     entry.get("id"),
+                    ",".join(item.get("chunk_id", "") for item in chunk_group),
+                )
+                return CandidateModelAttempt(
+                    payload={},
+                    source="hermes",
+                    ok=False,
+                    failure_reason="system_hermes_no_json",
                 )
-                return {}
             except TimeoutExpired:
-                self._candidate_model_disabled = True
                 logger.warning(
-                    "System Hermes timed out during LLM Wiki candidate extraction doc=%s; using fallback candidates.",
+                    "System Hermes timed out during LLM Wiki candidate extraction doc=%s chunk_group=%s.",
                     entry.get("id"),
+                    ",".join(item.get("chunk_id", "") for item in chunk_group),
+                )
+                return CandidateModelAttempt(
+                    payload={},
+                    source="hermes",
+                    ok=False,
+                    failure_reason="system_hermes_timeout",
                 )
-                return {}
             except Exception as exc:
-                self._candidate_model_disabled = True
                 logger.warning(
-                    "System Hermes failed during LLM Wiki candidate extraction doc=%s: %s",
+                    "System Hermes failed during LLM Wiki candidate extraction doc=%s chunk_group=%s: %s",
                     entry.get("id"),
+                    ",".join(item.get("chunk_id", "") for item in chunk_group),
                     exc,
                 )
-                return {}
+                return CandidateModelAttempt(
+                    payload={},
+                    source="hermes",
+                    ok=False,
+                    failure_reason=str(exc) or "system_hermes_failed",
+                )
 
         response_text = self.runtime_chat_service.complete(
             [
@@ -727,10 +1005,129 @@ class LlmWikiService:
             temperature=0.0,
         )
         payload = self._extract_json_payload(response_text)
-        if not payload:
+        if payload is None:
-            self._candidate_model_disabled = True
+            return CandidateModelAttempt(
-            return {}
+                payload={},
-        return payload
+                source="runtime",
+                ok=False,
+                failure_reason="runtime_no_json",
+            )
+        return CandidateModelAttempt(
+            payload=payload,
+            source="runtime",
+            ok=True,
+            failure_reason="system_hermes_unavailable",
+        )
+
+    def _select_candidate_chunks(self, chunks: list[dict[str, Any]]) -> list[dict[str, Any]]:
+        selected: list[dict[str, Any]] = []
+        for chunk in chunks:
+            if self._is_low_signal_chunk(chunk):
+                continue
+            selected.append(chunk)
+        return selected
+
+    def _is_low_signal_chunk(self, chunk: dict[str, Any]) -> bool:
+        title = str(chunk.get("title") or "").strip()
+        content = str(chunk.get("content") or "").strip()
+        page = int(chunk.get("source_page") or 0)
+        if not content:
+            return True
+        if self._looks_like_table_of_contents(title=title, content=content):
+            return True
+        if self._looks_like_cover_notice(title=title, content=content, source_page=page):
+            return True
+
+        compact_content = re.sub(r"\s+", "", content)
+        if len(compact_content) < 24 and not self._has_policy_substance(content):
+            return True
+        if title.startswith("附件") and len(compact_content) < 40:
+            return True
+        return False
+
+    def _is_low_signal_candidate(self, *, title: str, content: str) -> bool:
+        compact_content = re.sub(r"\s+", "", content)
+        if len(compact_content) < 24 and not self._has_policy_substance(content):
+            return True
+        if self._looks_like_table_of_contents(title=title, content=content):
+            return True
+        if self._looks_like_cover_notice(title=title, content=content, source_page=0):
+            return True
+        return False
+
+    @staticmethod
+    def _has_policy_substance(text: str) -> bool:
+        sample = str(text or "")
+        return any(keyword in sample for keyword in POLICY_SUBSTANCE_KEYWORDS)
+
+    @staticmethod
+    def _looks_like_table_of_contents(*, title: str, content: str) -> bool:
+        title_text = str(title or "").strip()
+        content_text = str(content or "").strip()
+        if title_text == "目录" or content_text == "目录":
+            return True
+
+        lines = [line.strip() for line in content_text.splitlines() if line.strip()]
+        if lines and sum(1 for line in lines if LOW_SIGNAL_DOTTED_LINE_PATTERN.search(line)) >= max(2, len(lines) // 2):
+            return True
+
+        if LOW_SIGNAL_DOTTED_LINE_PATTERN.search(content_text) and "第" in title_text:
+            return True
+        return False
+
+    def _looks_like_cover_notice(self, *, title: str, content: str, source_page: int) -> bool:
+        text = f"{title}\n{content}"
+        if PAGE_FOOTER_PATTERN.fullmatch(str(content or "").strip()):
+            return True
+        cover_keywords = ("关于颁布", "特此通知", "印发", "商密", "制度〔", "有限公司文件", "通知")
+        if source_page == 1 and any(keyword in text for keyword in cover_keywords):
+            return True
+        if source_page > 2:
+            return False
+        if any(keyword in text for keyword in cover_keywords):
+            if "必须" not in text and "应当" not in text and "不得" not in text:
+                return True
+        return False
+
+    def _resolve_quality_status(
+        self,
+        *,
+        stats: CandidateExtractionStats,
+        knowledge_candidates: list[dict[str, Any]],
+    ) -> tuple[str, str]:
+        if stats.formal_knowledge_candidate_count <= 0:
+            runtime_count = sum(
+                1 for item in knowledge_candidates if str(item.get("extraction_mode") or "") == "runtime"
+            )
+            if runtime_count > 0:
+                return (
+                    "runtime_only",
+                    "当前知识候选来自运行时模型而非系统 Hermes，仅供人工参考，不计入正式归纳。",
+                )
+            if stats.fallback_knowledge_candidate_count > 0:
+                return (
+                    "fallback_only",
+                    "Hermes 未形成正式知识候选，当前仅保留降级兜底预览，不能作为正式知识上线。",
+                )
+            return (
+                "failed",
+                "Hermes 未能从当前文档提炼出可用知识候选，请调整文档内容或重新归纳。",
+            )
+
+        if stats.failed_group_count > 0:
+            return (
+                "partial_degraded",
+                f"Hermes 成功处理 {stats.successful_group_count}/{stats.group_count} 个分组，"
+                f"仍有 {stats.failed_group_count} 个分组未成功，请人工复核后再使用。",
+            )
+
+        if stats.filtered_chunk_count > 0:
+            return (
+                "formal",
+                f"已自动过滤 {stats.filtered_chunk_count} 个封面、目录或低信息量分块，当前结果来自正文条款。",
+            )
+
+        return ("formal", "Hermes 已基于正文条款完成正式归纳。")
 
     def _normalize_knowledge_candidates(
         self,
@@ -739,6 +1136,7 @@ class LlmWikiService:
         entry: dict[str, Any],
         chunk_group: list[dict[str, Any]],
         seen_keys: set[str],
+        extraction_mode: str,
     ) -> list[dict[str, Any]]:
         normalized: list[dict[str, Any]] = []
         default_chunk_ids = [item["chunk_id"] for item in chunk_group]
@@ -750,10 +1148,17 @@ class LlmWikiService:
             content = str(item.get("content") or "").strip()
             if not title or not content:
                 continue
+            if self._is_low_signal_candidate(title=title, content=content):
+                continue
             candidate_key = f"{title.casefold()}::{content[:80].casefold()}"
             if candidate_key in seen_keys:
                 continue
             seen_keys.add(candidate_key)
+            quality_flags: list[str] = []
+            fallback_reason = ""
+            if extraction_mode != "hermes":
+                quality_flags.append("non_hermes_source")
+                fallback_reason = "当前知识候选不是由系统 Hermes 正式提炼，不能视为正式归纳。"
             normalized.append(
                 {
                     "candidate_id": f"kc_{uuid4().hex[:12]}",
@@ -775,6 +1180,9 @@ class LlmWikiService:
                     "status": "draft",
                     "created_by": "hermes",
                     "created_at": datetime.now(UTC).isoformat(),
+                    "extraction_mode": extraction_mode,
+                    "quality_flags": quality_flags,
+                    "fallback_reason": fallback_reason,
                 }
             )
         return normalized
@@ -1218,6 +1626,7 @@ class LlmWikiService:
         *,
         entry: dict[str, Any],
         chunks: list[dict[str, Any]],
+        reason: str,
     ) -> dict[str, Any] | None:
         first_chunk = next((item for item in chunks if str(item.get("content") or "").strip()), None)
         if first_chunk is None:
@@ -1244,6 +1653,9 @@ class LlmWikiService:
             "status": "draft",
             "created_by": "hermes",
             "created_at": datetime.now(UTC).isoformat(),
+            "extraction_mode": "fallback",
+            "quality_flags": ["fallback_only", "not_formal_ingest"],
+            "fallback_reason": reason,
         }
 
     @staticmethod
@@ -1266,10 +1678,38 @@ class LlmWikiService:
             f"- 来源文档：{document_name}",
             f"- 知识条目数：{len(knowledge_candidates)}",
             "",
-            "## 核心知识",
-            "",
         ]
 
+        quality_status = str(entry.get("quality_status") or "formal").strip() or "formal"
+        quality_note = str(entry.get("quality_note") or "").strip()
+        if quality_status != "formal":
+            lines.extend(
+                [
+                    "## 归纳状态",
+                    "",
+                    f"- 质量状态：{quality_status}",
+                    f"- 说明：{quality_note or '当前结果不是正式 Hermes 归纳。'}",
+                    "",
+                ]
+            )
+        elif quality_note:
+            lines.extend(
+                [
+                    "## 归纳状态",
+                    "",
+                    f"- 质量状态：{quality_status}",
+                    f"- 说明：{quality_note}",
+                    "",
+                ]
+            )
+
+        lines.extend(
+            [
+                "## 核心知识",
+                "",
+            ]
+        )
+
         if not knowledge_candidates:
             lines.extend(
                 [
@@ -1624,6 +2064,10 @@ class LlmWikiService:
     def _clean_line(line: str) -> str:
         cleaned = str(line or "").replace("\u3000", " ").strip()
         cleaned = re.sub(r"\s+", " ", cleaned)
+        if PAGE_FOOTER_PATTERN.fullmatch(cleaned):
+            return ""
+        if cleaned in {"商密【中】", "商密【高】", "商密【低】"}:
+            return ""
         return cleaned
 
     @staticmethod
@@ -1701,6 +2145,11 @@ class LlmWikiService:
             return "forced_rebuild"
         if existing is None:
             return "initial_build"
+        existing_quality_status = str(existing.get("quality_status") or "").strip()
+        if existing_quality_status and existing_quality_status != "formal":
+            return f"quality_{existing_quality_status}_rebuild"
+        if int(existing.get("formal_knowledge_candidate_count") or 0) <= 0:
+            return "formal_candidate_missing_rebuild"
 
         previous_signature = existing.get("signature")
         if not isinstance(previous_signature, dict):
@@ -1723,6 +2172,35 @@ class LlmWikiService:
             return "unchanged_skipped"
         return ",".join(reasons)
 
+    @staticmethod
+    def _emit_progress(
+        progress_callback: Callable[[dict[str, Any], str], None] | None,
+        payload: dict[str, Any],
+        summary: str,
+    ) -> None:
+        if progress_callback is None:
+            return
+        progress_callback(payload, summary)
+
+    @staticmethod
+    def _calculate_progress_percent(
+        *,
+        completed_documents: int,
+        skipped_documents: int,
+        total_documents: int,
+        group_count: int = 0,
+        current_group_index: int = 0,
+    ) -> int:
+        if total_documents <= 0:
+            return 100
+
+        completed_units = completed_documents + skipped_documents
+        if group_count > 0 and current_group_index > 0:
+            completed_units += min(current_group_index, group_count) / group_count
+
+        percent = round((completed_units / total_documents) * 100)
+        return max(0, min(percent, 100))
+
     @staticmethod
     def _build_document_signature(entry: dict[str, Any]) -> dict[str, Any]:
         return {

server/tests/test_llm_wiki_service.py

@@ -16,7 +16,7 @@ from app.core.agent_enums import AgentReviewStatus, AgentRunSource, AgentRunStat
 from app.db.base import Base
 from app.main import create_app
 from app.schemas.agent_asset import AgentAssetReviewCreate
-from app.schemas.knowledge import LlmWikiSummaryUpdateWrite, LlmWikiSyncRead
+from app.schemas.knowledge import LlmWikiSummaryUpdateWrite
 from app.services.agent_assets import AgentAssetService
 from app.services.agent_runs import AgentRunService
 from app.services.knowledge import (
@@ -25,7 +25,7 @@ from app.services.knowledge import (
     KNOWLEDGE_INGEST_STATUS_PUBLISHED,
     KnowledgeService,
 )
-from app.services.llm_wiki import LlmWikiService
+from app.services.llm_wiki import CandidateModelAttempt, LlmWikiService
 
 
 def build_session() -> Session:
@@ -86,6 +86,36 @@ def upload_policy_document(storage_root: Path, *, filename: str = "公司差旅
     return document.id
 
 
+def upload_multipage_policy_document(storage_root: Path, *, filename: str = "公司支出管理办法.txt") -> str:
+    service = KnowledgeService(storage_root=storage_root)
+    service.ensure_library_ready()
+    document = service.upload_document(
+        folder="报销制度",
+        filename=filename,
+        content=(
+            "商密【中】\n"
+            "关于颁布《公司支出管理办法》的通知\n"
+            "特此通知。\n"
+            "\f"
+            "目录\n"
+            "第一章 总则................................4\n"
+            "第二章 报销审批................................7\n"
+            "\f"
+            "第一条 报销申请\n"
+            "员工提交报销申请时，应附发票、行程单和审批说明。\n"
+            "第二条 报销审批\n"
+            "住宿费超过制度标准时，必须升级至总经理审批。\n"
+            "第三条 附件补充\n"
+            "缺少附件时不得提交报销。\n"
+            "\f"
+            "第四条 财务复核\n"
+            "财务复核时应校验预算、发票真伪和审批链完整性。\n"
+        ).encode("utf-8"),
+        current_user=build_admin_user(),
+    )
+    return document.id
+
+
 def build_candidate_payload(chunk_id: str, *, summary: str = "住宿费超过标准时必须升级审批。") -> dict[str, object]:
     return {
         "knowledge_candidates": [
@@ -222,10 +252,14 @@ def test_llm_wiki_sync_creates_artifacts_and_draft_rule(tmp_path, monkeypatch) -
 
         document_payload = json.loads((document_dir / "document.json").read_text(encoding="utf-8"))
         assert document_payload["sync_reason"] == "initial_build"
+        assert document_payload["quality_status"] == "formal"
+        assert document_payload["formal_knowledge_candidate_count"] == 1
+        assert document_payload["fallback_knowledge_candidate_count"] == 0
 
         detail = service.get_document_detail(document_id)
         assert "公司差旅报销制度.txt 知识总结" in detail.knowledge_summary_markdown
         assert "住宿费升级审批要求" in detail.knowledge_summary_markdown
+        assert detail.quality_status == "formal"
 
         asset = AgentAssetService(db).get_asset(result.generated_rule_asset_ids[0])
         assert asset is not None
@@ -386,9 +420,91 @@ def test_llm_wiki_sync_uses_fallback_candidates_when_system_hermes_times_out(
     assert result.knowledge_candidate_count >= 1
     assert runtime_called["count"] == 0
 
-    detail = KnowledgeService(storage_root=tmp_path).get_document_detail(document_id)
+    knowledge_service = KnowledgeService(storage_root=tmp_path)
-    assert detail.stateCode == KNOWLEDGE_INGEST_STATUS_INGESTED
+    detail = knowledge_service.get_document_detail(document_id)
-    assert detail.state == "已归纳"
+    assert detail.stateCode == KNOWLEDGE_INGEST_STATUS_FAILED
+    assert detail.state == "归纳失败"
+    assert detail.llmWikiAvailable is True
+    assert detail.llmWikiQualityStatus == "fallback_only"
+
+    document_payload = json.loads(
+        (
+            tmp_path
+            / "knowledge"
+            / ".llm_wiki"
+            / "documents"
+            / document_id
+            / "document.json"
+        ).read_text(encoding="utf-8")
+    )
+    assert document_payload["quality_status"] == "fallback_only"
+    assert document_payload["formal_knowledge_candidate_count"] == 0
+    assert document_payload["fallback_knowledge_candidate_count"] == 1
+
+    candidates_payload = json.loads(
+        (
+            tmp_path
+            / "knowledge"
+            / ".llm_wiki"
+            / "documents"
+            / document_id
+            / "knowledge_candidates.json"
+        ).read_text(encoding="utf-8")
+    )
+    assert candidates_payload[0]["extraction_mode"] == "fallback"
+    assert "fallback_only" in candidates_payload[0]["quality_flags"]
+
+
+def test_llm_wiki_sync_continues_after_single_group_failure(tmp_path, monkeypatch) -> None:
+    document_id = upload_multipage_policy_document(tmp_path, filename="多页支出制度.txt")
+    call_count = {"count": 0}
+
+    def fake_call_candidate_model(self, *, entry, chunk_group):
+        call_count["count"] += 1
+        if call_count["count"] == 1:
+            return CandidateModelAttempt(
+                payload={},
+                source="hermes",
+                ok=False,
+                failure_reason="simulated_timeout",
+            )
+        return build_candidate_payload(chunk_group[0]["chunk_id"])
+
+    monkeypatch.setattr(LlmWikiService, "_call_candidate_model", fake_call_candidate_model)
+
+    with build_session() as db:
+        service = LlmWikiService(db, storage_root=tmp_path)
+        result = service.sync_folder(
+            folder="报销制度",
+            current_user=build_admin_user(),
+            document_ids=[document_id],
+        )
+        detail = service.get_document_detail(document_id)
+
+    assert result.document_count == 1
+    assert call_count["count"] >= 2
+    assert detail.quality_status == "partial_degraded"
+    assert detail.successful_group_count >= 1
+    assert detail.failed_group_count >= 1
+    assert detail.formal_knowledge_candidate_count >= 1
+
+    knowledge_detail = KnowledgeService(storage_root=tmp_path).get_document_detail(document_id)
+    assert knowledge_detail.stateCode == KNOWLEDGE_INGEST_STATUS_INGESTED
+    assert knowledge_detail.llmWikiQualityStatus == "partial_degraded"
+
+
+def test_llm_wiki_filters_cover_and_catalog_chunks_before_candidate_extraction(tmp_path) -> None:
+    document_id = upload_multipage_policy_document(tmp_path, filename="封面目录过滤测试.txt")
+
+    with build_session() as db:
+        service = LlmWikiService(db, storage_root=tmp_path)
+        text = service.knowledge_service.extract_document_text(document_id)
+        chunks = service._build_chunks(document_id=document_id, text=text)
+        candidate_chunks = service._select_candidate_chunks(chunks)
+
+    assert len(chunks) > len(candidate_chunks)
+    assert candidate_chunks
+    assert all(int(item.get("source_page") or 0) >= 3 for item in candidate_chunks)
 
 
 def test_llm_wiki_sync_skips_unchanged_and_rebuilds_on_updated_at_change(tmp_path, monkeypatch) -> None:
@@ -475,22 +591,46 @@ def test_llm_wiki_sync_does_not_overwrite_active_rule(tmp_path, monkeypatch) ->
 
 
 def test_llm_wiki_sync_endpoint_records_agent_run(monkeypatch) -> None:
-    def fake_sync_folder(self, *, folder="报销制度", current_user, document_ids=None, force=False):
-        return LlmWikiSyncRead(
-            ok=True,
-            run_id="wiki_test_sync",
-            folder=folder,
-            document_count=1,
-            knowledge_candidate_count=2,
-            rule_candidate_count=1,
-            generated_rule_count=1,
-            generated_rule_asset_ids=["asset-rule-1"],
-            summary="已完成 Hermes LLM Wiki 同步。",
-        )
-
-    monkeypatch.setattr(LlmWikiService, "sync_folder", fake_sync_folder)
-
     client, session_factory = build_client()
+
+    def fake_submit_sync(*, agent_run_id, folder, current_user, document_ids=None, force=False):
+        with session_factory() as db:
+            service = AgentRunService(db)
+            service.record_tool_call(
+                run_id=agent_run_id,
+                tool_type="llm",
+                tool_name="system_hermes_llm_wiki_sync",
+                request_json={
+                    "folder": folder,
+                    "document_ids": list(document_ids or []),
+                    "force": force,
+                },
+                response_json={"run_id": "wiki_test_sync"},
+                status="succeeded",
+                duration_ms=0,
+            )
+            service.merge_route_json(
+                agent_run_id,
+                {
+                    "phase": "succeeded",
+                    "sync_run_id": "wiki_test_sync",
+                    "progress": {
+                        "total_documents": len(document_ids or []),
+                        "completed_documents": len(document_ids or []),
+                        "failed_documents": 0,
+                        "skipped_documents": 0,
+                        "percent": 100,
+                    },
+                },
+                status=AgentRunStatus.SUCCEEDED.value,
+                result_summary="已完成 Hermes LLM Wiki 同步。",
+            )
+
+    monkeypatch.setattr(
+        "app.services.llm_wiki_tasks.llm_wiki_task_manager.submit_sync",
+        fake_submit_sync,
+    )
+
     with session_factory() as db:
         before_count = len(AgentRunService(db).list_runs(limit=100))
 
@@ -506,8 +646,8 @@ def test_llm_wiki_sync_endpoint_records_agent_run(monkeypatch) -> None:
 
     assert response.status_code == 200
     payload = response.json()
-    assert payload["run_id"] == "wiki_test_sync"
+    assert payload["agent_run_id"].startswith("run_")
-    assert payload["generated_rule_count"] == 1
+    assert payload["status"] == AgentRunStatus.RUNNING.value
 
     with session_factory() as db:
         service = AgentRunService(db)
@@ -521,4 +661,4 @@ def test_llm_wiki_sync_endpoint_records_agent_run(monkeypatch) -> None:
         assert latest_run.tool_calls
         assert latest_run.tool_calls[0].tool_name == "system_hermes_llm_wiki_sync"
         assert latest_run.tool_calls[0].status == "succeeded"
-        assert latest_run.tool_calls[0].response_json["run_id"] == "wiki_test_sync"
+        assert latest_run.route_json["sync_run_id"] == "wiki_test_sync"