fix 文档管理模块 & 法规对话模块

.env

@@ -7,26 +7,29 @@ APP_VERSION=0.1.0
 DEBUG=false
 
 # ===== Milvus向量数据库配置（已有）=====
-MILVUS_HOST=localhost
+MILVUS_HOST=6.86.80.8
 MILVUS_PORT=19530
 MILVUS_COLLECTION=regulations_dense_1024_v1
 MILVUS_DB_NAME=default
+MILVUS_INDEX_TYPE=IVF_FLAT
+MILVUS_NLIST=128
+MILVUS_NPROBE=16
 
 # ===== MinIO对象存储配置（已有）=====
-MINIO_ENDPOINT=localhost:9000
+MINIO_ENDPOINT=6.86.80.8:9000
 MINIO_ACCESS_KEY=minioadmin
 MINIO_SECRET_KEY=minioadmin
 MINIO_BUCKET=compliance-docs
 MINIO_SECURE=false
 
 # ===== Redis配置（已有）=====
-REDIS_HOST=localhost
+REDIS_HOST=6.86.80.8
 REDIS_PORT=6379
 REDIS_PASSWORD=redis@123
 REDIS_DB=0
 
 # ===== PostgreSQL配置（已有）=====
-POSTGRES_HOST=localhost
+POSTGRES_HOST=6.86.80.8
 POSTGRES_PORT=5432
 POSTGRES_USER=postgresql
 POSTGRES_PASSWORD=postgresql123456
@@ -43,6 +46,10 @@ EMBEDDING_TIMEOUT_SECONDS=120
 CHUNK_SIZE=512
 CHUNK_OVERLAP=50
 MAX_FILE_SIZE_MB=100
+PARSER_BACKEND=aliyun
+CHUNK_BACKEND=aliyun
+# 文档元数据存储后端：json（默认）或 postgres
+DOCUMENT_REPOSITORY_BACKEND=json
 
 # ===== API配置 =====
 API_HOST=0.0.0.0

.env.development

@@ -6,6 +6,9 @@ MILVUS_HOST=6.86.80.8
 MILVUS_PORT=19530
 MILVUS_COLLECTION=regulations_dense_1024_v1
 MILVUS_DB_NAME=default
+MILVUS_INDEX_TYPE=IVF_FLAT
+MILVUS_NLIST=128
+MILVUS_NPROBE=16
 
 # ===== MinIO对象存储配置（已有）=====
 MINIO_ENDPOINT=6.86.80.8:9000
@@ -26,3 +29,7 @@ POSTGRES_PORT=5432
 POSTGRES_USER=postgresql
 POSTGRES_PASSWORD=postgresql123456
 POSTGRES_DB=compliance_db
+
+# ===== 文档元数据后端 =====
+# 改为 postgres 以启用 PG 持久化（structure_nodes + semantic_blocks 入库）
+DOCUMENT_REPOSITORY_BACKEND=json

.env.example

@@ -7,10 +7,13 @@ APP_VERSION=0.1.0
 DEBUG=false
 
 # ===== Milvus向量数据库配置 =====
-MILVUS_HOST=localhost
+MILVUS_HOST=6.86.80.8
 MILVUS_PORT=19530
 MILVUS_COLLECTION=regulations_dense_1024_v1
 MILVUS_DB_NAME=default
+MILVUS_INDEX_TYPE=IVF_FLAT
+MILVUS_NLIST=128
+MILVUS_NPROBE=16
 
 # ===== 嵌入模型配置 =====
 EMBEDDING_MODEL=text-embedding-v3
@@ -20,20 +23,20 @@ EMBEDDING_BASE_URL=http://6.86.80.4:30080/v1
 EMBEDDING_TIMEOUT_SECONDS=120
 
 # ===== MinIO对象存储配置 =====
-MINIO_ENDPOINT=localhost:9000
+MINIO_ENDPOINT=6.86.80.8:9000
 MINIO_ACCESS_KEY=minioadmin
 MINIO_SECRET_KEY=minioadmin123
 MINIO_BUCKET=compliance-docs
 MINIO_SECURE=false
 
 # ===== Redis配置 =====
-REDIS_HOST=localhost
+REDIS_HOST=6.86.80.8
 REDIS_PORT=6379
 REDIS_PASSWORD=
 REDIS_DB=0
 
 # ===== PostgreSQL配置 =====
-POSTGRES_HOST=localhost
+POSTGRES_HOST=6.86.80.8
 POSTGRES_PORT=5432
 POSTGRES_USER=compliance
 POSTGRES_PASSWORD=compliance123
@@ -46,6 +49,8 @@ MAX_FILE_SIZE_MB=100
 DOCUMENT_METADATA_PATH=backend/data/documents.json
 PARSER_BACKEND=aliyun
 CHUNK_BACKEND=aliyun
+# 文档元数据存储后端：json（默认，无需数据库）或 postgres（启用 PG 持久化）
+DOCUMENT_REPOSITORY_BACKEND=json
 
 # ===== 阿里云文档解析 =====
 ALIBABA_ACCESS_KEY_ID=your_aliyun_access_key_id
@@ -88,9 +93,18 @@ DEEPSEEK_MODEL=deepseek-v4-flash
 
 # ===== RAG配置 =====
 RAG_TOP_K=10
+RAG_RETRIEVAL_TOP_K=20
 RAG_MAX_CONTEXT_TOKENS=4000
 RAG_SUMMARY_MAX_TOKENS=1024
 
+# ===== Reranker配置（Cross-Encoder精排，默认关闭）=====
+# 设置 RERANKER_ENABLED=true 并配置 RERANKER_BASE_URL 以启用精排
+RERANKER_ENABLED=false
+RERANKER_BASE_URL=
+RERANKER_MODEL=BAAI/bge-reranker-v2-m3
+RERANKER_API_KEY=
+RERANKER_TOP_K=5
+
 # ===== 会话配置 =====
 SESSION_MAX_SESSIONS=100
 SESSION_TIMEOUT_MINUTES=30

backend/app/api/models/document.py

@@ -23,6 +23,8 @@ class DocumentUploadResponse(BaseModel):
     num_chunks: int = Field(default=0, description="分块数量")
     summary: str = Field(default="", description="LLM生成的文档摘要")
     summary_latency_ms: int = Field(default=0, description="摘要生成耗时(ms)")
+    regulation_type: str = Field(default="", description="法规类型")
+    version: str = Field(default="", description="文档版本号")
     timestamp: datetime = Field(default_factory=datetime.now, description="时间戳")
 
 

backend/app/api/routes/compliance.py

@@ -14,30 +14,22 @@ from app.schemas.compliance import (
     AnalyzeResponse,
     ComplianceChatRequest,
 )
-from app.services.mock_data import (
+from app.services.mock_data import generate_task_id, get_mock_compliance_result
-    generate_task_id,
+from app.shared.bootstrap import get_agent_conversation_service
-    get_mock_compliance_result,
-    get_mock_compliance_chat_response,
-)
-# Keep route handlers close to their transport-layer wiring for easier auditing.
 
 
 router = APIRouter(prefix="/compliance", tags=["合规分析"])
 
-# Keep route handlers close to their transport-layer wiring for easier auditing.
 tasks_store: dict[str, dict] = {}
 
-# Store uploaded compliance files inside the local backend data directory.
 RAW_DATA_DIR = Path(__file__).resolve().parents[3] / "data" / "raw"
 
 
 @router.post("/analyze", response_model=AnalyzeResponse)
 async def analyze_document(file: UploadFile = File(...)):
     """Handle analyze document."""
-    # Keep route handlers close to their transport-layer wiring for easier auditing.
     task_id = generate_task_id()
 
-    # Keep route handlers close to their transport-layer wiring for easier auditing.
     RAW_DATA_DIR.mkdir(parents=True, exist_ok=True)
     file_path = RAW_DATA_DIR / f"compliance_{task_id}_{file.filename}"
 
@@ -45,7 +37,6 @@ async def analyze_document(file: UploadFile = File(...)):
     with file_path.open("wb") as f:
         f.write(content)
 
-    # Keep route handlers close to their transport-layer wiring for easier auditing.
     tasks_store[task_id] = {
         "task_id": task_id,
         "file_path": str(file_path),
@@ -53,8 +44,6 @@ async def analyze_document(file: UploadFile = File(...)):
         "result": None,
     }
 
-    # Keep route handlers close to their transport-layer wiring for easier auditing.
-    # Keep route handlers close to their transport-layer wiring for easier auditing.
     tasks_store[task_id]["status"] = "completed"
     tasks_store[task_id]["result"] = get_mock_compliance_result(task_id)
 
@@ -65,47 +54,44 @@ async def analyze_document(file: UploadFile = File(...)):
 async def get_result(task_id: str):
     """Return result."""
     if task_id not in tasks_store:
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
         return get_mock_compliance_result(task_id)
 
     task = tasks_store[task_id]
-
     if task["status"] == "processing":
         return {"status": "processing", "message": "分析进行中"}
-
     return task["result"]
 
 
 @router.post("/chat/{segment_id}")
 async def compliance_chat(segment_id: int, request: ComplianceChatRequest):
-    """Handle compliance chat."""
+    """Stream compliance Q&A grounded in real vector retrieval."""
-    # Keep route handlers close to their transport-layer wiring for easier auditing.
+    query = request.query
-    intent_map = {
+    if request.segment_context:
-        1: "车身结构设计",
+        query = f"[段落分析上下文]\n{request.segment_context}\n\n用户问题：{request.query}"
-        2: "动力系统配置",
-        3: "安全配置设计",
-    }
-    intent = intent_map.get(segment_id, "车身结构设计")
 
-    async def generate() -> AsyncGenerator[str, None]:
+    _, event_stream = get_agent_conversation_service().stream_chat(
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
+        query=query,
-        """Handle generate."""
+        top_k=5,
-        response = get_mock_compliance_chat_response(intent, request.query)
+        prompt_template="compliance_qa",
-
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
-        sentences = response.split("\n\n")
-        for sentence in sentences:
-            if sentence.strip():
-                chunks = sentence.split("\n")
-                for chunk in chunks:
-                    if chunk.strip():
-                        await asyncio.sleep(0.05)
-                        yield (
-                            "event: message\n"
-                            f"data: {json.dumps({'type': 'chunk', 'text': chunk + chr(10)}, ensure_ascii=False)}\n\n"
     )
 
-        yield f"event: message\ndata: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
+    async def generate() -> AsyncGenerator[str, None]:
+        """Translate agent SSE events to compliance chunk/done format."""
+        for event in event_stream:
+            event_type = event.get("event", "")
+            if event_type == "content":
+                text = event.get("data", "")
+                if text:
+                    yield (
+                        "event: message\n"
+                        f"data: {json.dumps({'type': 'chunk', 'text': text}, ensure_ascii=False)}\n\n"
+                    )
+            elif event_type == "done":
+                yield (
+                    "event: message\n"
+                    f"data: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
+                )
+            await asyncio.sleep(0)
 
     return StreamingResponse(
         generate(),

backend/app/api/routes/documents.py

@@ -80,6 +80,8 @@ async def get_document_status(doc_id: str):
         num_chunks=document.chunk_count,
         summary=document.summary,
         summary_latency_ms=document.summary_latency_ms,
+        regulation_type=document.regulation_type,
+        version=document.version,
     )
 
 
@@ -123,7 +125,7 @@ async def list_documents():
 @router.get("/management-list")
 async def get_document_management_list():
     """Return document management list."""
-    documents = get_document_query_service().list_documents(limit=10)
+    documents = get_document_query_service().list_documents()
     return {
         "documents": [
             {
@@ -131,10 +133,37 @@ async def get_document_management_list():
                 "doc_name": item.doc_name,
                 "status": item.status.value,
                 "chunk_count": item.chunk_count,
+                "size_bytes": item.size_bytes,
+                "summary": item.summary,
                 "updated_at": item.updated_at.isoformat(),
+                "regulation_type": item.regulation_type,
+                "version": item.version,
             }
             for item in documents
         ],
         "total": len(documents),
-        "limit": 10,
     }
+
+
+@router.delete("/{doc_id}")
+async def delete_document(doc_id: str):
+    """Delete a document and its associated data."""
+    deleted = get_document_command_service().delete(doc_id)
+    if not deleted:
+        raise HTTPException(status_code=404, detail="文档不存在")
+    return {"doc_id": doc_id, "deleted": True}
+
+
+@router.post("/{doc_id}/retry", response_model=DocumentUploadResponse)
+async def retry_document(doc_id: str):
+    """Re-process a failed document."""
+    try:
+        result = get_document_command_service().retry(doc_id)
+        if result.status == "failed":
+            raise HTTPException(status_code=500, detail=result.message)
+        return _document_response(result)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        logger.exception("文档重试失败")
+        raise HTTPException(status_code=500, detail=str(exc))

backend/app/api/routes/rag.py

@@ -9,73 +9,74 @@ from typing import AsyncGenerator
 from fastapi import APIRouter
 from fastapi.responses import StreamingResponse
 
+from app.config.settings import settings
 from app.schemas.rag import RagChatRequest, QuickQuestionsResponse, QuickQuestion
-from app.services.mock_data import (
+from app.shared.bootstrap import get_agent_conversation_service
-    get_mock_quick_questions,
-    get_mock_retrieval,
-    get_mock_rag_answer,
-)
-# Keep route handlers close to their transport-layer wiring for easier auditing.
 
 
 router = APIRouter(prefix="/rag", tags=["RAG问答"])
 
+_DEFAULT_QUICK_QUESTIONS = [
+    {"id": "1", "question": "请总结最新入库法规对电池安全的核心要求", "category": "法规解读"},
+    {"id": "2", "question": "我上传的制度文档与新能源法规有哪些潜在冲突？", "category": "差距分析"},
+    {"id": "3", "question": "请给出法规依据，并按条款列出整改建议", "category": "整改建议"},
+    {"id": "4", "question": "请解释 UN-ECE 与 GB 标准在网络安全方面的差异", "category": "标准对比"},
+    {"id": "5", "question": "IATF 16949 对供应商质量管理有哪些强制要求？", "category": "法规解读"},
+    {"id": "6", "question": "ISO 45001 与 AQ 标准在职业健康安全方面的主要差异是什么？", "category": "标准对比"},
+]
+
 
 @router.post("/chat")
 async def rag_chat(request: RagChatRequest):
-    """Handle rag chat."""
+    """Stream RAG Q&A using the real agent service."""
+    _, event_stream = get_agent_conversation_service().stream_chat(
+        query=request.query,
+        session_id=request.session_id,
+        filters=request.filters,
+        top_k=request.top_k or settings.rag_top_k,
+    )
 
     async def generate() -> AsyncGenerator[str, None]:
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
+        """Translate agent SSE events to rag format."""
-        """Handle generate."""
+        for event in event_stream:
-        yield f"event: message\ndata: {json.dumps({'type': 'retrieving'}, ensure_ascii=False)}\n\n"
+            event_type = event.get("event", "")
-
+            data = event.get("data", "")
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
+            if event_type == "sources":
-        await asyncio.sleep(0.3)
+                docs = [
-
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
-        docs = get_mock_retrieval(request.query, top_k=request.top_k)
-
-        retrieved_data = [
                     {
-                "id": d["id"],
+                        "id": str(s.get("chunk_id") or s.get("doc_id") or idx + 1),
-                "score": d["score"],
+                        "score": s.get("score", 0),
-                "preview": d["preview"],
+                        "preview": s.get("content", "")[:200],
-                "doc_name": d.get("doc_name", ""),
+                        "doc_name": s.get("doc_name", ""),
-                "clause": d.get("clause", ""),
+                        "clause": s.get("section_title", "法规片段"),
+                        "doc_id": s.get("doc_id"),
+                        "download_url": (
+                            f"/api/v1/documents/download/{s['doc_id']}" if s.get("doc_id") else None
+                        ),
                     }
-            for d in docs
+                    for idx, s in enumerate(data if isinstance(data, list) else [])
                 ]
-        yield f"event: message\ndata: {json.dumps({'type': 'retrieved', 'docs': retrieved_data}, ensure_ascii=False)}\n\n"
-
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
-        yield (
-            f"event: message\ndata: "
-            f"{json.dumps({'type': 'generating', 'text': '正在生成答案...'}, ensure_ascii=False)}\n\n"
-        )
-
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
-        await asyncio.sleep(0.2)
-
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
-        answer = get_mock_rag_answer(request.query)
-
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
-        sentences = answer.split("\n\n")
-        for sentence in sentences:
-            if sentence.strip():
-                # Keep route handlers close to their transport-layer wiring for easier auditing.
-                chunks = sentence.split("\n")
-                for chunk in chunks:
-                    if chunk.strip():
-                        await asyncio.sleep(0.05)  # Keep route handlers close to their transport-layer wiring for easier auditing.
                 yield (
                     "event: message\n"
-                            f"data: {json.dumps({'type': 'chunk', 'text': chunk + chr(10)}, ensure_ascii=False)}\n\n"
+                    f"data: {json.dumps({'type': 'retrieved', 'docs': docs}, ensure_ascii=False)}\n\n"
                 )
-
+            elif event_type == "content":
-        # Keep route handlers close to their transport-layer wiring for easier auditing.
+                if data:
-        yield f"event: message\ndata: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
+                    yield (
+                        "event: message\n"
+                        f"data: {json.dumps({'type': 'chunk', 'text': data}, ensure_ascii=False)}\n\n"
+                    )
+            elif event_type == "done":
+                yield (
+                    "event: message\n"
+                    f"data: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
+                )
+            elif event_type == "status":
+                yield (
+                    "event: message\n"
+                    f"data: {json.dumps({'type': 'status', 'text': data}, ensure_ascii=False)}\n\n"
+                )
+            await asyncio.sleep(0)
 
     return StreamingResponse(
         generate(),
@@ -86,9 +87,13 @@ async def rag_chat(request: RagChatRequest):
 
 @router.get("/quick-questions", response_model=QuickQuestionsResponse)
 async def get_quick_questions():
-    """Return quick questions."""
+    """Return configurable quick questions from settings or defaults."""
+    raw = getattr(settings, "rag_quick_questions", None)
+    if raw and isinstance(raw, list):
         questions = [
-        QuickQuestion(id=q["id"], question=q["question"], category=q["category"])
+            QuickQuestion(id=str(i + 1), question=q if isinstance(q, str) else q.get("question", ""), category=q.get("category", "法规问答") if isinstance(q, dict) else "法规问答")
-        for q in get_mock_quick_questions()
+            for i, q in enumerate(raw)
         ]
+    else:
+        questions = [QuickQuestion(**q) for q in _DEFAULT_QUICK_QUESTIONS]
     return QuickQuestionsResponse(questions=questions)

backend/app/application/documents/services.py

@@ -17,6 +17,7 @@ from app.domain.documents import (
     DocumentParser,
     DocumentRepository,
     DocumentStatus,
+    ParseArtifactStore,
     ParsedDocument,
 )
 from app.domain.retrieval import EmbeddingProvider, VectorIndex
@@ -47,6 +48,7 @@ class DocumentCommandService:
         chunk_builder: ChunkBuilder,
         embedding_provider: EmbeddingProvider,
         vector_index: VectorIndex,
+        parse_artifact_store: ParseArtifactStore | None = None,
     ) -> None:
         """Initialize the Document Command Service instance."""
         self.document_repository = document_repository
@@ -55,6 +57,7 @@ class DocumentCommandService:
         self.chunk_builder = chunk_builder
         self.embedding_provider = embedding_provider
         self.vector_index = vector_index
+        self.parse_artifact_store = parse_artifact_store
 
     def _save_parse_artifacts(self, *, doc_id: str, parsed_document: ParsedDocument) -> dict[str, str]:
         """Persist parse artifacts so troubleshooting does not depend on provider retention windows."""
@@ -143,6 +146,15 @@ class DocumentCommandService:
                     "processing_stage": "parsed",
                 },
             )
+            if self.parse_artifact_store:
+                try:
+                    self.parse_artifact_store.save(
+                        doc_id,
+                        parsed_document.structure_nodes,
+                        parsed_document.semantic_blocks,
+                    )
+                except Exception:
+                    logger.warning("ParseArtifactStore.save failed for doc_id={}", doc_id)
 
             chunks = self.chunk_builder.build(
                 parsed_document=parsed_document,
@@ -205,20 +217,120 @@ class DocumentCommandService:
                     logger.warning("临时文件清理失败: {}", temp_path)
 
 
+    def delete(self, doc_id: str) -> bool:
+        """Delete document record, binary file, and vector chunks."""
+        document = self.document_repository.get(doc_id)
+        if not document:
+            return False
+        try:
+            self.binary_store.delete(document.object_name)
+        except Exception:
+            logger.warning("Binary delete failed for doc_id={}", doc_id)
+        try:
+            self.vector_index.delete_by_document(doc_id)
+        except Exception:
+            logger.warning("Vector delete failed for doc_id={}", doc_id)
+        if self.parse_artifact_store:
+            try:
+                self.parse_artifact_store.delete(doc_id)
+            except Exception:
+                logger.warning("ParseArtifactStore delete failed for doc_id={}", doc_id)
+        self.document_repository.delete(doc_id)
+        return True
+
+    def retry(self, doc_id: str) -> DocumentProcessResult:
+        """Re-process a failed document from its stored binary."""
+        document = self.document_repository.get(doc_id)
+        if not document:
+            return DocumentProcessResult(doc_id=doc_id, doc_name="", status="failed", message="文档不存在")
+        content = self.binary_store.read(document.object_name)
+        return self.upload_and_process(
+            doc_id=doc_id,
+            file_name=document.file_name,
+            content=content,
+            content_type=document.content_type,
+            doc_name=document.doc_name,
+            regulation_type=document.regulation_type,
+            version=document.version,
+            generate_summary=bool(document.metadata.get("generate_summary", False)),
+        )
+
+
 class DocumentQueryService:
     """Provide the Document Query Service service."""
-    def __init__(self, *, document_repository: DocumentRepository, binary_store: DocumentBinaryStore) -> None:
+    def __init__(self, *, document_repository: DocumentRepository, binary_store: DocumentBinaryStore, vector_index: VectorIndex) -> None:
         """Initialize the Document Query Service instance."""
         self.document_repository = document_repository
         self.binary_store = binary_store
+        self.vector_index = vector_index
 
     def get(self, doc_id: str) -> Document | None:
         """Handle get for the Document Query Service instance."""
         return self.document_repository.get(doc_id)
 
     def list_documents(self, limit: int | None = None) -> list[Document]:
-        """List documents for the Document Query Service instance."""
+        """Return documents with real-time state from Milvus as the authoritative source.
-        return self.document_repository.list(limit=limit)
+
+        Algorithm:
+        1. Query Milvus for all doc metadata (doc_id, doc_name, chunk_count, …).
+        2. Load JSON/PG metadata records and index them by doc_id.
+        3. Merge: Milvus-present docs get status=INDEXED and live chunk_count;
+           metadata-only docs with status=INDEXED are demoted to FAILED.
+        4. Milvus-only docs (no metadata record) are surfaced as synthetic INDEXED
+           entries so they are never invisible to the management list.
+        """
+        # Fetch live Milvus state first.
+        try:
+            milvus_rows = self.vector_index.list_document_metadata()
+        except Exception:
+            milvus_rows = []
+
+        milvus_by_id: dict[str, dict] = {r["doc_id"]: r for r in milvus_rows}
+
+        # Load metadata store records.
+        meta_docs = self.document_repository.list(limit=limit)
+        meta_by_id: dict[str, Document] = {d.doc_id: d for d in meta_docs}
+
+        result: list[Document] = []
+
+        # Reconcile metadata records against Milvus.
+        for doc in meta_docs:
+            if doc.doc_id in milvus_by_id:
+                row = milvus_by_id[doc.doc_id]
+                doc.chunk_count = row["chunk_count"]
+                doc.status = DocumentStatus.INDEXED
+                # Backfill fields that may be missing from older JSON records.
+                if not doc.doc_name and row.get("doc_name"):
+                    doc.doc_name = row["doc_name"]
+                if not doc.regulation_type and row.get("regulation_type"):
+                    doc.regulation_type = row["regulation_type"]
+                if not doc.version and row.get("version"):
+                    doc.version = row["version"]
+            elif doc.status == DocumentStatus.INDEXED:
+                # Metadata says indexed but Milvus has no chunks.
+                doc.status = DocumentStatus.FAILED
+                doc.error_message = "向量数据库中未找到对应数据"
+            result.append(doc)
+
+        # Surface Milvus-only docs that have no metadata record at all.
+        for doc_id, row in milvus_by_id.items():
+            if doc_id not in meta_by_id:
+                synthetic = Document(
+                    doc_id=doc_id,
+                    doc_name=row.get("doc_name", doc_id),
+                    file_name=row.get("doc_name", doc_id),
+                    object_name="",
+                    content_type="",
+                    size_bytes=0,
+                    status=DocumentStatus.INDEXED,
+                    regulation_type=row.get("regulation_type", ""),
+                    version=row.get("version", ""),
+                    chunk_count=row["chunk_count"],
+                )
+                result.append(synthetic)
+
+        result.sort(key=lambda d: d.updated_at, reverse=True)
+        return result[:limit] if limit is not None else result
 
     def download(self, doc_id: str) -> tuple[Document, bytes]:
         """Handle download for the Document Query Service instance."""

backend/app/application/knowledge/services.py

@@ -3,17 +3,24 @@
 from __future__ import annotations
 
 from app.domain.retrieval import RetrievalQuery, Retriever, RetrievedChunk
+from app.domain.retrieval.ports import Reranker
 # Keep orchestration logic centralized so use-case flow stays easy to trace.
 
 
-
 class KnowledgeRetrievalService:
     """Provide the Knowledge Retrieval Service service."""
-    def __init__(self, *, retriever: Retriever) -> None:
+
+    def __init__(self, *, retriever: Retriever, reranker: Reranker | None = None, reranker_top_k: int = 5) -> None:
         """Initialize the Knowledge Retrieval Service instance."""
         self.retriever = retriever
+        self.reranker = reranker
+        self.reranker_top_k = reranker_top_k
 
     def retrieve(self, *, query: str, top_k: int, filters: str | None = None) -> list[RetrievedChunk]:
-        """Handle retrieve for the Knowledge Retrieval Service instance."""
+        """Retrieve and optionally rerank chunks for a query."""
-        retrieval_query = RetrievalQuery(query=query, top_k=top_k, filters=filters)
+        candidate_k = top_k if self.reranker is None else max(top_k * 4, 20)
-        return self.retriever.retrieve(retrieval_query)
+        retrieval_query = RetrievalQuery(query=query, top_k=candidate_k, filters=filters)
+        candidates = self.retriever.retrieve(retrieval_query)
+        if self.reranker and candidates:
+            return self.reranker.rerank(query, candidates, top_k=self.reranker_top_k)
+        return candidates[:top_k]

backend/app/config/settings.py

@@ -31,7 +31,7 @@ class Settings(BaseSettings):
     debug: bool = Field(default=False, description="调试模式")
 
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
-    milvus_host: str = Field(default="localhost", description="Milvus服务地址")
+    milvus_host: str = Field(default="6.86.80.8", description="Milvus服务地址")
     milvus_port: int = Field(default=19530, description="Milvus服务端口")
     milvus_collection: str = Field(default="regulations_dense_1024_v1", description="法规向量集合名称")
     milvus_db_name: str = Field(default="default", description="Milvus数据库名称")
@@ -54,20 +54,20 @@ class Settings(BaseSettings):
     parser_failure_mode: str = Field(default="fail", description="解析失败策略")
 
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
-    minio_endpoint: str = Field(default="localhost:9000", description="MinIO服务地址")
+    minio_endpoint: str = Field(default="6.86.80.8:9000", description="MinIO服务地址")
     minio_access_key: str = Field(default="minioadmin", description="MinIO访问密钥")
     minio_secret_key: str = Field(default="minioadmin123", description="MinIO秘密密钥")
     minio_bucket: str = Field(default="upload-files", description="文档存储桶名称")
     minio_secure: bool = Field(default=False, description="是否使用HTTPS")
 
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
-    redis_host: str = Field(default="localhost", description="Redis服务地址")
+    redis_host: str = Field(default="6.86.80.8", description="Redis服务地址")
     redis_port: int = Field(default=6379, description="Redis服务端口")
     redis_password: str = Field(default="", description="Redis密码")
     redis_db: int = Field(default=0, description="Redis数据库编号")
 
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
-    postgres_host: str = Field(default="localhost", description="PostgreSQL服务地址")
+    postgres_host: str = Field(default="6.86.80.8", description="PostgreSQL服务地址")
     postgres_port: int = Field(default=5432, description="PostgreSQL服务端口")
     postgres_user: str = Field(default="compliance", description="PostgreSQL用户名")
     postgres_password: str = Field(default="compliance123", description="PostgreSQL密码")
@@ -80,6 +80,7 @@ class Settings(BaseSettings):
     document_metadata_path: str = Field(default="backend/data/documents.json", description="文档元数据存储路径")
     parser_backend: str = Field(default="aliyun", description="解析后端(local/aliyun)")
     chunk_backend: str = Field(default="aliyun", description="分块后端(local/aliyun)")
+    document_repository_backend: str = Field(default="json", description="文档元数据存储后端 (json/postgres)")
 
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
     api_host: str = Field(default="0.0.0.0", description="API服务地址")
@@ -104,9 +105,16 @@ class Settings(BaseSettings):
 
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
     rag_top_k: int = Field(default=5, description="检索召回数量")
+    rag_retrieval_top_k: int = Field(default=20, description="精排前召回候选数量（reranker 启用时生效）")
     rag_max_context_tokens: int = Field(default=2000, description="RAG最大上下文token数")
     rag_summary_max_tokens: int = Field(default=10240, description="文档摘要最大token数")
 
+    reranker_enabled: bool = Field(default=False, description="是否启用 Cross-Encoder 精排")
+    reranker_base_url: str = Field(default="", description="Reranker API 地址")
+    reranker_model: str = Field(default="BAAI/bge-reranker-v2-m3", description="Reranker 模型名称")
+    reranker_api_key: str = Field(default="", description="Reranker API 密钥")
+    reranker_top_k: int = Field(default=5, description="精排后保留的最终结果数量")
+
     # Keep configuration setup explicit so runtime behavior is easy to reason about.
     milvus_index_type: str = Field(default="IVF_FLAT", description="Milvus索引类型")
     milvus_nlist: int = Field(default=128, description="Milvus nlist参数")

backend/app/core/config.py

@@ -25,7 +25,7 @@ class Settings(BaseSettings):
     dashscope_api_key: str = ""
 
     # Milvus
-    milvus_host: str = "localhost"
+    milvus_host: str = "6.86.80.8"
     milvus_port: int = 19530
     milvus_collection: str = "regulations_dense_1024_v1"
 

backend/app/domain/documents/__init__.py

@@ -1,7 +1,7 @@
 """Initialize the app.domain.documents package."""
 
 from .models import Chunk, Document, DocumentStatus, ParsedDocument
-from .ports import ChunkBuilder, DocumentBinaryStore, DocumentParser, DocumentRepository
+from .ports import ChunkBuilder, DocumentBinaryStore, DocumentParser, DocumentRepository, ParseArtifactStore
 # Keep package boundaries explicit so backend imports stay predictable.
 
 
@@ -14,4 +14,5 @@ __all__ = [
     "DocumentBinaryStore",
     "DocumentParser",
     "DocumentRepository",
+    "ParseArtifactStore",
 ]

backend/app/domain/documents/ports.py

@@ -31,6 +31,11 @@ class DocumentRepository(ABC):
         """Handle list for the Document Repository instance."""
         pass
 
+    @abstractmethod
+    def delete(self, doc_id: str) -> bool:
+        """Delete a document record. Returns True if deleted, False if not found."""
+        pass
+
     @abstractmethod
     def update_status(
         self,
@@ -94,3 +99,32 @@ class ChunkBuilder(ABC):
     ) -> list[Chunk]:
         """Handle build for the Chunk Builder instance."""
         pass
+
+
+class ParseArtifactStore(ABC):
+    """Persist parse artifacts (structure nodes and semantic blocks) for relational queries."""
+
+    @abstractmethod
+    def save(
+        self,
+        doc_id: str,
+        structure_nodes: list[dict],
+        semantic_blocks: list[dict],
+    ) -> None:
+        """Persist structure nodes and semantic blocks for a document."""
+        pass
+
+    @abstractmethod
+    def delete(self, doc_id: str) -> None:
+        """Remove all parse artifacts for a document."""
+        pass
+
+    @abstractmethod
+    def get_semantic_blocks(self, doc_id: str) -> list[dict]:
+        """Return all semantic blocks for a document."""
+        pass
+
+    @abstractmethod
+    def get_structure_nodes(self, doc_id: str) -> list[dict]:
+        """Return all structure nodes for a document."""
+        pass

backend/app/domain/retrieval/__init__.py

@@ -1,8 +1,8 @@
 """Initialize the app.domain.retrieval package."""
 
 from .models import RetrievalQuery, RetrievedChunk
-from .ports import EmbeddingProvider, Retriever, VectorIndex
+from .ports import EmbeddingProvider, Reranker, Retriever, VectorIndex
 # Keep package boundaries explicit so backend imports stay predictable.
 
 
-__all__ = ["RetrievalQuery", "RetrievedChunk", "EmbeddingProvider", "Retriever", "VectorIndex"]
+__all__ = ["RetrievalQuery", "RetrievedChunk", "EmbeddingProvider", "Reranker", "Retriever", "VectorIndex"]

backend/app/domain/retrieval/ports.py

@@ -10,7 +10,6 @@ from .models import RetrievalQuery, RetrievedChunk
 # Keep domain contracts explicit so adapters can swap implementations cleanly.
 
 
-
 class EmbeddingProvider(ABC):
     """Provide the Embedding Provider provider."""
     @abstractmethod
@@ -41,12 +40,35 @@ class VectorIndex(ABC):
         """Handle search for the Vector Index instance."""
         pass
 
+    @abstractmethod
+    def count_by_document(self) -> dict[str, int]:
+        """Return a mapping of doc_id -> chunk count from the vector store."""
+        pass
+
+    @abstractmethod
+    def list_document_metadata(self) -> list[dict]:
+        """Return per-document metadata rows from the vector store.
+
+        Each row contains at minimum: doc_id, doc_name, chunk_count.
+        Optional fields: regulation_type, version.
+        """
+        pass
+
     @abstractmethod
     def health(self) -> dict:
         """Handle health for the Vector Index instance."""
         pass
 
 
+class Reranker(ABC):
+    """Re-score and re-order a candidate list using a cross-encoder model."""
+
+    @abstractmethod
+    def rerank(self, query: str, chunks: list[RetrievedChunk], top_k: int) -> list[RetrievedChunk]:
+        """Return top_k chunks sorted by cross-encoder score (descending)."""
+        pass
+
+
 class Retriever(ABC):
     """Provide the Retriever retriever."""
     @abstractmethod

backend/app/infrastructure/parser/aliyun_layout_normalizer.py

@@ -289,7 +289,7 @@ def build_vector_chunks(
                 {
                     "doc_id": doc_id,
                     "doc_title": doc_title,
-                    "chunk_id": f"chunk-{chunk_index}",
+                    "chunk_id": f"{doc_id}-chunk-{chunk_index}",
                     "chunk_index": chunk_index,
                     "semantic_id": block["semantic_id"],
                     "chunk_type": block["block_type"],

backend/app/infrastructure/storage/json_document_repository.py

@@ -75,6 +75,15 @@ class JsonDocumentRepository(DocumentRepository):
         documents.sort(key=lambda item: item.updated_at, reverse=True)
         return documents[:limit] if limit is not None else documents
 
+    def delete(self, doc_id: str) -> bool:
+        """Delete a document record."""
+        payload = self._load()
+        if doc_id not in payload:
+            return False
+        del payload[doc_id]
+        self._save(payload)
+        return True
+
     def update_status(
         self,
         doc_id: str,

backend/app/infrastructure/storage/postgres_document_repository.py

@@ -0,0 +1,228 @@
+"""Implement infrastructure support for postgres document repository."""
+
+from __future__ import annotations
+
+import json
+from contextlib import contextmanager
+from datetime import UTC, datetime
+from typing import Any
+
+import psycopg2
+import psycopg2.extras
+from psycopg2.pool import ThreadedConnectionPool
+
+from app.config.settings import settings
+from app.domain.documents import Document, DocumentRepository, DocumentStatus
+
+_CREATE_TABLE = """
+CREATE TABLE IF NOT EXISTS documents (
+    doc_id         VARCHAR(128) PRIMARY KEY,
+    doc_name       VARCHAR(512)  NOT NULL DEFAULT '',
+    file_name      VARCHAR(512)  NOT NULL DEFAULT '',
+    object_name    VARCHAR(1024) NOT NULL DEFAULT '',
+    content_type   VARCHAR(128)  NOT NULL DEFAULT '',
+    size_bytes     BIGINT        NOT NULL DEFAULT 0,
+    status         VARCHAR(32)   NOT NULL DEFAULT 'pending',
+    regulation_type VARCHAR(128) NOT NULL DEFAULT '',
+    version        VARCHAR(64)   NOT NULL DEFAULT '',
+    summary        TEXT          NOT NULL DEFAULT '',
+    summary_latency_ms INTEGER   NOT NULL DEFAULT 0,
+    chunk_count    INTEGER       NOT NULL DEFAULT 0,
+    parser_name    VARCHAR(128)  NOT NULL DEFAULT '',
+    index_name     VARCHAR(128)  NOT NULL DEFAULT '',
+    error_message  TEXT          NOT NULL DEFAULT '',
+    metadata       JSONB         NOT NULL DEFAULT '{}',
+    created_at     TIMESTAMPTZ   NOT NULL DEFAULT NOW(),
+    updated_at     TIMESTAMPTZ   NOT NULL DEFAULT NOW()
+);
+"""
+
+_COLUMNS = (
+    "doc_id", "doc_name", "file_name", "object_name", "content_type",
+    "size_bytes", "status", "regulation_type", "version", "summary",
+    "summary_latency_ms", "chunk_count", "parser_name", "index_name",
+    "error_message", "metadata", "created_at", "updated_at",
+)
+
+
+class PostgresDocumentRepository(DocumentRepository):
+    """DocumentRepository implementation backed by PostgreSQL."""
+
+    def __init__(self) -> None:
+        self._pool = ThreadedConnectionPool(
+            minconn=1,
+            maxconn=5,
+            host=settings.postgres_host,
+            port=settings.postgres_port,
+            user=settings.postgres_user,
+            password=settings.postgres_password,
+            dbname=settings.postgres_db,
+        )
+        self._ensure_schema()
+
+    def _ensure_schema(self) -> None:
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                cur.execute(_CREATE_TABLE)
+            conn.commit()
+
+    @contextmanager
+    def _conn(self):
+        conn = self._pool.getconn()
+        try:
+            yield conn
+        finally:
+            self._pool.putconn(conn)
+
+    # ------------------------------------------------------------------
+    # Serialization helpers
+    # ------------------------------------------------------------------
+
+    def _row_to_document(self, row: dict[str, Any]) -> Document:
+        return Document(
+            doc_id=row["doc_id"],
+            doc_name=row["doc_name"],
+            file_name=row["file_name"],
+            object_name=row["object_name"],
+            content_type=row["content_type"],
+            size_bytes=row["size_bytes"],
+            status=DocumentStatus(row["status"]),
+            regulation_type=row["regulation_type"],
+            version=row["version"],
+            summary=row["summary"],
+            summary_latency_ms=row["summary_latency_ms"],
+            chunk_count=row["chunk_count"],
+            parser_name=row["parser_name"],
+            index_name=row["index_name"],
+            error_message=row["error_message"],
+            metadata=row["metadata"] if isinstance(row["metadata"], dict) else json.loads(row["metadata"] or "{}"),
+            created_at=row["created_at"],
+            updated_at=row["updated_at"],
+        )
+
+    # ------------------------------------------------------------------
+    # DocumentRepository interface
+    # ------------------------------------------------------------------
+
+    def create(self, document: Document) -> Document:
+        sql = """
+            INSERT INTO documents
+                (doc_id, doc_name, file_name, object_name, content_type, size_bytes,
+                 status, regulation_type, version, summary, summary_latency_ms,
+                 chunk_count, parser_name, index_name, error_message, metadata,
+                 created_at, updated_at)
+            VALUES
+                (%(doc_id)s, %(doc_name)s, %(file_name)s, %(object_name)s, %(content_type)s,
+                 %(size_bytes)s, %(status)s, %(regulation_type)s, %(version)s, %(summary)s,
+                 %(summary_latency_ms)s, %(chunk_count)s, %(parser_name)s, %(index_name)s,
+                 %(error_message)s, %(metadata)s, %(created_at)s, %(updated_at)s)
+            ON CONFLICT (doc_id) DO NOTHING
+        """
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                cur.execute(sql, self._to_params(document))
+            conn.commit()
+        return document
+
+    def update(self, document: Document) -> Document:
+        document.updated_at = datetime.now(UTC)
+        sql = """
+            UPDATE documents SET
+                doc_name=%(doc_name)s, file_name=%(file_name)s, object_name=%(object_name)s,
+                content_type=%(content_type)s, size_bytes=%(size_bytes)s, status=%(status)s,
+                regulation_type=%(regulation_type)s, version=%(version)s, summary=%(summary)s,
+                summary_latency_ms=%(summary_latency_ms)s, chunk_count=%(chunk_count)s,
+                parser_name=%(parser_name)s, index_name=%(index_name)s,
+                error_message=%(error_message)s, metadata=%(metadata)s, updated_at=%(updated_at)s
+            WHERE doc_id=%(doc_id)s
+        """
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                cur.execute(sql, self._to_params(document))
+            conn.commit()
+        return document
+
+    def get(self, doc_id: str) -> Document | None:
+        sql = "SELECT * FROM documents WHERE doc_id = %s"
+        with self._conn() as conn:
+            with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
+                cur.execute(sql, (doc_id,))
+                row = cur.fetchone()
+        return self._row_to_document(dict(row)) if row else None
+
+    def list(self, limit: int | None = None) -> list[Document]:
+        sql = "SELECT * FROM documents ORDER BY updated_at DESC"
+        if limit is not None:
+            sql += f" LIMIT {int(limit)}"
+        with self._conn() as conn:
+            with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
+                cur.execute(sql)
+                rows = cur.fetchall()
+        return [self._row_to_document(dict(r)) for r in rows]
+
+    def delete(self, doc_id: str) -> bool:
+        sql = "DELETE FROM documents WHERE doc_id = %s"
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                cur.execute(sql, (doc_id,))
+                deleted = cur.rowcount > 0
+            conn.commit()
+        return deleted
+
+    def update_status(
+        self,
+        doc_id: str,
+        status: DocumentStatus,
+        *,
+        error_message: str = "",
+        chunk_count: int | None = None,
+        summary: str | None = None,
+        summary_latency_ms: int | None = None,
+        parser_name: str | None = None,
+        index_name: str | None = None,
+        metadata: dict | None = None,
+    ) -> Document | None:
+        document = self.get(doc_id)
+        if not document:
+            return None
+        document.status = status
+        document.error_message = error_message
+        if chunk_count is not None:
+            document.chunk_count = chunk_count
+        if summary is not None:
+            document.summary = summary
+        if summary_latency_ms is not None:
+            document.summary_latency_ms = summary_latency_ms
+        if parser_name is not None:
+            document.parser_name = parser_name
+        if index_name is not None:
+            document.index_name = index_name
+        if metadata:
+            document.metadata.update(metadata)
+        return self.update(document)
+
+    # ------------------------------------------------------------------
+    # Internal helpers
+    # ------------------------------------------------------------------
+
+    def _to_params(self, document: Document) -> dict[str, Any]:
+        return {
+            "doc_id": document.doc_id,
+            "doc_name": document.doc_name,
+            "file_name": document.file_name,
+            "object_name": document.object_name,
+            "content_type": document.content_type,
+            "size_bytes": document.size_bytes,
+            "status": document.status.value,
+            "regulation_type": document.regulation_type,
+            "version": document.version,
+            "summary": document.summary,
+            "summary_latency_ms": document.summary_latency_ms,
+            "chunk_count": document.chunk_count,
+            "parser_name": document.parser_name,
+            "index_name": document.index_name,
+            "error_message": document.error_message,
+            "metadata": json.dumps(document.metadata, ensure_ascii=False),
+            "created_at": document.created_at,
+            "updated_at": document.updated_at,
+        }

backend/app/infrastructure/storage/postgres_parse_artifact_store.py

@@ -0,0 +1,196 @@
+"""Implement infrastructure support for postgres parse artifact store."""
+
+from __future__ import annotations
+
+import json
+from contextlib import contextmanager
+from typing import Any
+
+import psycopg2
+import psycopg2.extras
+from psycopg2.pool import ThreadedConnectionPool
+
+from app.config.settings import settings
+from app.domain.documents import ParseArtifactStore
+
+_CREATE_STRUCTURE_NODES = """
+CREATE TABLE IF NOT EXISTS structure_nodes (
+    id        SERIAL PRIMARY KEY,
+    doc_id    VARCHAR(128) NOT NULL,
+    unique_id VARCHAR(128),
+    page      INTEGER      NOT NULL DEFAULT 0,
+    idx       INTEGER      NOT NULL DEFAULT 0,
+    level     INTEGER      NOT NULL DEFAULT 0,
+    title     TEXT         NOT NULL DEFAULT '',
+    type      VARCHAR(64),
+    sub_type  VARCHAR(64),
+    created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
+    CONSTRAINT fk_sn_doc FOREIGN KEY (doc_id) REFERENCES documents(doc_id) ON DELETE CASCADE
+);
+CREATE INDEX IF NOT EXISTS idx_structure_nodes_doc_id ON structure_nodes(doc_id);
+"""
+
+_CREATE_SEMANTIC_BLOCKS = """
+CREATE TABLE IF NOT EXISTS semantic_blocks (
+    id           SERIAL PRIMARY KEY,
+    doc_id       VARCHAR(128) NOT NULL,
+    semantic_id  VARCHAR(128) NOT NULL,
+    block_type   VARCHAR(64)  NOT NULL DEFAULT '',
+    page_start   INTEGER      NOT NULL DEFAULT 0,
+    page_end     INTEGER      NOT NULL DEFAULT 0,
+    section_path JSONB        NOT NULL DEFAULT '[]',
+    section_level INTEGER     NOT NULL DEFAULT 0,
+    section_title VARCHAR(512) NOT NULL DEFAULT '',
+    source_ids   JSONB        NOT NULL DEFAULT '[]',
+    text         TEXT         NOT NULL DEFAULT '',
+    created_at   TIMESTAMPTZ  NOT NULL DEFAULT NOW(),
+    CONSTRAINT fk_sb_doc FOREIGN KEY (doc_id) REFERENCES documents(doc_id) ON DELETE CASCADE,
+    CONSTRAINT uq_semantic_blocks UNIQUE (doc_id, semantic_id)
+);
+CREATE INDEX IF NOT EXISTS idx_semantic_blocks_doc_id ON semantic_blocks(doc_id);
+"""
+
+
+class PostgresParseArtifactStore(ParseArtifactStore):
+    """ParseArtifactStore implementation backed by PostgreSQL.
+
+    Requires the `documents` table to exist first (created by PostgresDocumentRepository).
+    """
+
+    def __init__(self) -> None:
+        self._pool = ThreadedConnectionPool(
+            minconn=1,
+            maxconn=5,
+            host=settings.postgres_host,
+            port=settings.postgres_port,
+            user=settings.postgres_user,
+            password=settings.postgres_password,
+            dbname=settings.postgres_db,
+        )
+        self._ensure_schema()
+
+    def _ensure_schema(self) -> None:
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                cur.execute(_CREATE_STRUCTURE_NODES)
+                cur.execute(_CREATE_SEMANTIC_BLOCKS)
+            conn.commit()
+
+    @contextmanager
+    def _conn(self):
+        conn = self._pool.getconn()
+        try:
+            yield conn
+        finally:
+            self._pool.putconn(conn)
+
+    # ------------------------------------------------------------------
+    # ParseArtifactStore interface
+    # ------------------------------------------------------------------
+
+    def save(
+        self,
+        doc_id: str,
+        structure_nodes: list[dict],
+        semantic_blocks: list[dict],
+    ) -> None:
+        """Persist structure nodes and semantic blocks, replacing any existing records."""
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                # Delete existing records first to keep save idempotent.
+                cur.execute("DELETE FROM structure_nodes WHERE doc_id = %s", (doc_id,))
+                cur.execute("DELETE FROM semantic_blocks WHERE doc_id = %s", (doc_id,))
+
+                if structure_nodes:
+                    psycopg2.extras.execute_values(
+                        cur,
+                        """
+                        INSERT INTO structure_nodes
+                            (doc_id, unique_id, page, idx, level, title, type, sub_type)
+                        VALUES %s
+                        """,
+                        [
+                            (
+                                doc_id,
+                                node.get("unique_id"),
+                                int(node.get("page", 0) or 0),
+                                int(node.get("index", 0) or 0),
+                                int(node.get("level", 0) or 0),
+                                str(node.get("title", "")),
+                                node.get("type"),
+                                node.get("sub_type"),
+                            )
+                            for node in structure_nodes
+                        ],
+                    )
+
+                if semantic_blocks:
+                    psycopg2.extras.execute_values(
+                        cur,
+                        """
+                        INSERT INTO semantic_blocks
+                            (doc_id, semantic_id, block_type, page_start, page_end,
+                             section_path, section_level, section_title, source_ids, text)
+                        VALUES %s
+                        """,
+                        [
+                            (
+                                doc_id,
+                                block.get("semantic_id", ""),
+                                block.get("block_type", ""),
+                                int(block.get("page_start", 0) or 0),
+                                int(block.get("page_end", 0) or 0),
+                                json.dumps(block.get("section_path", []), ensure_ascii=False),
+                                int(block.get("section_level", 0) or 0),
+                                str(block.get("section_title", "")),
+                                json.dumps(block.get("source_ids", []), ensure_ascii=False),
+                                str(block.get("text", "")),
+                            )
+                            for block in semantic_blocks
+                        ],
+                    )
+            conn.commit()
+
+    def delete(self, doc_id: str) -> None:
+        """Remove all parse artifacts for a document (ON DELETE CASCADE handles child rows)."""
+        with self._conn() as conn:
+            with conn.cursor() as cur:
+                cur.execute("DELETE FROM structure_nodes WHERE doc_id = %s", (doc_id,))
+                cur.execute("DELETE FROM semantic_blocks WHERE doc_id = %s", (doc_id,))
+            conn.commit()
+
+    def get_semantic_blocks(self, doc_id: str) -> list[dict[str, Any]]:
+        """Return all semantic blocks for a document ordered by id."""
+        sql = """
+            SELECT semantic_id, block_type, page_start, page_end,
+                   section_path, section_level, section_title, source_ids, text
+            FROM semantic_blocks
+            WHERE doc_id = %s
+            ORDER BY id
+        """
+        with self._conn() as conn:
+            with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
+                cur.execute(sql, (doc_id,))
+                rows = cur.fetchall()
+        results = []
+        for row in rows:
+            item = dict(row)
+            for key in ("section_path", "source_ids"):
+                if isinstance(item[key], str):
+                    item[key] = json.loads(item[key])
+            results.append(item)
+        return results
+
+    def get_structure_nodes(self, doc_id: str) -> list[dict[str, Any]]:
+        """Return all structure nodes for a document ordered by idx."""
+        sql = """
+            SELECT unique_id, page, idx, level, title, type, sub_type
+            FROM structure_nodes
+            WHERE doc_id = %s
+            ORDER BY idx
+        """
+        with self._conn() as conn:
+            with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
+                cur.execute(sql, (doc_id,))
+                rows = cur.fetchall()
+        return [dict(r) for r in rows]

backend/app/infrastructure/vectorstore/cross_encoder_reranker.py

@@ -0,0 +1,84 @@
+"""Implement cross-encoder reranking via an OpenAI-compatible reranker API."""
+
+from __future__ import annotations
+
+import time
+
+import requests
+from loguru import logger
+
+from app.config.settings import settings
+from app.domain.retrieval import Reranker, RetrievedChunk
+
+
+class OpenAICompatibleReranker(Reranker):
+    """Call a TEI / Cohere-style reranker endpoint to re-score retrieved chunks."""
+
+    def __init__(
+        self,
+        base_url: str | None = None,
+        model: str | None = None,
+        api_key: str | None = None,
+        timeout: int = 30,
+    ) -> None:
+        self._base_url = (base_url or settings.reranker_base_url).rstrip("/")
+        self._model = model or settings.reranker_model
+        self._api_key = api_key or settings.reranker_api_key
+        self._timeout = timeout
+
+    def rerank(self, query: str, chunks: list[RetrievedChunk], top_k: int) -> list[RetrievedChunk]:
+        """Return up to top_k chunks re-sorted by cross-encoder score."""
+        if not chunks:
+            return []
+
+        texts = [chunk.content for chunk in chunks]
+        start = time.time()
+        try:
+            scores = self._call_reranker(query, texts)
+        except Exception as exc:
+            logger.warning("Reranker call failed ({}), falling back to original order: {}", type(exc).__name__, exc)
+            return chunks[:top_k]
+
+        elapsed_ms = int((time.time() - start) * 1000)
+        logger.debug("Reranker scored {} chunks in {}ms", len(chunks), elapsed_ms)
+
+        ranked = sorted(
+            [(score, chunk) for score, chunk in zip(scores, chunks)],
+            key=lambda x: x[0],
+            reverse=True,
+        )
+        result = []
+        for score, chunk in ranked[:top_k]:
+            chunk.score = float(score)
+            result.append(chunk)
+        return result
+
+    def _call_reranker(self, query: str, texts: list[str]) -> list[float]:
+        """Call the reranker API and return a score per text."""
+        headers = {"Content-Type": "application/json"}
+        if self._api_key:
+            headers["Authorization"] = f"Bearer {self._api_key}"
+
+        # Try TEI format first: POST /rerank
+        payload = {"query": query, "texts": texts, "raw_scores": False, "return_text": False}
+        url = f"{self._base_url}/rerank"
+        resp = requests.post(url, json=payload, headers=headers, timeout=self._timeout)
+
+        if resp.status_code == 404:
+            # Fall back to Cohere / OpenAI-style: POST /v1/rerank
+            payload_v1 = {"model": self._model, "query": query, "documents": texts}
+            url = f"{self._base_url}/v1/rerank"
+            resp = requests.post(url, json=payload_v1, headers=headers, timeout=self._timeout)
+
+        resp.raise_for_status()
+        data = resp.json()
+
+        # TEI response: list of {"index": N, "score": F}
+        if isinstance(data, list):
+            ordered = sorted(data, key=lambda x: x["index"])
+            return [float(item["score"]) for item in ordered]
+
+        # Cohere/OpenAI response: {"results": [{"index": N, "relevance_score": F}]}
+        results = data.get("results", [])
+        ordered = sorted(results, key=lambda x: x["index"])
+        return [float(item.get("relevance_score", item.get("score", 0))) for item in ordered]

backend/app/infrastructure/vectorstore/milvus_vector_index.py

@@ -100,14 +100,42 @@ class MilvusVectorIndex(VectorIndex):
         result = self.collection.delete(f'doc_id == "{doc_id}"')
         return len(result.primary_keys)
 
+    def _parse_filters(self, filters: str | None) -> str | None:
+        """Parse filter string into Milvus expression."""
+        if not filters or not filters.strip():
+            return None
+
+        filters = filters.strip()
+
+        # Check if already a Milvus expression (contains operators)
+        if any(op in filters for op in ["==", "!=", "in", "not in", ">", "<", ">=", "<=", "and", "or"]):
+            return filters
+
+        # Parse simple regulation_type filter
+        # Support: "GB" or "GB,UN-ECE" or "GB, UN-ECE"
+        types = [t.strip() for t in filters.split(",") if t.strip()]
+
+        if not types:
+            return None
+
+        if len(types) == 1:
+            # Single value: regulation_type == "GB"
+            return f'regulation_type == "{types[0]}"'
+        else:
+            # Multiple values: regulation_type in ["GB", "UN-ECE"]
+            quoted_types = [f'"{t}"' for t in types]
+            return f'regulation_type in [{", ".join(quoted_types)}]'
+
     def search(self, query_vector: list[float], top_k: int, filters: str | None = None) -> list[RetrievedChunk]:
         """Handle search for the Milvus Vector Index instance."""
+        milvus_expr = self._parse_filters(filters)
+
         results = self.collection.search(
             data=[query_vector],
             anns_field="embedding",
             param={"metric_type": "COSINE", "params": {"nprobe": settings.milvus_nprobe}},
             limit=top_k,
-            filter=filters,
+            expr=milvus_expr,
             output_fields=[
                 "doc_id",
                 "doc_name",
@@ -145,6 +173,49 @@ class MilvusVectorIndex(VectorIndex):
                 )
         return payload
 
+    def count_by_document(self) -> dict[str, int]:
+        """Return doc_id -> chunk count from Milvus."""
+        try:
+            rows = self.collection.query(expr="doc_id != \"\"", output_fields=["doc_id"])
+        except Exception:
+            return {}
+        counts: dict[str, int] = {}
+        for row in rows:
+            doc_id = row.get("doc_id", "")
+            if doc_id:
+                counts[doc_id] = counts.get(doc_id, 0) + 1
+        return counts
+
+    def list_document_metadata(self) -> list[dict]:
+        """Return one metadata row per document from Milvus (single query, no embeddings)."""
+        try:
+            rows = self.collection.query(
+                expr="doc_id != \"\"",
+                output_fields=["doc_id", "doc_name", "regulation_type", "version"],
+            )
+        except Exception:
+            return []
+
+        seen: dict[str, dict] = {}
+        counts: dict[str, int] = {}
+        for row in rows:
+            doc_id = row.get("doc_id", "")
+            if not doc_id:
+                continue
+            counts[doc_id] = counts.get(doc_id, 0) + 1
+            if doc_id not in seen:
+                seen[doc_id] = {
+                    "doc_id": doc_id,
+                    "doc_name": row.get("doc_name", ""),
+                    "regulation_type": row.get("regulation_type", ""),
+                    "version": row.get("version", ""),
+                }
+
+        return [
+            {**meta, "chunk_count": counts[meta["doc_id"]]}
+            for meta in seen.values()
+        ]
+
     def health(self) -> dict:
         """Handle health for the Milvus Vector Index instance."""
         return {

backend/app/schemas/compliance.py

@@ -74,6 +74,7 @@ class ComplianceResult(BaseModel):
 class ComplianceChatRequest(BaseModel):
     """Define the Compliance Chat Request API model."""
     query: str
+    segment_context: Optional[str] = None
 
 
 class AnalyzeResponse(BaseModel):

backend/app/schemas/rag.py

@@ -10,6 +10,8 @@ class RagChatRequest(BaseModel):
     """Define the Rag Chat Request API model."""
     query: str
     top_k: int = 5
+    session_id: Optional[str] = None
+    filters: Optional[str] = None
 
 
 class RetrievedDoc(BaseModel):

backend/app/services/llm/deepseek_client.py

@@ -95,6 +95,57 @@ class DeepSeekClient(BaseLLMClient):
                 error=str(e)
             )
 
+    def stream_chat(
+        self,
+        messages: List[Dict[str, str]],
+        max_tokens: Optional[int] = None,
+        temperature: Optional[float] = None,
+        **kwargs
+    ):
+        """Stream chat for the Deep Seek Client instance."""
+        try:
+            payload = {
+                "model": self.config.model,
+                "messages": messages,
+                "max_tokens": max_tokens or self.config.max_tokens,
+                "temperature": temperature or self.config.temperature,
+                "top_p": kwargs.get("top_p", self.config.top_p),
+                "stream": True
+            }
+
+            with self._client.stream("POST", "/chat/completions", json=payload) as response:
+                response.raise_for_status()
+                for line in response.iter_lines():
+                    if not line or line.startswith(b":"):
+                        continue
+
+                    line_str = line.decode("utf-8").strip()
+                    if not line_str.startswith("data: "):
+                        continue
+
+                    data_str = line_str[6:]
+                    if data_str == "[DONE]":
+                        break
+
+                    try:
+                        import json
+                        data = json.loads(data_str)
+                        choices = data.get("choices", [])
+                        if choices:
+                            delta = choices[0].get("delta", {})
+                            content = delta.get("content", "")
+                            if content:
+                                yield content
+                    except json.JSONDecodeError:
+                        continue
+
+        except httpx.HTTPStatusError as e:
+            logger.error(f"DeepSeek Stream API错误: {e.response.status_code}")
+            yield ""
+        except Exception as e:
+            logger.error(f"DeepSeek Stream调用失败: {e}")
+            yield ""
+
     def get_available_models(self) -> List[str]:
         """Return available models for the Deep Seek Client instance."""
         return self.SUPPORTED_MODELS

backend/app/shared/bootstrap.py

@@ -17,18 +17,31 @@ from app.infrastructure.parser.vector_chunk_builder import AliyunVectorChunkBuil
 from app.infrastructure.session.in_memory_conversation_store import InMemoryConversationStore
 from app.infrastructure.storage.json_document_repository import JsonDocumentRepository
 from app.infrastructure.storage.minio_binary_store import MinioDocumentBinaryStore
+from app.infrastructure.storage.postgres_document_repository import PostgresDocumentRepository
+from app.infrastructure.storage.postgres_parse_artifact_store import PostgresParseArtifactStore
 from app.infrastructure.vectorstore.dense_retriever import DenseRetriever
 from app.infrastructure.vectorstore.milvus_vector_index import MilvusVectorIndex
+from app.infrastructure.vectorstore.cross_encoder_reranker import OpenAICompatibleReranker
 # Keep shared wiring centralized so dependency construction remains consistent.
 
 
 
 @lru_cache
-def get_document_repository() -> JsonDocumentRepository:
+def get_document_repository():
-    """Return document repository."""
+    """Return document repository (json or postgres, controlled by settings)."""
+    if settings.document_repository_backend == "postgres":
+        return PostgresDocumentRepository()
     return JsonDocumentRepository(settings.document_metadata_path)
 
 
+@lru_cache
+def get_parse_artifact_store():
+    """Return parse artifact store, or None when postgres backend is not enabled."""
+    if settings.document_repository_backend == "postgres":
+        return PostgresParseArtifactStore()
+    return None
+
+
 @lru_cache
 def get_binary_store() -> MinioDocumentBinaryStore:
     """Return binary store."""
@@ -66,6 +79,14 @@ def get_vector_index() -> MilvusVectorIndex:
     return MilvusVectorIndex()
 
 
+@lru_cache
+def get_reranker():
+    """Return reranker if enabled, else None."""
+    if settings.reranker_enabled and settings.reranker_base_url:
+        return OpenAICompatibleReranker()
+    return None
+
+
 @lru_cache
 def get_retrieval_service() -> KnowledgeRetrievalService:
     """Return retrieval service."""
@@ -73,7 +94,11 @@ def get_retrieval_service() -> KnowledgeRetrievalService:
         embedding_provider=get_embedding_provider(),
         vector_index=get_vector_index(),
     )
-    return KnowledgeRetrievalService(retriever=retriever)
+    return KnowledgeRetrievalService(
+        retriever=retriever,
+        reranker=get_reranker(),
+        reranker_top_k=settings.reranker_top_k,
+    )
 
 
 @lru_cache
@@ -86,6 +111,7 @@ def get_document_command_service() -> DocumentCommandService:
         chunk_builder=get_chunk_builder(),
         embedding_provider=get_embedding_provider(),
         vector_index=get_vector_index(),
+        parse_artifact_store=get_parse_artifact_store(),
     )
 
 
@@ -95,6 +121,7 @@ def get_document_query_service() -> DocumentQueryService:
     return DocumentQueryService(
         document_repository=get_document_repository(),
         binary_store=get_binary_store(),
+        vector_index=get_vector_index(),
     )
 
 

backend/requirements.txt

@@ -13,6 +13,7 @@ tenacity>=8.2.0
 
 pymilvus>=2.4.0
 minio>=7.1.0
+psycopg2-binary>=2.9.0
 
 pymupdf>=1.24.0
 python-docx>=1.1.0

dev.sh

@@ -12,7 +12,8 @@ API_PID_FILE="$LOG_DIR/api.pid"
 FRONTEND_PID_FILE="$LOG_DIR/frontend.pid"
 API_LOG_FILE="$LOG_DIR/api.log"
 FRONTEND_LOG_FILE="$LOG_DIR/frontend.log"
-DOCKER_CONTAINERS="milvus minio redis postgres"
+DISPLAY_HOST="localhost"
+SERVICE_HOST="6.86.80.8"
 
 RED='\033[0;31m'
 GREEN='\033[0;32m'
@@ -54,6 +55,51 @@ ensure_log_dir() {
     mkdir -p "$LOG_DIR"
 }
 
+check_tcp_connectivity() {
+    local host="$1"
+    local port="$2"
+
+    if command -v nc > /dev/null 2>&1; then
+        nc -z -w 3 "$host" "$port" > /dev/null 2>&1
+        return
+    fi
+
+    require_python_bootstrap
+    "$PYTHON_BOOTSTRAP" - <<PY > /dev/null 2>&1
+import socket
+import sys
+
+try:
+    with socket.create_connection(("${host}", ${port}), timeout=3):
+        pass
+except Exception:
+    sys.exit(1)
+
+sys.exit(0)
+PY
+}
+
+check_foundation_services() {
+    local name
+    local port
+
+    for service in \
+        "Milvus:19530" \
+        "MinIO API:9000" \
+        "MinIO Console:9001" \
+        "Redis:6379" \
+        "PostgreSQL:5432"
+    do
+        name="${service%%:*}"
+        port="${service##*:}"
+        if check_tcp_connectivity "$SERVICE_HOST" "$port"; then
+            success "${name}: ${SERVICE_HOST}:${port} 可连通"
+        else
+            warn "${name}: ${SERVICE_HOST}:${port} 不可连通"
+        fi
+    done
+}
+
 print_header() {
     echo ""
     echo -e "${CYAN}========================================${NC}"
@@ -197,21 +243,8 @@ run_setup() {
     success "前端依赖安装完成"
     echo ""
 
-    info "[4/4] 检查 Docker 基础服务"
+    info "[4/4] 检查 6.86.80.8 基础服务连通性"
-    if command -v docker > /dev/null 2>&1; then
+    check_foundation_services
-        local container
-        for container in $DOCKER_CONTAINERS; do
-            if docker ps --format '{{.Names}}' | grep -q "^${container}$"; then
-                success "${container}: 运行中"
-            elif docker ps -a --format '{{.Names}}' | grep -q "^${container}$"; then
-                warn "${container}: 已创建但未运行"
-            else
-                warn "${container}: 未找到容器"
-            fi
-        done
-    else
-        warn "未检测到 Docker，已跳过容器检查"
-    fi
 
     echo ""
     success "环境初始化完成"
@@ -223,7 +256,7 @@ run_setup() {
 
 api_health_ok() {
     if command -v curl > /dev/null 2>&1; then
-        curl -fsS "http://localhost:$API_PORT/health" > /dev/null 2>&1
+        curl -fsS "http://${DISPLAY_HOST}:$API_PORT/health" > /dev/null 2>&1
         return
     fi
 
@@ -233,7 +266,7 @@ import sys
 from urllib.request import urlopen
 
 try:
-    with urlopen("http://localhost:${API_PORT}/health", timeout=3) as response:
+    with urlopen("http://${DISPLAY_HOST}:${API_PORT}/health", timeout=3) as response:
         body = response.read().decode("utf-8", errors="ignore")
     sys.exit(0 if "healthy" in body.lower() else 1)
 except Exception:
@@ -260,9 +293,9 @@ start_api() {
     if [ "$mode" = "foreground" ]; then
         print_header "AI+合规智能中枢 - 启动 API"
         echo "运行模式: 前台调试（带 --reload）"
-        echo "服务地址: http://localhost:$API_PORT"
+        echo "服务地址: http://${DISPLAY_HOST}:$API_PORT"
-        echo "文档地址: http://localhost:$API_PORT/docs"
+        echo "文档地址: http://${DISPLAY_HOST}:$API_PORT/docs"
-        echo "健康检查: http://localhost:$API_PORT/health"
+        echo "健康检查: http://${DISPLAY_HOST}:$API_PORT/health"
         echo ""
         exec "$VENV_PYTHON" -m uvicorn app.main:app --host "$API_HOST" --port "$API_PORT" --reload
     fi
@@ -274,8 +307,8 @@ start_api() {
 
     if is_pid_running "$pid"; then
         success "API 启动成功 (PID: $pid)"
-        echo "  地址: http://localhost:$API_PORT"
+        echo "  地址: http://${DISPLAY_HOST}:$API_PORT"
-        echo "  文档: http://localhost:$API_PORT/docs"
+        echo "  文档: http://${DISPLAY_HOST}:$API_PORT/docs"
         echo "  日志: $API_LOG_FILE"
     else
         rm -f "$API_PID_FILE"
@@ -316,7 +349,7 @@ start_frontend() {
 
     if is_pid_running "$pid"; then
         success "前端启动成功 (PID: $pid)"
-        echo "  地址: http://localhost:$FRONTEND_PORT"
+        echo "  地址: http://${DISPLAY_HOST}:$FRONTEND_PORT"
         echo "  模式: $mode"
         echo "  日志: $FRONTEND_LOG_FILE"
     else
@@ -407,6 +440,8 @@ run_status() {
     local frontend_running=false
     local pid
     local port_listener
+    local service_name
+    local service_port
 
     echo -e "${YELLOW}API 服务:${NC}"
     pid="$(read_pid "$API_PID_FILE")"
@@ -432,8 +467,8 @@ run_status() {
             warn "  健康检查: 未通过"
         fi
     fi
-    echo "  地址:    http://localhost:$API_PORT"
+    echo "  地址:    http://${DISPLAY_HOST}:$API_PORT"
-    echo "  文档:    http://localhost:${API_PORT}/docs"
+    echo "  文档:    http://${DISPLAY_HOST}:${API_PORT}/docs"
     echo ""
 
     echo -e "${YELLOW}前端服务:${NC}"
@@ -453,24 +488,25 @@ run_status() {
         fi
     fi
     echo "  模式:    $FRONTEND_MODE"
-    echo "  地址:    http://localhost:$FRONTEND_PORT"
+    echo "  地址:    http://${DISPLAY_HOST}:$FRONTEND_PORT"
     echo ""
 
-    echo -e "${YELLOW}Docker 服务:${NC}"
+    echo -e "${YELLOW}基础服务连通性:${NC}"
-    if command -v docker > /dev/null 2>&1; then
+    for service in \
-        local container
+        "Milvus:19530" \
-        for container in $DOCKER_CONTAINERS; do
+        "MinIO API:9000" \
-            if docker ps --format '{{.Names}}' | grep -q "^${container}$"; then
+        "MinIO Console:9001" \
-                success "  ${container}: 运行中"
+        "Redis:6379" \
-            elif docker ps -a --format '{{.Names}}' | grep -q "^${container}$"; then
+        "PostgreSQL:5432"
-                warn "  ${container}: 已停止"
+    do
+        service_name="${service%%:*}"
+        service_port="${service##*:}"
+        if check_tcp_connectivity "$SERVICE_HOST" "$service_port"; then
+            success "  ${service_name}: ${SERVICE_HOST}:${service_port} 可连通"
         else
-                warn "  ${container}: 未创建"
+            warn "  ${service_name}: ${SERVICE_HOST}:${service_port} 不可连通"
         fi
     done
-    else
-        warn "  Docker 未安装，已跳过"
-    fi
 
     echo ""
     if [ "$api_running" = true ] && [ "$frontend_running" = true ]; then
@@ -526,7 +562,7 @@ AI+合规智能中枢统一脚本
   setup
     进行一次性的本地初始化。
     包含 Python 版本检查、.venv 虚拟环境创建、后端依赖安装、前端 npm install、
-    以及 Docker 基础容器状态检查。
+    以及 6.86.80.8 基础服务端口连通性检查。
 
   start
     启动服务。默认行为等同于 ./dev.sh start all。
@@ -548,7 +584,7 @@ AI+合规智能中枢统一脚本
     restart frontend --mode static 可直接切换前端启动模式。
 
   status
-    查看 API、前端、Docker 基础容器的状态。
+    查看 API、前端、6.86.80.8 基础服务的状态。
     API 状态包含健康检查；前端状态包含当前模式和访问地址。
 
   logs

docker/docker-compose.yml

@@ -58,7 +58,7 @@ services:
       retries: 5
     restart: unless-stopped
 
-  # PostgreSQL数据库 (可选)
+  # PostgreSQL数据库 (可选，启用 DOCUMENT_REPOSITORY_BACKEND=postgres 时使用)
   postgres:
     image: postgres:15-alpine
     container_name: postgres
@@ -71,7 +71,7 @@ services:
     volumes:
       - postgres_data:/var/lib/postgresql/data
     healthcheck:
-      test: ["CMD-SHELL", "pg_isready -U compliance"]
+      test: ["CMD-SHELL", "pg_isready -U compliance -d compliance_db"]
       interval: 30s
       timeout: 10s
       retries: 5

docs/superpowers/specs/2026-05-20-rag-dialogue-optimization-design.md

@@ -0,0 +1,145 @@
+# 法规对话模块优化设计文档
+
+**日期**: 2026-05-20  
+**状态**: 已批准，实施中
+
+---
+
+## 背景
+
+当前法规对话模块存在以下问题：
+1. `compliance.py` `/compliance/chat/{segment_id}` 返回硬编码 Mock 数据
+2. `rag.py` `/rag/chat` 返回硬编码 Mock 数据（前端实际调用 `/agent/chat/stream`，此路由可统一）
+3. 前端快速问题列表硬编码在 `rag.ts`，未调用后端
+4. 仅有 Dense 向量检索（COSINE），无 BM25 混合检索与精排
+5. LLM 输出的 `[1][2]` 引用编号未在前端内联高亮
+6. 会话存储仅为内存（100条上限，30分钟过期）
+
+---
+
+## 方案：分层优先（4个阶段）
+
+### Phase 1 — 接入真实服务（Week 1）
+
+**目标**：消灭所有 Mock，让系统真正可用。
+
+#### 后端变更
+
+**`backend/app/schemas/compliance.py`**
+- `ComplianceChatRequest` 新增 `segment_context: str | None = None`
+
+**`backend/app/api/routes/compliance.py`**
+- 移除 `get_mock_compliance_chat_response` 导入
+- `/compliance/chat/{segment_id}` 接入 `get_agent_conversation_service().stream_chat()`
+- 将 `segment_context` 拼接到 query 前缀作为上下文
+- 将 agent `content` 事件翻译为 `{"type":"chunk","text":"..."}` 格式，保持前端兼容
+
+**`backend/app/api/routes/rag.py`**
+- 移除 `get_mock_retrieval`、`get_mock_rag_answer` 导入
+- `/rag/chat` 接入 `get_agent_conversation_service().stream_chat()`
+- 翻译 agent 事件为 rag 格式（`retrieved`/`chunk`/`done`）
+
+**`backend/app/schemas/rag.py`**
+- `RagChatRequest` 新增 `session_id: str | None = None`，`filters: str | None = None`
+
+#### 前端变更
+
+**`frontend/src/api/rag.ts`**
+- `getQuickQuestions()` 改为真实调用 `GET /api/v1/rag/quick-questions`，失败时降级为本地数组
+
+**`frontend/src/api/compliance.ts`**
+- `complianceChat()` 新增第三个参数 `segmentContext: string | undefined`，传入 request body
+
+**`frontend/src/pages/Compliance/CompliancePage.tsx`**
+- `sendChatMessage()` 中构建 `segmentContext`（intent + content 摘要 + 法规名）
+- 传给 `complianceChat()`
+
+---
+
+### Phase 2 — 混合检索 + Reranking（Week 2-3）
+
+**目标**：提升召回质量（BM25 + dense RRF融合）+ 精排。
+
+#### 2a — Cross-Encoder Reranking（优先，无需 schema 变更）
+
+- 新增端口 `backend/app/domain/retrieval/ports.py`: `Reranker` ABC
+- 新增适配器 `backend/app/infrastructure/vectorstore/cross_encoder_reranker.py`
+  - 调用 OpenAI-compatible reranker API（BAAI/bge-reranker-v2-m3）
+- 修改 `KnowledgeRetrievalService`：先 retrieve top-20，再 rerank 到 top-5
+- 新增 settings: `reranker_enabled: bool = False`，`reranker_model: str`，`reranker_top_k: int = 5`
+
+#### 2b — Milvus Sparse BM25（需 schema 迁移）
+
+- Milvus collection 新增 `sparse_embedding SPARSE_FLOAT_VECTOR` 字段
+- 新增端口 `SparseEmbeddingProvider`（sparse embed 接口）
+- 适配器优先使用 BGE-M3 API（同时输出 dense + sparse），不可用时降级为 TF-IDF keyword weights
+- `MilvusVectorIndex.upsert()` 同时写入 sparse 向量
+- `MilvusVectorIndex.search()` 改为 hybrid search（`WeightedRanker` 或 `RRFRanker`）
+- 提供一次性迁移脚本：dump 所有 chunks → recreate collection → re-embed → re-insert
+
+---
+
+### Phase 3 — 引用溯源 + 筛选 UI（Week 4）
+
+**目标**：答案文本中 `[1][2]` 可点击跳转原文片段；法规类型/版本可筛选。
+
+#### 引用内联解析
+
+- 新增 React 组件 `CitedAnswer`：接受 `text` + `sources[]`
+  - 用正则 `/\[(\d+)\]/g` 拆分文本，将 `[N]` 渲染为可点击 `<cite>` 元素
+  - 点击高亮/滚动到来源面板对应条目
+- `RagChatPage.tsx` 将 assistant 消息改用 `CitedAnswer` 组件渲染
+- 来源面板各条目加 `id="source-N"` 属性
+
+#### 法规筛选 UI
+
+- `RagChatPage.tsx` 在输入框上方加筛选栏：`regulation_type` 下拉 + `version` 输入
+- 筛选值作为 `filters` 参数传到 `/agent/chat/stream`
+- `MilvusVectorIndex.search()` 解析 `filters` 字符串为 Milvus expr（如 `regulation_type == "GB"`）
+
+#### 快速问题动态化
+
+- 后端 `/rag/quick-questions` 改为从 settings 或配置文件加载，不硬编码
+- 前端已在 Phase 1 中改为调用后端
+
+---
+
+### Phase 4 — 会话持久化 + 上下文压缩（Week 5）
+
+**目标**：长对话不丢失；上下文过长时智能压缩。
+
+#### PostgreSQL 会话存储
+
+- 新增 `backend/app/infrastructure/session/postgres_conversation_store.py`
+  - 实现 `ConversationStore` port
+  - 复用现有 PostgreSQL 连接
+  - DDL: `conversation_sessions` + `conversation_messages` 两张表
+- 新增 settings: `conversation_store_backend: str = "memory"`
+- `bootstrap.py` 按 settings 切换实现
+
+#### 上下文压缩
+
+- 在 `AgentConversationService` 中，当对话轮数 > N 时，将早期消息用 LLM 摘要
+  - 摘要替换为一条 `system` 消息 `"对话摘要：..."`
+- 新增 `AnswerGenerator.summarize(messages) -> str` 方法
+
+---
+
+## 关键设计决策
+
+| 决策 | 选择 | 原因 |
+|------|------|------|
+| BM25 实现 | Milvus sparse vectors | 不引入新服务，Milvus 2.4+ 原生支持 |
+| Reranking | API-based cross-encoder | 复用现有 OpenAI-compatible 接口 |
+| 会话持久化 | PostgreSQL | 复用现有 PostgreSQL 基础设施 |
+| 引用解析 | 前端纯客户端 | LLM 已输出 [N] 编号，无需后端改动 |
+| segment_context | 前端构建传后端 | 合规结果存在前端状态，无需后端持久化 |
+
+---
+
+## 验证标准
+
+- Phase 1: 合规对话面板返回真实法规检索结果，不再固定响应
+- Phase 2: 相同 query 在 hybrid 模式下比 dense-only 召回更相关结果
+- Phase 3: 点击答案中的 `[1]` 能跳转到来源面板第一条
+- Phase 4: 刷新页面后历史对话仍可恢复

frontend/src/api/compliance.ts

@@ -31,11 +31,18 @@ export async function getComplianceResult(
 export function complianceChat(
   segmentId: number,
   query: string,
+  segmentContext: string | undefined,
   onMessage: (data: SSEMessage) => void,
   onError?: (error: Error) => void,
   onComplete?: () => void
 ): void {
-  void streamSSE<SSEMessage>(`/compliance/chat/${segmentId}`, { query }, onMessage, onError, onComplete);
+  void streamSSE<SSEMessage>(
+    `/compliance/chat/${segmentId}`,
+    { query, segment_context: segmentContext },
+    onMessage,
+    onError,
+    onComplete,
+  );
 }
 
 export type { ComplianceResult, SSEMessage };

frontend/src/api/docs.ts

@@ -6,7 +6,11 @@ interface BackendDocumentItem {
   doc_name: string;
   status: string;
   chunk_count: number;
+  size_bytes?: number;
+  summary?: string;
   updated_at?: string;
+  regulation_type?: string;
+  version?: string;
 }
 
 interface BackendDocumentListResponse {
@@ -44,6 +48,7 @@ export interface RegulationSearchResponse {
 }
 
 function mapDoc(item: BackendDocumentItem): DocInfo {
+  const sizeMB = item.size_bytes ? (item.size_bytes / (1024 * 1024)).toFixed(1) + 'MB' : '';
   return {
     id: item.doc_id,
     name: item.doc_name,
@@ -51,14 +56,23 @@ function mapDoc(item: BackendDocumentItem): DocInfo {
     status: item.status,
     updated_at: item.updated_at,
     download_url: `${API_BASE_URL}/documents/download/${item.doc_id}`,
+    size_text: sizeMB,
+    summary: item.summary,
+    regulation_type: item.regulation_type,
+    version: item.version,
   };
 }
 
-export async function uploadDocument(file: File): Promise<DocUploadResponse> {
+export async function uploadDocument(
+  file: File,
+  opts?: { regulationType?: string; version?: string }
+): Promise<DocUploadResponse> {
   const formData = new FormData();
   formData.append('file', file);
   formData.append('doc_name', file.name);
   formData.append('generate_summary', 'true');
+  if (opts?.regulationType) formData.append('regulation_type', opts.regulationType);
+  if (opts?.version) formData.append('version', opts.version);
 
   const response = await fetch(`${API_BASE_URL}/documents/upload`, {
     method: 'POST',
@@ -92,6 +106,29 @@ export async function getDocumentList(): Promise<DocListResponse> {
   };
 }
 
+export async function getDocumentStatus(docId: string): Promise<DocUploadResponse> {
+  const response = await fetch(`${API_BASE_URL}/documents/status/${docId}`);
+  if (!response.ok) {
+    throw new Error(`Status check failed: ${response.status}`);
+  }
+  return response.json() as Promise<DocUploadResponse>;
+}
+
+export async function deleteDocument(docId: string): Promise<void> {
+  const response = await fetch(`${API_BASE_URL}/documents/${docId}`, { method: 'DELETE' });
+  if (!response.ok) {
+    throw new Error(`Delete failed: ${response.status}`);
+  }
+}
+
+export async function retryDocument(docId: string): Promise<DocUploadResponse> {
+  const response = await fetch(`${API_BASE_URL}/documents/${docId}/retry`, { method: 'POST' });
+  if (!response.ok) {
+    throw new Error(`Retry failed: ${response.status}`);
+  }
+  return response.json() as Promise<DocUploadResponse>;
+}
+
 export async function searchRegulations(query: string, topK: number = 8): Promise<RegulationSearchResponse> {
   const response = await fetch(`${API_BASE_URL}/knowledge/retrieval`, {
     method: 'POST',

frontend/src/api/index.ts

@@ -136,6 +136,9 @@ export interface DocInfo {
   updated_at?: string;
   download_url?: string;
   size_text?: string;
+  summary?: string;
+  regulation_type?: string;
+  version?: string;
 }
 
 export interface DocListResponse {
@@ -149,6 +152,8 @@ export interface DocUploadResponse {
   message?: string;
   num_chunks?: number;
   summary?: string;
+  regulation_type?: string;
+  version?: string;
 }
 
 export interface QuickQuestion {

frontend/src/api/rag.ts

@@ -2,15 +2,21 @@ import type { QuickQuestionsResponse, SSEMessage } from './index';
 
 const AGENT_API_BASE = '/api/v1';
 
-export async function getQuickQuestions(): Promise<QuickQuestionsResponse> {
+const _FALLBACK_QUESTIONS = [
-  return {
-    questions: [
   { id: '1', question: '请总结最新入库法规对电池安全的核心要求', category: '法规解读' },
   { id: '2', question: '我上传的制度文档与新能源法规有哪些潜在冲突？', category: '差距分析' },
   { id: '3', question: '请给出法规依据，并按条款列出整改建议', category: '整改建议' },
   { id: '4', question: '请解释 UN-ECE 与 GB 标准在网络安全方面的差异', category: '标准对比' },
-    ],
+];
-  };
+
+export async function getQuickQuestions(): Promise<QuickQuestionsResponse> {
+  try {
+    const response = await fetch(`${AGENT_API_BASE}/rag/quick-questions`);
+    if (!response.ok) throw new Error(`status ${response.status}`);
+    return response.json() as Promise<QuickQuestionsResponse>;
+  } catch {
+    return { questions: _FALLBACK_QUESTIONS };
+  }
 }
 
 function parseSSEChunk(raw: string, onMessage: (data: SSEMessage) => void) {
@@ -67,7 +73,8 @@ export async function ragChat(
   topK: number = 5,
   onMessage: (data: SSEMessage) => void,
   onError?: (error: Error) => void,
-  onComplete?: () => void
+  onComplete?: () => void,
+  filters?: string
 ): Promise<void> {
   try {
     const response = await fetch(`${AGENT_API_BASE}/agent/chat/stream`, {
@@ -76,7 +83,7 @@ export async function ragChat(
         'Content-Type': 'application/json',
         Accept: 'text/event-stream',
       },
-      body: JSON.stringify({ query, top_k: topK }),
+      body: JSON.stringify({ query, top_k: topK, ...(filters ? { filters } : {}) }),
     });
 
     if (!response.ok || !response.body) {

frontend/src/pages/Compliance/CompliancePage.tsx

@@ -250,11 +250,20 @@ export const CompliancePage: React.FC = () => {
     setChatInput('');
     setChatLoading(true);
 
+    const segmentContext = [
+      `意图：${chunk.intent}`,
+      `内容：${chunk.content.slice(0, 300)}`,
+      chunk.regulations.length > 0
+        ? `相关法规：${chunk.regulations.slice(0, 3).map(r => `${r.name}${r.clause ? ' ' + r.clause : ''}（相关性 ${Math.round(r.score * 100)}%）`).join('；')}`
+        : '',
+    ].filter(Boolean).join('\n');
+
     let currentResponse = '';
 
     complianceChat(
       activeChunkId,
       chatInput,
+      segmentContext,
       (data: unknown) => {
         const sseData = data as { type: string; text?: string };
         if (sseData.type === 'chunk' && sseData.text) {

frontend/src/pages/Docs/DocsPage.tsx

@@ -2,7 +2,7 @@ import React, { useEffect, useRef, useState } from 'react';
 import { useTheme } from '../../contexts';
 import { Content } from '../../components/layout/Content';
 import { TPattern } from '../../components/common/TPattern';
-import { getDocumentList, searchRegulations, uploadDocument, type RegulationSearchItem } from '../../api/docs';
+import { getDocumentList, getDocumentStatus, searchRegulations, uploadDocument, deleteDocument, retryDocument, type RegulationSearchItem } from '../../api/docs';
 import type { Doc } from '../../types';
 
 type PipelineStatus = 'idle' | 'running' | 'completed' | 'error';
@@ -15,13 +15,13 @@ const PIPELINE_STEPS = [
   { name: 'STORE' },
 ];
 
+const REGULATION_TYPES = ['', '国家标准', '行业标准', '地方标准', '企业标准', '法律法规', '监管规定'];
+
 const STEP_DURATION_MS = 700;
 const INITIAL_SEARCH_QUERY = '新能源汽车电池安全要求';
 
 function wait(ms: number) {
-  return new Promise<void>((resolve) => {
+  return new Promise<void>((resolve) => { window.setTimeout(resolve, ms); });
-    window.setTimeout(resolve, ms);
-  });
 }
 
 export const DocsPage: React.FC = () => {
@@ -41,6 +41,13 @@ export const DocsPage: React.FC = () => {
   const [searchLoading, setSearchLoading] = useState(false);
   const [searchError, setSearchError] = useState('');
 
+  // Upload metadata
+  const [regulationType, setRegulationType] = useState('');
+  const [version, setVersion] = useState('');
+
+  // Batch queue: files waiting to be uploaded after the current one finishes
+  const batchQueueRef = useRef<File[]>([]);
+
   async function loadDocuments() {
     setLoading(true);
     try {
@@ -54,6 +61,9 @@ export const DocsPage: React.FC = () => {
         docId: doc.id,
         downloadUrl: doc.download_url,
         updatedAt: doc.updated_at,
+        summary: doc.summary,
+        regulationType: doc.regulation_type,
+        version: doc.version,
       }));
       setDocs(apiDocs);
     } catch (error) {
@@ -81,62 +91,71 @@ export const DocsPage: React.FC = () => {
   }
 
   useEffect(() => {
-    const timerId = window.setTimeout(() => {
+    const timerId = window.setTimeout(() => { void loadDocuments(); }, 0);
-      void loadDocuments();
-    }, 0);
     return () => window.clearTimeout(timerId);
   }, []);
 
   useEffect(() => {
-    const timerId = window.setTimeout(() => {
+    const timerId = window.setTimeout(() => { void runSearch(INITIAL_SEARCH_QUERY); }, 0);
-      void runSearch(INITIAL_SEARCH_QUERY);
-    }, 0);
     return () => window.clearTimeout(timerId);
   }, []);
 
   useEffect(() => {
-    return () => {
+    return () => { pipelineRunIdRef.current += 1; };
-      pipelineRunIdRef.current += 1;
-    };
   }, []);
 
+  useEffect(() => {
+    const parsingDocs = docs.filter(
+      (doc) => doc.status === 'parsing' && doc.docId && !doc.docId.startsWith('pending-')
+    );
+    if (parsingDocs.length === 0) return;
+
+    const timerId = window.setInterval(() => {
+      parsingDocs.forEach((doc) => {
+        void getDocumentStatus(doc.docId!).then((res) => {
+          if (res.status === 'indexed' || res.status === 'failed') {
+            setDocs((prev) =>
+              prev.map((d) =>
+                d.docId === doc.docId
+                  ? {
+                      ...d,
+                      status: res.status === 'indexed' ? 'indexed' : 'failed',
+                      chunks: res.num_chunks ?? d.chunks,
+                      summary: res.summary ?? d.summary,
+                      regulationType: res.regulation_type ?? d.regulationType,
+                      version: res.version ?? d.version,
+                    }
+                  : d
+              )
+            );
+          }
+        }).catch(() => {});
+      });
+    }, 5000);
+
+    return () => window.clearInterval(timerId);
+  }, [docs]);
+
   const runPipelineFlow = async (runId: number, uploadPromise: Promise<Awaited<ReturnType<typeof uploadDocument>>>) => {
-    const guardedSetActiveStep = (step: number) => {
+    const guard = (fn: () => void) => { if (pipelineRunIdRef.current !== runId) return false; fn(); return true; };
-      if (pipelineRunIdRef.current !== runId) return false;
-      setActiveStep(step);
-      return true;
-    };
 
-    const guardedCompleteStep = (step: number) => {
+    for (let i = 0; i < PIPELINE_STEPS.length - 1; i++) {
-      if (pipelineRunIdRef.current !== runId) return false;
+      if (!guard(() => setActiveStep(i))) return;
-      setCompletedSteps((prev) => (prev.includes(step) ? prev : [...prev, step]));
-      return true;
-    };
-
-    for (let index = 0; index < PIPELINE_STEPS.length - 1; index += 1) {
-      if (!guardedSetActiveStep(index)) return;
       await wait(STEP_DURATION_MS);
-      if (!guardedCompleteStep(index)) return;
+      if (!guard(() => setCompletedSteps((p) => p.includes(i) ? p : [...p, i]))) return;
     }
 
-    if (!guardedSetActiveStep(PIPELINE_STEPS.length - 1)) return;
+    if (!guard(() => setActiveStep(PIPELINE_STEPS.length - 1))) return;
     await uploadPromise;
-    if (!guardedCompleteStep(PIPELINE_STEPS.length - 1)) return;
+    if (!guard(() => setCompletedSteps((p) => { const last = PIPELINE_STEPS.length - 1; return p.includes(last) ? p : [...p, last]; }))) return;
 
     await wait(240);
     if (pipelineRunIdRef.current !== runId) return;
-
     setActiveStep(-1);
     setPipelineStatus('completed');
   };
 
-  const handleFileSelect = async (event: React.ChangeEvent<HTMLInputElement>) => {
+  const uploadSingleFile = async (file: File, runId: number) => {
-    const file = event.target.files?.[0];
-    if (!file || uploading) return;
-
-    const runId = pipelineRunIdRef.current + 1;
-    pipelineRunIdRef.current = runId;
-
     setUploading(true);
     setUploadFileName(file.name);
     setActiveStep(-1);
@@ -152,11 +171,16 @@ export const DocsPage: React.FC = () => {
       size: `${fileSizeMB}MB`,
       status: 'parsing',
       docId: tempDocId,
+      regulationType: regulationType || undefined,
+      version: version || undefined,
     };
 
     setDocs((prev) => [newDoc, ...prev]);
 
-    const uploadPromise = uploadDocument(file);
+    const uploadPromise = uploadDocument(file, {
+      regulationType: regulationType || undefined,
+      version: version || undefined,
+    });
     void runPipelineFlow(runId, uploadPromise);
 
     try {
@@ -166,143 +190,123 @@ export const DocsPage: React.FC = () => {
       setDocs((prev) =>
         prev.map((doc) =>
           doc.id === newDoc.id
-            ? {
+            ? { ...doc, status: 'indexed', docId: uploadRes.doc_id, chunks: uploadRes.num_chunks || doc.chunks, summary: uploadRes.summary }
-                ...doc,
-                status: 'indexed',
-                docId: uploadRes.doc_id,
-                chunks: uploadRes.num_chunks || doc.chunks,
-                summary: uploadRes.summary,
-              }
             : doc
         )
       );
-
-      setUploading(false);
-      setUploadFileName('');
       void loadDocuments();
     } catch (error) {
       console.error('Upload failed:', error);
       if (pipelineRunIdRef.current !== runId) return;
-
-      setUploading(false);
-      setUploadFileName('');
       setDocs((prev) => prev.filter((doc) => doc.id !== newDoc.id));
       setPipelineStatus('error');
       setActiveStep(-1);
       setCompletedSteps([]);
     } finally {
-      if (fileInputRef.current) {
+      setUploading(false);
-        fileInputRef.current.value = '';
+      setUploadFileName('');
+      if (fileInputRef.current) fileInputRef.current.value = '';
+
+      // Process next file in batch queue
+      const next = batchQueueRef.current.shift();
+      if (next) {
+        const nextRunId = pipelineRunIdRef.current + 1;
+        pipelineRunIdRef.current = nextRunId;
+        void uploadSingleFile(next, nextRunId);
       }
     }
   };
 
-  const triggerFileUpload = () => {
+  const handleFileSelect = async (event: React.ChangeEvent<HTMLInputElement>) => {
-    if (uploading) return;
+    const files = Array.from(event.target.files ?? []);
-    fileInputRef.current?.click();
+    if (files.length === 0 || uploading) return;
+
+    const [first, ...rest] = files;
+    batchQueueRef.current = rest;
+
+    const runId = pipelineRunIdRef.current + 1;
+    pipelineRunIdRef.current = runId;
+    await uploadSingleFile(first, runId);
   };
 
-  const handleDragOver = (event: React.DragEvent) => {
+  const handleDelete = async (docId: string) => {
-    event.preventDefault();
+    try {
-    event.stopPropagation();
+      await deleteDocument(docId);
+      setDocs((prev) => prev.filter((doc) => doc.docId !== docId));
+    } catch (error) {
+      console.error('Delete failed:', error);
+    }
   };
 
+  const handleRetry = async (docId: string) => {
+    setDocs((prev) => prev.map((doc) => doc.docId === docId ? { ...doc, status: 'parsing' } : doc));
+    try {
+      const result = await retryDocument(docId);
+      setDocs((prev) =>
+        prev.map((doc) => doc.docId === docId ? { ...doc, status: 'indexed', chunks: result.num_chunks || doc.chunks } : doc)
+      );
+    } catch (error) {
+      console.error('Retry failed:', error);
+      setDocs((prev) => prev.map((doc) => doc.docId === docId ? { ...doc, status: 'failed' } : doc));
+    }
+  };
+
+  const triggerFileUpload = () => { if (uploading) return; fileInputRef.current?.click(); };
+
+  const handleDragOver = (event: React.DragEvent) => { event.preventDefault(); event.stopPropagation(); };
+
   const handleDrop = (event: React.DragEvent) => {
     event.preventDefault();
     event.stopPropagation();
-
+    const files = Array.from(event.dataTransfer.files);
-    const files = event.dataTransfer.files;
     if (files.length === 0 || uploading) return;
 
-    const droppedFile = files[0];
+    const [first, ...rest] = files;
-    if (fileInputRef.current) {
+    batchQueueRef.current = rest;
-      const dataTransfer = new DataTransfer();
+    const runId = pipelineRunIdRef.current + 1;
-      dataTransfer.items.add(droppedFile);
+    pipelineRunIdRef.current = runId;
-      fileInputRef.current.files = dataTransfer.files;
+    void uploadSingleFile(first, runId);
-    }
-
-    void handleFileSelect({
-      target: { files: [droppedFile] as unknown as FileList },
-    } as React.ChangeEvent<HTMLInputElement>);
   };
 
   const getStepStyle = (index: number) => {
-    const isActive = activeStep === index;
+    if (activeStep === index) return { background: theme.bgCard, border: `2px solid ${theme.accent}`, boxShadow: `0 0 12px ${theme.accent}40` };
-    const isCompleted = completedSteps.includes(index);
+    if (completedSteps.includes(index)) return { background: theme.bgCard, border: `1px solid ${theme.green}` };
-
+    return { background: theme.bgCard, border: `1px solid ${theme.border}` };
-    if (isActive) {
-      return {
-        background: theme.bgCard,
-        border: `2px solid ${theme.accent}`,
-        boxShadow: `0 0 12px ${theme.accent}40`,
-      };
-    }
-
-    if (isCompleted) {
-      return {
-        background: theme.bgCard,
-        border: `1px solid ${theme.green}`,
-      };
-    }
-
-    return {
-      background: theme.bgCard,
-      border: `1px solid ${theme.border}`,
-    };
   };
 
   const getCheckStyle = (index: number) => {
-    const isActive = activeStep === index;
+    if (activeStep === index) return { background: theme.gradientAccent, color: '#fff', animation: 'pulse 0.6s infinite' };
-    const isCompleted = completedSteps.includes(index);
+    if (completedSteps.includes(index)) return { background: theme.green, color: '#fff' };
-
+    return { background: theme.bgHover, color: theme.text3 };
-    if (isActive) {
-      return {
-        background: theme.gradientAccent,
-        color: '#fff',
-        animation: 'pulse 0.6s infinite',
-      };
-    }
-
-    if (isCompleted) {
-      return {
-        background: theme.green,
-        color: '#fff',
-      };
-    }
-
-    return {
-      background: theme.bgHover,
-      color: theme.text3,
-    };
   };
 
   const getPipelineHint = () => {
     if (pipelineStatus === 'running') {
-      return activeStep >= 0 ? `${PIPELINE_STEPS[activeStep].name} · ${uploadFileName}` : `LOAD · ${uploadFileName}`;
+      const queueLen = batchQueueRef.current.length;
-    }
+      const suffix = queueLen > 0 ? ` (+${queueLen} 待上传)` : '';
-    if (pipelineStatus === 'completed') {
+      return `${activeStep >= 0 ? PIPELINE_STEPS[activeStep].name : 'LOAD'} · ${uploadFileName}${suffix}`;
-      return 'PIPELINE COMPLETE';
-    }
-    if (pipelineStatus === 'error') {
-      return 'PIPELINE FAILED';
     }
+    if (pipelineStatus === 'completed') return 'PIPELINE COMPLETE';
+    if (pipelineStatus === 'error') return 'PIPELINE FAILED';
     return 'WAITING FOR UPLOAD';
   };
 
+  const inputStyle: React.CSSProperties = {
+    padding: '8px 12px',
+    fontSize: 13,
+    background: theme.bgCard,
+    border: `1px solid ${theme.border}`,
+    borderRadius: 8,
+    color: theme.text,
+    outline: 'none',
+  };
+
   return (
     <Content>
       <TPattern />
 
       <section style={{ marginBottom: 56 }}>
-        <h2
+        <h2 style={{ fontSize: 14, fontWeight: 600, color: theme.accent, marginBottom: 20, letterSpacing: '1px' }}>
-          style={{
-            fontSize: 14,
-            fontWeight: 600,
-            color: theme.accent,
-            marginBottom: 20,
-            letterSpacing: '1px',
-          }}
-        >
           UPLOAD
         </h2>
 
@@ -310,10 +314,30 @@ export const DocsPage: React.FC = () => {
           ref={fileInputRef}
           type="file"
           accept=".pdf,.docx,.doc"
+          multiple
           onChange={handleFileSelect}
           style={{ display: 'none' }}
         />
 
+        {/* Metadata row */}
+        <div style={{ display: 'flex', gap: 12, marginBottom: 12 }}>
+          <select
+            value={regulationType}
+            onChange={(e) => setRegulationType(e.target.value)}
+            style={{ ...inputStyle, flex: 1 }}
+          >
+            {REGULATION_TYPES.map((t) => (
+              <option key={t} value={t}>{t || '法规类型（可选）'}</option>
+            ))}
+          </select>
+          <input
+            value={version}
+            onChange={(e) => setVersion(e.target.value)}
+            placeholder="版本号（可选，如 2024）"
+            style={{ ...inputStyle, flex: 1 }}
+          />
+        </div>
+
         <div
           onClick={triggerFileUpload}
           onDragOver={handleDragOver}
@@ -330,30 +354,11 @@ export const DocsPage: React.FC = () => {
             opacity: uploading ? 0.78 : 1,
           }}
         >
-          <div
+          <div style={{ width: 80, height: 80, borderRadius: 20, background: theme.bgHover, display: 'flex', alignItems: 'center', justifyContent: 'center', margin: '0 auto 20px' }}>
-            style={{
-              width: 80,
-              height: 80,
-              borderRadius: 20,
-              background: theme.bgHover,
-              display: 'flex',
-              alignItems: 'center',
-              justifyContent: 'center',
-              margin: '0 auto 20px',
-            }}
-          >
             {uploading ? (
               <div style={{ animation: 'spin 1s linear infinite' }}>
                 <svg width="36" height="36" viewBox="0 0 24 24" fill="none">
-                  <circle
+                  <circle cx="12" cy="12" r="10" stroke={theme.accent} strokeWidth="2" strokeDasharray="60" strokeDashoffset="20" />
-                    cx="12"
-                    cy="12"
-                    r="10"
-                    stroke={theme.accent}
-                    strokeWidth="2"
-                    strokeDasharray="60"
-                    strokeDashoffset="20"
-                  />
                 </svg>
               </div>
             ) : (
@@ -363,26 +368,17 @@ export const DocsPage: React.FC = () => {
               </svg>
             )}
           </div>
-
           <div style={{ fontSize: 16, fontWeight: 500, marginBottom: 8 }}>
-            {uploading ? '正在上传并启动处理链路...' : '拖拽文件或点击上传'}
+            {uploading ? '正在上传并启动处理链路...' : '拖拽文件或点击上传（支持多选）'}
           </div>
           <div className="mono" style={{ fontSize: 12, color: theme.text3 }}>
-            {uploading ? uploadFileName : 'PDF · DOCX · DOC · MAX 100MB'}
+            {uploading ? uploadFileName : 'PDF · DOCX · DOC · MAX 100MB · 支持批量'}
           </div>
         </div>
       </section>
 
       <section style={{ marginBottom: 40 }}>
-        <h2
+        <h2 style={{ fontSize: 14, fontWeight: 600, color: theme.accent, marginBottom: 20, letterSpacing: '1px' }}>
-          style={{
-            fontSize: 14,
-            fontWeight: 600,
-            color: theme.accent,
-            marginBottom: 20,
-            letterSpacing: '1px',
-          }}
-        >
           PROCESSING PIPELINE
         </h2>
 
@@ -390,12 +386,7 @@ export const DocsPage: React.FC = () => {
           className="mono"
           style={{
             fontSize: 11,
-            color:
+            color: pipelineStatus === 'error' ? '#d64545' : pipelineStatus === 'completed' ? theme.green : theme.text3,
-              pipelineStatus === 'error'
-                ? '#d64545'
-                : pipelineStatus === 'completed'
-                  ? theme.green
-                  : theme.text3,
             letterSpacing: '1px',
             marginBottom: 12,
           }}
@@ -405,63 +396,24 @@ export const DocsPage: React.FC = () => {
 
         <div style={{ display: 'flex', gap: 16 }}>
           {PIPELINE_STEPS.map((step, index) => {
-            const stepStyle = getStepStyle(index);
-            const checkStyle = getCheckStyle(index);
-            const arrowActive = activeStep > index || completedSteps.includes(index);
             const isCompleted = completedSteps.includes(index);
             const isActive = activeStep === index;
+            const arrowActive = activeStep > index || isCompleted;
 
             return (
               <div
                 key={step.name}
-                style={{
+                style={{ flex: 1, padding: 20, textAlign: 'center', borderRadius: 12, position: 'relative', boxShadow: !isDark ? '0 2px 8px rgba(226,0,116,0.04)' : 'none', transition: 'all 0.3s ease', ...getStepStyle(index) }}
-                  flex: 1,
-                  padding: 20,
-                  textAlign: 'center',
-                  borderRadius: 12,
-                  position: 'relative',
-                  boxShadow: !isDark ? '0 2px 8px rgba(226,0,116,0.04)' : 'none',
-                  transition: 'all 0.3s ease',
-                  ...stepStyle,
-                }}
-              >
-                <div
-                  style={{
-                    width: 36,
-                    height: 36,
-                    borderRadius: 8,
-                    display: 'flex',
-                    alignItems: 'center',
-                    justifyContent: 'center',
-                    margin: '0 auto 12px',
-                    fontSize: 16,
-                    transition: 'all 0.3s ease',
-                    ...checkStyle,
-                  }}
               >
+                <div style={{ width: 36, height: 36, borderRadius: 8, display: 'flex', alignItems: 'center', justifyContent: 'center', margin: '0 auto 12px', fontSize: 16, transition: 'all 0.3s ease', ...getCheckStyle(index) }}>
                   {isActive ? step.name : isCompleted ? '✓' : step.name}
                 </div>
-
+                <div className="mono" style={{ fontSize: 12, fontWeight: 600 }}>{step.name}</div>
-                <div className="mono" style={{ fontSize: 12, fontWeight: 600 }}>
-                  {step.name}
-                </div>
                 <div className="mono" style={{ fontSize: 10, color: theme.text3, marginTop: 8 }}>
                   {isCompleted ? 'DONE' : isActive ? 'RUNNING' : 'PENDING'}
                 </div>
-
                 {index < PIPELINE_STEPS.length - 1 && (
-                  <div
+                  <div style={{ position: 'absolute', right: -8, top: '50%', transform: 'translateY(-50%)', color: arrowActive ? theme.green : theme.borderLight, fontWeight: arrowActive ? 700 : 400, opacity: arrowActive ? 1 : 0.45, transition: 'all 0.3s ease' }}>
-                    style={{
-                      position: 'absolute',
-                      right: -8,
-                      top: '50%',
-                      transform: 'translateY(-50%)',
-                      color: arrowActive ? theme.green : theme.borderLight,
-                      fontWeight: arrowActive ? 700 : 400,
-                      opacity: arrowActive ? 1 : 0.45,
-                      transition: 'all 0.3s ease',
-                    }}
-                  >
                     →
                   </div>
                 )}
@@ -473,15 +425,7 @@ export const DocsPage: React.FC = () => {
 
       <section style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: 24, marginBottom: 56 }}>
         <div>
-          <h2
+          <h2 style={{ fontSize: 14, fontWeight: 600, color: theme.accent, marginBottom: 20, letterSpacing: '1px' }}>
-            style={{
-              fontSize: 14,
-              fontWeight: 600,
-              color: theme.accent,
-              marginBottom: 20,
-              letterSpacing: '1px',
-            }}
-          >
             文档管理清单 ({loading ? '...' : docs.length})
           </h2>
 
@@ -489,36 +433,12 @@ export const DocsPage: React.FC = () => {
             {docs.map((doc) => (
               <div
                 key={doc.id}
-                style={{
+                style={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', padding: 20, background: theme.bgCard, borderRadius: 12, border: `1px solid ${doc.status === 'parsing' ? theme.accent : theme.border}`, transition: 'all 0.2s ease', boxShadow: !isDark ? '0 2px 8px rgba(226,0,116,0.04)' : 'none' }}
-                  display: 'flex',
-                  alignItems: 'center',
-                  justifyContent: 'space-between',
-                  padding: 20,
-                  background: theme.bgCard,
-                  borderRadius: 12,
-                  border: `1px solid ${doc.status === 'parsing' ? theme.accent : theme.border}`,
-                  transition: 'all 0.2s ease',
-                  boxShadow: !isDark ? '0 2px 8px rgba(226,0,116,0.04)' : 'none',
-                }}
-              >
-                <div style={{ display: 'flex', alignItems: 'center', gap: 16 }}>
-                  <div
-                    style={{
-                      width: 44,
-                      height: 44,
-                      borderRadius: 10,
-                      background: theme.bgHover,
-                      display: 'flex',
-                      alignItems: 'center',
-                      justifyContent: 'center',
-                    }}
               >
+                <div style={{ display: 'flex', alignItems: 'flex-start', gap: 16 }}>
+                  <div style={{ width: 44, height: 44, borderRadius: 10, background: theme.bgHover, display: 'flex', alignItems: 'center', justifyContent: 'center', flexShrink: 0 }}>
                     <svg width="20" height="20" viewBox="0 0 24 24" fill="none">
-                      <path
+                      <path d="M14 2H6C5 2 4 3 4 4V20C4 21 5 22 6 22H18C19 22 20 21 20 20V8L14 2Z" stroke={theme.accent} strokeWidth="1.5" />
-                        d="M14 2H6C5 2 4 3 4 4V20C4 21 5 22 6 22H18C19 22 20 21 20 20V8L14 2Z"
-                        stroke={theme.accent}
-                        strokeWidth="1.5"
-                      />
                       <path d="M14 2V8H20" stroke={theme.accent} strokeWidth="1.5" />
                     </svg>
                   </div>
@@ -529,36 +449,48 @@ export const DocsPage: React.FC = () => {
                       {doc.updatedAt ? new Date(doc.updatedAt).toLocaleString() : doc.size}
                       {doc.docId ? ` · ${doc.docId}` : ''}
                     </div>
+                    {/* Tags row */}
+                    {(doc.regulationType || doc.version) && (
+                      <div style={{ display: 'flex', gap: 6, marginTop: 5, flexWrap: 'wrap' }}>
+                        {doc.regulationType && (
+                          <span style={{ fontSize: 11, padding: '2px 8px', borderRadius: 4, background: `${theme.accent}18`, color: theme.accent, fontWeight: 500 }}>
+                            {doc.regulationType}
+                          </span>
+                        )}
+                        {doc.version && (
+                          <span style={{ fontSize: 11, padding: '2px 8px', borderRadius: 4, background: theme.bgHover, color: theme.text2 }}>
+                            v{doc.version}
+                          </span>
+                        )}
+                      </div>
+                    )}
+                    {doc.summary && (
+                      <div style={{ fontSize: 12, color: theme.text2, marginTop: 6, lineHeight: 1.5, maxWidth: 320, display: '-webkit-box', WebkitLineClamp: 2, WebkitBoxOrient: 'vertical', overflow: 'hidden' }}>
+                        {doc.summary}
+                      </div>
+                    )}
                   </div>
                 </div>
 
-                <div style={{ display: 'flex', alignItems: 'center', gap: 20 }}>
+                <div style={{ display: 'flex', alignItems: 'flex-start', gap: 12, flexShrink: 0 }}>
-                  {doc.downloadUrl && (
+                  {doc.status === 'failed' && doc.docId && !doc.docId.startsWith('pending-') && (
-                    <a
+                    <button onClick={() => void handleRetry(doc.docId!)} style={{ fontSize: 12, padding: '6px 12px', background: 'transparent', border: `1px solid ${theme.accent}`, borderRadius: 6, color: theme.accent, cursor: 'pointer' }}>
-                      href={doc.downloadUrl}
+                      重试
-                      target="_blank"
+                    </button>
-                      rel="noreferrer"
+                  )}
-                      style={{ fontSize: 12, color: theme.accent, textDecoration: 'none' }}
+                  {doc.downloadUrl && doc.status === 'indexed' && (
-                    >
+                    <a href={doc.downloadUrl} target="_blank" rel="noreferrer" style={{ fontSize: 12, color: theme.accent, textDecoration: 'none' }}>
                       下载
                     </a>
                   )}
-                  <div
+                  <div className="mono" style={{ fontSize: 12, padding: '6px 12px', background: theme.bgHover, borderRadius: 6, color: doc.status === 'failed' ? '#d64545' : theme.text2 }}>
-                    className="mono"
+                    {doc.status === 'parsing' ? '处理中...' : doc.status === 'failed' ? '处理失败' : `${doc.chunks} chunks`}
-                    style={{
-                      fontSize: 12,
-                      padding: '6px 12px',
-                      background: theme.bgHover,
-                      borderRadius: 6,
-                      color: doc.status === 'failed' ? '#d64545' : theme.text2,
-                    }}
-                  >
-                    {doc.status === 'parsing'
-                      ? '处理中...'
-                      : doc.status === 'failed'
-                        ? '处理失败'
-                        : `${doc.chunks} chunks`}
                   </div>
+                  {doc.docId && !doc.docId.startsWith('pending-') && (
+                    <button onClick={() => void handleDelete(doc.docId!)} style={{ fontSize: 12, padding: '6px 10px', background: 'transparent', border: `1px solid ${theme.border}`, borderRadius: 6, color: theme.text3, cursor: 'pointer' }}>
+                      删除
+                    </button>
+                  )}
                 </div>
               </div>
             ))}
@@ -566,15 +498,7 @@ export const DocsPage: React.FC = () => {
         </div>
 
         <div>
-          <h2
+          <h2 style={{ fontSize: 14, fontWeight: 600, color: theme.accent, marginBottom: 20, letterSpacing: '1px' }}>
-            style={{
-              fontSize: 14,
-              fontWeight: 600,
-              color: theme.accent,
-              marginBottom: 20,
-              letterSpacing: '1px',
-            }}
-          >
             文档管理内法规检索
           </h2>
 
@@ -582,86 +506,37 @@ export const DocsPage: React.FC = () => {
             <input
               value={searchQuery}
               onChange={(event) => setSearchQuery(event.target.value)}
-              onKeyDown={(event) => {
+              onKeyDown={(event) => { if (event.key === 'Enter') void runSearch(searchQuery); }}
-                if (event.key === 'Enter') {
-                  void runSearch(searchQuery);
-                }
-              }}
               placeholder="输入法规关键词、条款或制度主题"
-              style={{
+              style={{ flex: 1, padding: 12, fontSize: 14, background: theme.bgCard, border: `1px solid ${theme.border}`, borderRadius: 8, color: theme.text, outline: 'none' }}
-                flex: 1,
-                padding: 12,
-                fontSize: 14,
-                background: theme.bgCard,
-                border: `1px solid ${theme.border}`,
-                borderRadius: 8,
-                color: theme.text,
-                outline: 'none',
-              }}
             />
             <button
               onClick={() => void runSearch(searchQuery)}
               disabled={searchLoading || !searchQuery.trim()}
-              style={{
+              style={{ padding: '12px 18px', fontSize: 13, fontWeight: 600, background: searchLoading || !searchQuery.trim() ? theme.bgHover : theme.gradientAccent, color: searchLoading || !searchQuery.trim() ? theme.text3 : '#fff', border: 'none', borderRadius: 8, cursor: searchLoading || !searchQuery.trim() ? 'not-allowed' : 'pointer' }}
-                padding: '12px 18px',
-                fontSize: 13,
-                fontWeight: 600,
-                background: searchLoading || !searchQuery.trim() ? theme.bgHover : theme.gradientAccent,
-                color: searchLoading || !searchQuery.trim() ? theme.text3 : '#fff',
-                border: 'none',
-                borderRadius: 8,
-                cursor: searchLoading || !searchQuery.trim() ? 'not-allowed' : 'pointer',
-              }}
             >
               检索
             </button>
           </div>
 
-          {searchError && (
+          {searchError && <div style={{ marginBottom: 12, fontSize: 13, color: '#d64545' }}>{searchError}</div>}
-            <div style={{ marginBottom: 12, fontSize: 13, color: '#d64545' }}>
-              {searchError}
-            </div>
-          )}
 
           <div style={{ display: 'flex', flexDirection: 'column', gap: 12 }}>
             {searchResults.map((item) => (
-              <div
+              <div key={`${item.id}-${item.file}`} style={{ padding: 18, background: theme.bgCard, borderRadius: 12, border: `1px solid ${theme.border}`, boxShadow: !isDark ? '0 2px 8px rgba(226,0,116,0.04)' : 'none' }}>
-                key={`${item.id}-${item.file}`}
-                style={{
-                  padding: 18,
-                  background: theme.bgCard,
-                  borderRadius: 12,
-                  border: `1px solid ${theme.border}`,
-                  boxShadow: !isDark ? '0 2px 8px rgba(226,0,116,0.04)' : 'none',
-                }}
-              >
                 <div style={{ display: 'flex', justifyContent: 'space-between', gap: 12, marginBottom: 6 }}>
                   <div style={{ fontSize: 14, fontWeight: 600, color: theme.text }}>{item.file}</div>
-                  <div className="mono" style={{ fontSize: 11, color: theme.accent }}>
+                  <div className="mono" style={{ fontSize: 11, color: theme.accent }}>{(item.score * 100).toFixed(1)}%</div>
-                    {(item.score * 100).toFixed(1)}%
                 </div>
-                </div>
-
                 <div className="mono" style={{ fontSize: 11, color: theme.text3, marginBottom: 8 }}>
-                  {item.clause}
+                  {item.clause}{item.tags.length > 0 ? ` · ${item.tags.join(' · ')}` : ''}
-                  {item.tags.length > 0 ? ` · ${item.tags.join(' · ')}` : ''}
                 </div>
-
                 <div style={{ fontSize: 12, color: theme.text2, lineHeight: 1.6 }}>{item.content}</div>
               </div>
             ))}
 
             {!searchLoading && searchResults.length === 0 && (
-              <div
+              <div style={{ padding: 24, borderRadius: 12, background: theme.bgCard, border: `1px solid ${theme.border}`, textAlign: 'center', color: theme.text3 }}>
-                style={{
-                  padding: 24,
-                  borderRadius: 12,
-                  background: theme.bgCard,
-                  border: `1px solid ${theme.border}`,
-                  textAlign: 'center',
-                  color: theme.text3,
-                }}
-              >
                 暂无检索结果
               </div>
             )}

frontend/src/pages/RagChat/CitedAnswer.tsx

@@ -0,0 +1,58 @@
+import React, { useRef } from 'react';
+import { useTheme } from '../../contexts';
+import type { RetrievalData } from '../../types';
+
+interface CitedAnswerProps {
+  text: string;
+  sources: RetrievalData[];
+  onCiteClick: (index: number) => void;
+}
+
+export const CitedAnswer: React.FC<CitedAnswerProps> = ({ text, sources, onCiteClick }) => {
+  const { theme } = useTheme();
+
+  if (!text) return null;
+
+  // Split on [N] patterns, preserving delimiters
+  const parts = text.split(/(\[\d+\])/g);
+
+  return (
+    <span style={{ whiteSpace: 'pre-wrap', lineHeight: 1.6 }}>
+      {parts.map((part, i) => {
+        const match = part.match(/^\[(\d+)\]$/);
+        if (!match) return <React.Fragment key={i}>{part}</React.Fragment>;
+
+        const idx = parseInt(match[1], 10);
+        const source = sources[idx - 1];
+
+        return (
+          <sup
+            key={i}
+            title={source ? `${source.file} · ${source.clause}` : `引用 ${idx}`}
+            onClick={() => onCiteClick(idx)}
+            style={{
+              display: 'inline-flex',
+              alignItems: 'center',
+              justifyContent: 'center',
+              minWidth: 18,
+              height: 18,
+              padding: '0 4px',
+              marginLeft: 1,
+              fontSize: 10,
+              fontWeight: 700,
+              background: theme.gradientAccent,
+              color: '#fff',
+              borderRadius: 4,
+              cursor: source ? 'pointer' : 'default',
+              verticalAlign: 'super',
+              lineHeight: 1,
+              userSelect: 'none',
+            }}
+          >
+            {idx}
+          </sup>
+        );
+      })}
+    </span>
+  );
+};

frontend/src/pages/RagChat/RagChatPage.tsx

@@ -2,6 +2,7 @@ import React, { useEffect, useRef, useState } from 'react';
 import { useTheme } from '../../contexts';
 import type { ChatMessage, RetrievalData } from '../../types';
 import { getQuickQuestions, ragChat } from '../../api/rag';
+import { CitedAnswer } from './CitedAnswer';
 
 const ragQuickQuestionsDefault = [
   '电动自行车上路需要什么条件？',
@@ -24,6 +25,8 @@ export const RagChatPage: React.FC = () => {
   const [showClearConfirm, setShowClearConfirm] = useState<boolean>(false);
   const [selectedRetrieval, setSelectedRetrieval] = useState<RetrievalData | null>(null);
   const [quickQuestions, setQuickQuestions] = useState<string[]>(ragQuickQuestionsDefault);
+  const [filterRegulationType, setFilterRegulationType] = useState<string>('');
+  const [highlightedSourceIdx, setHighlightedSourceIdx] = useState<number | null>(null);
 
   function nextMessageId() {
     const currentId = nextMessageIdRef.current;
@@ -55,8 +58,10 @@ export const RagChatPage: React.FC = () => {
     setInput('');
     setLoading(true);
     setRetrievals([]);
+    setHighlightedSourceIdx(null);
 
     let currentResponse = '';
+    const activeFilters = filterRegulationType.trim() || undefined;
 
     void ragChat(
       text,
@@ -112,7 +117,8 @@ export const RagChatPage: React.FC = () => {
       },
       () => {
         setLoading(false);
-      }
+      },
+      activeFilters
     );
   };
 
@@ -130,8 +136,10 @@ export const RagChatPage: React.FC = () => {
     setLoading(true);
     setMessages((prev) => [...prev.slice(0, -1)]);
     setRetrievals([]);
+    setHighlightedSourceIdx(null);
 
     let currentResponse = '';
+    const activeFilters = filterRegulationType.trim() || undefined;
 
     void ragChat(
       lastUserMsg.content,
@@ -185,7 +193,8 @@ export const RagChatPage: React.FC = () => {
       },
       () => {
         setLoading(false);
-      }
+      },
+      activeFilters
     );
   };
 
@@ -267,7 +276,17 @@ export const RagChatPage: React.FC = () => {
                   whiteSpace: 'pre-wrap',
                   border: msg.role === 'assistant' ? `1px solid ${theme.border}` : 'none',
                 }}>
-                  {msg.content}
+                  {msg.role === 'assistant' ? (
+                    <CitedAnswer
+                      text={msg.content}
+                      sources={retrievals}
+                      onCiteClick={(idx) => {
+                        setHighlightedSourceIdx(idx);
+                        const el = document.getElementById(`source-${idx}`);
+                        if (el) el.scrollIntoView({ behavior: 'smooth', block: 'center' });
+                      }}
+                    />
+                  ) : msg.content}
                   {msg.role === 'assistant' && msg.retrievalIds && msg.retrievalIds.length > 0 && (
                     <div style={{
                       marginTop: 10,
@@ -331,6 +350,31 @@ export const RagChatPage: React.FC = () => {
           background: theme.bg,
           borderTop: `1px solid ${theme.border}`,
         }}>
+          <div style={{
+            display: 'flex',
+            gap: 8,
+            marginBottom: 10,
+            alignItems: 'center',
+          }}>
+            <span className="mono" style={{ fontSize: 11, color: theme.text3, whiteSpace: 'nowrap' }}>法规类型</span>
+            <input
+              value={filterRegulationType}
+              onChange={(e) => setFilterRegulationType(e.target.value)}
+              placeholder="如: GB / UN-ECE / IATF（留空不过滤）"
+              style={{
+                flex: 1,
+                maxWidth: 280,
+                padding: '5px 10px',
+                fontSize: 12,
+                background: theme.bgHover,
+                border: `1px solid ${theme.border}`,
+                borderRadius: 6,
+                color: theme.text,
+                outline: 'none',
+              }}
+            />
+          </div>
+
           <div style={{
             display: 'flex',
             gap: 8,
@@ -468,14 +512,16 @@ export const RagChatPage: React.FC = () => {
               {retrievals.map((r, i) => (
                 <div
                   key={r.id}
+                  id={`source-${i + 1}`}
                   onClick={() => setSelectedRetrieval(r)}
                   style={{
                     padding: 16,
-                    background: theme.bgHover,
+                    background: highlightedSourceIdx === i + 1 ? theme.bgElevated : theme.bgHover,
                     borderRadius: 10,
-                    border: `1px solid ${theme.border}`,
+                    border: `1px solid ${highlightedSourceIdx === i + 1 ? theme.accent : theme.border}`,
                     cursor: 'pointer',
                     position: 'relative',
+                    transition: 'border-color 0.2s, background 0.2s',
                   }}
                 >
                   <div style={{

frontend/src/types/doc.ts

@@ -8,6 +8,8 @@ export interface Doc {
   downloadUrl?: string;
   summary?: string;
   updatedAt?: string;
+  regulationType?: string;
+  version?: string;
 }
 
 export interface SearchResult {

frontend/vite.config.ts

@@ -4,7 +4,7 @@ import react from '@vitejs/plugin-react'
 // https://vite.dev/config/
 export default defineConfig(({ mode }) => {
   const env = loadEnv(mode, process.cwd(), '')
-  const apiHost = env.API_HOST || 'localhost'
+  const apiHost = env.API_HOST || '6.86.80.8'
   const apiPort = env.API_PORT || '8000'
   const proxyTarget = env.VITE_API_PROXY_TARGET || `http://${apiHost}:${apiPort}`