update: uploads

.env.example

@@ -1,6 +1,6 @@
 API_KEY=
 MODEL_NAME=gpt-4.1
-DMXAPI_URL=https://www.dmxapi.cn/v1/responses
+OPENAI_API_URL=https://api.openai.com/v1/responses
 JWT_SECRET_KEY=please_change_me
 JWT_ALGORITHM=HS256
 ACCESS_TOKEN_EXPIRE_MINUTES=720

README.md

@@ -30,6 +30,14 @@
 3. 打开：
    - `http://127.0.0.1:5173`
 
+## 导入中心（队列）说明
+
+- 导入任务使用**持久化队列**：任务与文件项写入数据库（`import_jobs` / `import_job_items`），后端单消费者按创建时间 FIFO 串行执行。
+- 状态枚举：`queued`（排队中）、`running`（执行中）、`success`、`failed`、`cancelled`、`retrying`。
+- 刷新页面后，前端会请求 `GET /api/import/jobs?status=queued,running` 恢复未完成任务并轮询进度；无需依赖本地缓存。
+- 失败项可通过「重试失败项」再次入队（新建任务）；排队中/执行中任务可取消。
+- 上传文件按任务与序号存为唯一路径（`upload_dir/{job_id}/{seq}_{filename}`），避免同名覆盖。
+
 ## 默认登录
 
 - 用户名：`admin`
@@ -38,8 +46,9 @@
 ## 功能清单
 
 - 题目 CRUD、搜索、筛选、批量删除、批量更新
-- AI 智能导入（PDF/Word -> DMXAPI -> 预览 -> 确认保存）
+- AI 智能导入（PDF/Word -> OpenAI兼容接口 -> 预览 -> 确认保存）
 - Excel 批量导入、模板下载、导出 JSON/CSV/Excel
+- **导入中心（持久化队列）**：严格 FIFO 串行执行，任务状态持久化到数据库；刷新页面后自动恢复未完成任务列表；支持取消排队中/执行中任务、对失败项一键重试入队。
 - 分类树管理（章节/知识点）
 - 练习模式（抽题、判题、解析反馈）
 - 仪表盘统计（总量、题型、难度、章节、导入历史）

backend/config.py

@@ -7,7 +7,7 @@ from pydantic_settings import BaseSettings, SettingsConfigDict
 class Settings(BaseSettings):
     api_key: str = ""
     model_name: str = "gpt-4.1"
-    dmxapi_url: str = "https://www.dmxapi.cn/v1/responses"
+    openai_api_url: str = "https://api.openai.com/v1/responses"
     jwt_secret_key: str = "change-me-in-env"
     jwt_algorithm: str = "HS256"
     access_token_expire_minutes: int = 60 * 12

backend/main.py

@@ -1,8 +1,10 @@
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
+import threading
 
-from backend.database import Base, engine
+from backend.database import Base, engine, SessionLocal
 from backend.routers import auth, categories, exports, imports, practice, questions, stats
+from backend.services.import_queue_service import reset_stale_running_jobs, run_worker_loop
 
 app = FastAPI(title="Problem Bank API", version="1.0.0")
 
@@ -16,6 +18,17 @@ app.add_middleware(
 
 Base.metadata.create_all(bind=engine)
 
+
+@app.on_event("startup")
+def startup() -> None:
+    db = SessionLocal()
+    try:
+        reset_stale_running_jobs(db)
+    finally:
+        db.close()
+    thread = threading.Thread(target=run_worker_loop, daemon=True)
+    thread.start()
+
 app.include_router(auth.router, prefix="/api/auth", tags=["auth"])
 app.include_router(questions.router, prefix="/api/questions", tags=["questions"])
 app.include_router(imports.router, prefix="/api/import", tags=["imports"])

backend/models.py

@@ -1,11 +1,29 @@
 from datetime import datetime
 
-from sqlalchemy import DateTime, ForeignKey, Integer, Text
+from sqlalchemy import DateTime, ForeignKey, Integer, String, Text
 from sqlalchemy.orm import Mapped, mapped_column, relationship
 
 from backend.database import Base
 
 
+# 导入任务/文件项统一状态
+JOB_STATUS_QUEUED = "queued"
+JOB_STATUS_RUNNING = "running"
+JOB_STATUS_SUCCESS = "success"
+JOB_STATUS_FAILED = "failed"
+JOB_STATUS_CANCELLED = "cancelled"
+JOB_STATUS_RETRYING = "retrying"
+
+JOB_STATUSES = (
+    JOB_STATUS_QUEUED,
+    JOB_STATUS_RUNNING,
+    JOB_STATUS_SUCCESS,
+    JOB_STATUS_FAILED,
+    JOB_STATUS_CANCELLED,
+    JOB_STATUS_RETRYING,
+)
+
+
 class Question(Base):
     __tablename__ = "questions"
 
@@ -52,3 +70,51 @@ class ImportHistory(Base):
     question_count: Mapped[int] = mapped_column(Integer, default=0)
     status: Mapped[str] = mapped_column(Text, default="success")
     created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+
+
+class ImportJob(Base):
+    """导入任务（持久化队列项）。"""
+
+    __tablename__ = "import_jobs"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, index=True)
+    status: Mapped[str] = mapped_column(String(32), default=JOB_STATUS_QUEUED, index=True)
+    method: Mapped[str] = mapped_column(String(32), nullable=False)
+    total: Mapped[int] = mapped_column(Integer, default=0)
+    processed: Mapped[int] = mapped_column(Integer, default=0)
+    success_count: Mapped[int] = mapped_column(Integer, default=0)
+    failed_count: Mapped[int] = mapped_column(Integer, default=0)
+    current_index: Mapped[int] = mapped_column(Integer, default=0)
+    current_file: Mapped[str] = mapped_column(Text, default="")
+    error: Mapped[str] = mapped_column(Text, default="")
+    attempt: Mapped[int] = mapped_column(Integer, default=1)
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+    started_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True)
+    ended_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True)
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime, default=datetime.utcnow, onupdate=datetime.utcnow
+    )
+
+    items: Mapped[list["ImportJobItem"]] = relationship(
+        "ImportJobItem", back_populates="job", order_by="ImportJobItem.seq", lazy="selectin"
+    )
+
+
+class ImportJobItem(Base):
+    """导入任务内的单个文件项。"""
+
+    __tablename__ = "import_job_items"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, index=True)
+    job_id: Mapped[int] = mapped_column(ForeignKey("import_jobs.id", ondelete="CASCADE"), nullable=False)
+    seq: Mapped[int] = mapped_column(Integer, nullable=False)
+    filename: Mapped[str] = mapped_column(Text, default="")
+    stored_path: Mapped[str] = mapped_column(Text, default="")
+    status: Mapped[str] = mapped_column(String(32), default=JOB_STATUS_QUEUED)
+    attempt: Mapped[int] = mapped_column(Integer, default=1)
+    error: Mapped[str] = mapped_column(Text, default="")
+    question_count: Mapped[int] = mapped_column(Integer, default=0)
+    started_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True)
+    ended_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True)
+
+    job: Mapped["ImportJob"] = relationship("ImportJob", back_populates="items")

backend/repositories/__init__.py

@@ -0,0 +1 @@
+# Repositories for DB access

backend/repositories/import_job_repo.py

@@ -0,0 +1,181 @@
+"""Import job persistence: create, get, list, update, claim for FIFO worker."""
+
+from datetime import datetime
+
+from sqlalchemy.orm import Session
+
+from backend.models import (
+    JOB_STATUS_FAILED,
+    JOB_STATUS_QUEUED,
+    JOB_STATUS_RUNNING,
+    ImportJob,
+    ImportJobItem,
+)
+
+
+def create_job(
+    db: Session,
+    method: str,
+    items: list[dict],
+) -> ImportJob:
+    """Create a new import job with items. items: [{"filename": str, "stored_path": str}, ...]."""
+    job = ImportJob(
+        status=JOB_STATUS_QUEUED,
+        method=method,
+        total=len(items),
+        processed=0,
+        success_count=0,
+        failed_count=0,
+    )
+    db.add(job)
+    db.flush()
+    for seq, it in enumerate(items, start=1):
+        db.add(
+            ImportJobItem(
+                job_id=job.id,
+                seq=seq,
+                filename=it.get("filename", ""),
+                stored_path=it.get("stored_path", ""),
+                status=JOB_STATUS_QUEUED,
+            )
+        )
+    db.commit()
+    db.refresh(job)
+    return job
+
+
+def create_job_empty(db: Session, method: str) -> ImportJob:
+    """Create job with no items; caller then adds items and sets total."""
+    job = ImportJob(
+        status=JOB_STATUS_QUEUED,
+        method=method,
+        total=0,
+        processed=0,
+        success_count=0,
+        failed_count=0,
+    )
+    db.add(job)
+    db.flush()
+    return job
+
+
+def add_job_items(db: Session, job_id: int, items: list[dict]) -> None:
+    """Append items to job and set job.total. items: [{"filename": str, "stored_path": str}, ...]."""
+    job = db.query(ImportJob).filter(ImportJob.id == job_id).first()
+    if not job:
+        return
+    for seq, it in enumerate(items, start=1):
+        db.add(
+            ImportJobItem(
+                job_id=job_id,
+                seq=seq,
+                filename=it.get("filename", ""),
+                stored_path=it.get("stored_path", ""),
+                status=JOB_STATUS_QUEUED,
+            )
+        )
+    job.total = len(items)
+    db.commit()
+
+
+def get_job(db: Session, job_id: int) -> ImportJob | None:
+    """Get job by id with items loaded."""
+    return db.query(ImportJob).filter(ImportJob.id == job_id).first()
+
+
+def list_jobs(
+    db: Session,
+    statuses: list[str] | None = None,
+    limit: int = 50,
+) -> list[ImportJob]:
+    """List jobs, optionally filtered by status(es), newest first."""
+    q = db.query(ImportJob).order_by(ImportJob.created_at.desc())
+    if statuses:
+        q = q.filter(ImportJob.status.in_(statuses))
+    return q.limit(limit).all()
+
+
+def update_job(db: Session, job_id: int, **kwargs) -> ImportJob | None:
+    """Update job fields. Returns updated job or None if not found."""
+    job = db.query(ImportJob).filter(ImportJob.id == job_id).first()
+    if not job:
+        return None
+    for k, v in kwargs.items():
+        if hasattr(job, k):
+            setattr(job, k, v)
+    job.updated_at = datetime.utcnow()
+    db.commit()
+    db.refresh(job)
+    return job
+
+
+def update_job_item(db: Session, item_id: int, **kwargs) -> ImportJobItem | None:
+    """Update a single job item."""
+    item = db.query(ImportJobItem).filter(ImportJobItem.id == item_id).first()
+    if not item:
+        return None
+    for k, v in kwargs.items():
+        if hasattr(item, k):
+            setattr(item, k, v)
+    db.commit()
+    db.refresh(item)
+    return item
+
+
+def claim_oldest_queued(db: Session) -> ImportJob | None:
+    """
+    Claim the oldest queued job by setting status to running.
+    Returns the job if claimed, None if no queued job.
+    Used by single-worker FIFO loop. (SQLite-compatible: no row locking.)
+    """
+    job = (
+        db.query(ImportJob)
+        .filter(ImportJob.status == JOB_STATUS_QUEUED)
+        .order_by(ImportJob.created_at.asc())
+        .first()
+    )
+    if not job:
+        return None
+    job.status = JOB_STATUS_RUNNING
+    job.started_at = datetime.utcnow()
+    job.updated_at = datetime.utcnow()
+    db.commit()
+    db.refresh(job)
+    return job
+
+
+def get_queued_job_for_worker(db: Session) -> ImportJob | None:
+    """
+    Get oldest queued job without locking (SQLite has limited FOR UPDATE support).
+    Caller must then update status to running in same or follow-up transaction.
+    """
+    job = (
+        db.query(ImportJob)
+        .filter(ImportJob.status == JOB_STATUS_QUEUED)
+        .order_by(ImportJob.created_at.asc())
+        .first()
+    )
+    return job
+
+
+def cancel_job(db: Session, job_id: int) -> ImportJob | None:
+    """Set job status to cancelled if it is queued or running."""
+    job = db.query(ImportJob).filter(ImportJob.id == job_id).first()
+    if not job or job.status not in (JOB_STATUS_QUEUED, JOB_STATUS_RUNNING):
+        return None
+    job.status = "cancelled"
+    job.ended_at = datetime.utcnow()
+    job.updated_at = datetime.utcnow()
+    db.commit()
+    db.refresh(job)
+    return job
+
+
+def get_failed_items(db: Session, job_id: int) -> list[ImportJobItem]:
+    """Return items with status failed for retry."""
+    return (
+        db.query(ImportJobItem)
+        .filter(ImportJobItem.job_id == job_id, ImportJobItem.status == JOB_STATUS_FAILED)
+        .order_by(ImportJobItem.seq.asc())
+        .all()
+    )

backend/requirements.txt

@@ -10,3 +10,4 @@ python-multipart
 requests
 openpyxl
 python-dotenv
+pytest

backend/routers/imports.py

@@ -1,25 +1,153 @@
+from datetime import datetime
 from pathlib import Path
-
-from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
+from threading import Lock
+from typing import Literal
+from uuid import uuid4
+from fastapi import APIRouter, BackgroundTasks, Depends, File, Form, HTTPException, Query, UploadFile
 from sqlalchemy.orm import Session
 
 from backend.auth import get_current_user
-from backend.database import get_db
+from backend.database import SessionLocal, get_db
 from backend.models import ImportHistory, Question
-from backend.schemas import ImportHistoryOut, QuestionOut
+from backend.repositories import import_job_repo
+from backend.schemas import ImportHistoryOut, ImportJobOut, QuestionOut
 from backend.services.excel_service import create_template_bytes, parse_excel_file
-from backend.services.file_utils import save_upload
-from backend.services.parser import DMXAPIService, extract_metadata
+from backend.services.file_utils import save_upload, save_upload_for_job
+from backend.services.parser import OpenAICompatibleParserService, extract_metadata
 
 router = APIRouter(dependencies=[Depends(get_current_user)])
 
+BATCH_TASKS: dict[str, dict] = {}
+BATCH_TASKS_LOCK = Lock()
+BatchMethod = Literal["excel", "ai"]
+
+
+
+def _set_task(task_id: str, **fields) -> None:
+    with BATCH_TASKS_LOCK:
+        task = BATCH_TASKS.get(task_id)
+        if not task:
+            return
+        task.update(fields)
+
+
+def _build_ai_rows(path: Path) -> list[dict]:
+    parser = OpenAICompatibleParserService()
+    metadata = extract_metadata(path.name)
+    questions = parser.parse_file(str(path))
+    rows = []
+    for q in questions:
+        rows.append(
+            {
+                "chapter": metadata["chapter"],
+                "primary_knowledge": "",
+                "secondary_knowledge": metadata["secondary_knowledge"],
+                "question_type": metadata["question_type"],
+                "difficulty": metadata["difficulty"],
+                "stem": q.get("题干", ""),
+                "option_a": q.get("选项A", ""),
+                "option_b": q.get("选项B", ""),
+                "option_c": q.get("选项C", ""),
+                "option_d": q.get("选项D", ""),
+                "answer": q.get("正确答案", ""),
+                "explanation": q.get("解析", ""),
+                "notes": q.get("备注", ""),
+                "source_file": metadata["source_file"],
+            }
+        )
+    return rows
+
+
+def _run_batch_import(task_id: str, files: list[dict], method: BatchMethod) -> None:
+    db = SessionLocal()
+    try:
+        for index, item in enumerate(files, start=1):
+            path = Path(item["path"])
+            filename = item["filename"]
+            _set_task(task_id, current_file=filename)
+            try:
+                if method == "excel":
+                    if path.suffix.lower() not in [".xlsx", ".xlsm", ".xltx", ".xltm"]:
+                        raise ValueError("仅支持 Excel 文件")
+                    rows = parse_excel_file(path)
+                else:
+                    rows = _build_ai_rows(path)
+
+                questions = [Question(**row) for row in rows]
+                if questions:
+                    db.add_all(questions)
+                db.add(
+                    ImportHistory(
+                        filename=filename,
+                        method=method,
+                        question_count=len(questions),
+                        status="success",
+                    )
+                )
+                db.commit()
+
+                with BATCH_TASKS_LOCK:
+                    task = BATCH_TASKS[task_id]
+                    task["success_count"] += 1
+                    task["total_questions"] += len(questions)
+                    task["results"].append(
+                        {
+                            "filename": filename,
+                            "status": "success",
+                            "question_count": len(questions),
+                        }
+                    )
+            except Exception as exc:
+                db.rollback()
+                db.add(
+                    ImportHistory(
+                        filename=filename,
+                        method=method,
+                        question_count=0,
+                        status="failed",
+                    )
+                )
+                db.commit()
+                with BATCH_TASKS_LOCK:
+                    task = BATCH_TASKS[task_id]
+                    task["failed_count"] += 1
+                    task["results"].append(
+                        {
+                            "filename": filename,
+                            "status": "failed",
+                            "error": str(exc),
+                            "question_count": 0,
+                        }
+                    )
+            finally:
+                _set_task(task_id, processed=index)
+
+        _set_task(
+            task_id,
+            status="completed",
+            current_file="",
+            ended_at=datetime.utcnow().isoformat(),
+        )
+    except Exception as exc:
+        _set_task(
+            task_id,
+            status="failed",
+            error=str(exc),
+            ended_at=datetime.utcnow().isoformat(),
+        )
+    finally:
+        db.close()
+
 
 @router.post("/ai/parse")
 def parse_by_ai(file: UploadFile = File(...)) -> dict:
     path = save_upload(file)
-    parser = DMXAPIService()
+    parser = OpenAICompatibleParserService()
     metadata = extract_metadata(file.filename or path.name)
-    questions = parser.parse_file(str(path))
+    try:
+        questions = parser.parse_file(str(path))
+    except ValueError as exc:
+        raise HTTPException(status_code=502, detail=str(exc)) from exc
     preview = []
     for q in questions:
         preview.append(
@@ -95,3 +223,110 @@ def download_template() -> dict:
 def import_history(db: Session = Depends(get_db)) -> list[ImportHistoryOut]:
     rows = db.query(ImportHistory).order_by(ImportHistory.created_at.desc()).limit(100).all()
     return [ImportHistoryOut.model_validate(r) for r in rows]
+
+
+@router.post("/batch/start")
+def start_batch_import(
+    background_tasks: BackgroundTasks,
+    files: list[UploadFile] = File(...),
+    method: BatchMethod = Form("ai"),
+) -> dict:
+    if not files:
+        raise HTTPException(status_code=400, detail="请至少上传一个文件")
+
+    task_id = uuid4().hex
+    saved_files: list[dict] = []
+    for f in files:
+        saved_path = save_upload(f)
+        saved_files.append({"path": str(saved_path), "filename": f.filename or Path(saved_path).name})
+
+    with BATCH_TASKS_LOCK:
+        BATCH_TASKS[task_id] = {
+            "task_id": task_id,
+            "status": "running",
+            "method": method,
+            "total": len(saved_files),
+            "processed": 0,
+            "current_file": "",
+            "success_count": 0,
+            "failed_count": 0,
+            "total_questions": 0,
+            "results": [],
+            "error": "",
+            "started_at": datetime.utcnow().isoformat(),
+            "ended_at": "",
+        }
+    background_tasks.add_task(_run_batch_import, task_id, saved_files, method)
+    return {"task_id": task_id}
+
+
+@router.get("/batch/{task_id}")
+def get_batch_import_progress(task_id: str) -> dict:
+    with BATCH_TASKS_LOCK:
+        task = BATCH_TASKS.get(task_id)
+        if not task:
+            raise HTTPException(status_code=404, detail="任务不存在")
+        total = task["total"] or 1
+        progress = round((task["processed"] / total) * 100, 2)
+        return {**task, "progress": progress}
+
+
+# ----- 持久化队列 Jobs API -----
+
+@router.post("/jobs", response_model=ImportJobOut)
+def create_import_job(
+    files: list[UploadFile] = File(...),
+    method: BatchMethod = Form("ai"),
+    db: Session = Depends(get_db),
+) -> ImportJobOut:
+    if not files:
+        raise HTTPException(status_code=400, detail="请至少上传一个文件")
+    job = import_job_repo.create_job_empty(db, method)
+    items: list[dict] = []
+    for seq, f in enumerate(files, start=1):
+        path = save_upload_for_job(job.id, seq, f)
+        items.append({"filename": f.filename or path.name, "stored_path": str(path)})
+    import_job_repo.add_job_items(db, job.id, items)
+    job = import_job_repo.get_job(db, job.id)
+    return ImportJobOut.model_validate(job)
+
+
+@router.get("/jobs/{job_id}", response_model=ImportJobOut)
+def get_import_job(job_id: int, db: Session = Depends(get_db)) -> ImportJobOut:
+    job = import_job_repo.get_job(db, job_id)
+    if not job:
+        raise HTTPException(status_code=404, detail="任务不存在")
+    return ImportJobOut.model_validate(job)
+
+
+@router.get("/jobs", response_model=list[ImportJobOut])
+def list_import_jobs(
+    status: str | None = Query(None, description="queued,running 等，逗号分隔"),
+    limit: int = Query(50, le=100),
+    db: Session = Depends(get_db),
+) -> list[ImportJobOut]:
+    statuses = [s.strip() for s in status.split(",") if s.strip()] if status else None
+    jobs = import_job_repo.list_jobs(db, statuses=statuses, limit=limit)
+    return [ImportJobOut.model_validate(j) for j in jobs]
+
+
+@router.post("/jobs/{job_id}/retry", response_model=ImportJobOut)
+def retry_import_job(job_id: int, db: Session = Depends(get_db)) -> ImportJobOut:
+    job = import_job_repo.get_job(db, job_id)
+    if not job:
+        raise HTTPException(status_code=404, detail="任务不存在")
+    failed = import_job_repo.get_failed_items(db, job_id)
+    if not failed:
+        raise HTTPException(status_code=400, detail="没有可重试的失败项")
+    items = [{"filename": it.filename, "stored_path": it.stored_path} for it in failed]
+    new_job = import_job_repo.create_job(db, job.method, items)
+    new_job = import_job_repo.get_job(db, new_job.id)
+    return ImportJobOut.model_validate(new_job)
+
+
+@router.post("/jobs/{job_id}/cancel", response_model=ImportJobOut)
+def cancel_import_job(job_id: int, db: Session = Depends(get_db)) -> ImportJobOut:
+    job = import_job_repo.cancel_job(db, job_id)
+    if not job:
+        raise HTTPException(status_code=400, detail="任务不存在或无法取消")
+    return ImportJobOut.model_validate(job)

backend/schemas.py

@@ -103,6 +103,45 @@ class ImportHistoryOut(BaseModel):
         from_attributes = True
 
 
+class ImportJobItemOut(BaseModel):
+    id: int
+    job_id: int
+    seq: int
+    filename: str
+    stored_path: str
+    status: str
+    attempt: int
+    error: str
+    question_count: int
+    started_at: datetime | None
+    ended_at: datetime | None
+
+    class Config:
+        from_attributes = True
+
+
+class ImportJobOut(BaseModel):
+    id: int
+    status: str
+    method: str
+    total: int
+    processed: int
+    success_count: int
+    failed_count: int
+    current_index: int
+    current_file: str
+    error: str
+    attempt: int
+    created_at: datetime
+    started_at: datetime | None
+    ended_at: datetime | None
+    updated_at: datetime
+    items: list[ImportJobItemOut] = []
+
+    class Config:
+        from_attributes = True
+
+
 class PracticeStartRequest(BaseModel):
     chapter: Optional[str] = None
     secondary_knowledge: Optional[str] = None

backend/services/file_utils.py

@@ -18,3 +18,14 @@ def save_upload(upload_file: UploadFile) -> Path:
     with target_path.open("wb") as buffer:
         shutil.copyfileobj(upload_file.file, buffer)
     return target_path
+
+
+def save_upload_for_job(job_id: int, seq: int, upload_file: UploadFile) -> Path:
+    """Save file with unique path under upload_dir/job_id/ to avoid overwrites."""
+    base = ensure_upload_dir() / str(job_id)
+    base.mkdir(parents=True, exist_ok=True)
+    name = upload_file.filename or "file"
+    target_path = base / f"{seq}_{name}"
+    with target_path.open("wb") as buffer:
+        shutil.copyfileobj(upload_file.file, buffer)
+    return target_path

backend/services/import_queue_service.py

@@ -0,0 +1,180 @@
+"""
+Import queue: single-consumer FIFO worker and job execution.
+Run run_worker_loop() in a background thread; on startup call reset_stale_running_jobs().
+"""
+
+from datetime import datetime
+from pathlib import Path
+import time
+
+from sqlalchemy.orm import Session
+
+from backend.database import SessionLocal
+from backend.models import (
+    JOB_STATUS_FAILED,
+    JOB_STATUS_QUEUED,
+    JOB_STATUS_RUNNING,
+    JOB_STATUS_SUCCESS,
+    ImportHistory,
+    ImportJob,
+    ImportJobItem,
+    Question,
+)
+from backend.repositories import import_job_repo as repo
+from backend.services.excel_service import parse_excel_file
+from backend.services.parser import OpenAICompatibleParserService, extract_metadata
+
+
+def _build_ai_rows(path: Path) -> list[dict]:
+    parser = OpenAICompatibleParserService()
+    metadata = extract_metadata(path.name)
+    questions = parser.parse_file(str(path))
+    rows = []
+    for q in questions:
+        rows.append(
+            {
+                "chapter": metadata["chapter"],
+                "primary_knowledge": "",
+                "secondary_knowledge": metadata["secondary_knowledge"],
+                "question_type": metadata["question_type"],
+                "difficulty": metadata["difficulty"],
+                "stem": q.get("题干", ""),
+                "option_a": q.get("选项A", ""),
+                "option_b": q.get("选项B", ""),
+                "option_c": q.get("选项C", ""),
+                "option_d": q.get("选项D", ""),
+                "answer": q.get("正确答案", ""),
+                "explanation": q.get("解析", ""),
+                "notes": q.get("备注", ""),
+                "source_file": metadata["source_file"],
+            }
+        )
+    return rows
+
+
+def _process_one_item(
+    db: Session,
+    job: ImportJob,
+    item: ImportJobItem,
+    method: str,
+) -> None:
+    path = Path(item.stored_path)
+    filename = item.filename
+    job.current_file = filename
+    job.current_index = item.seq
+    job.updated_at = datetime.utcnow()
+    item.status = JOB_STATUS_RUNNING
+    item.started_at = datetime.utcnow()
+    db.commit()
+
+    try:
+        if method == "excel":
+            if path.suffix.lower() not in [".xlsx", ".xlsm", ".xltx", ".xltm"]:
+                raise ValueError("仅支持 Excel 文件")
+            rows = parse_excel_file(path)
+        else:
+            rows = _build_ai_rows(path)
+
+        questions = [Question(**row) for row in rows]
+        if questions:
+            db.add_all(questions)
+        db.add(
+            ImportHistory(
+                filename=filename,
+                method=method,
+                question_count=len(questions),
+                status="success",
+            )
+        )
+        db.commit()
+
+        item.status = JOB_STATUS_SUCCESS
+        item.question_count = len(questions)
+        item.ended_at = datetime.utcnow()
+        job.success_count += 1
+        job.processed += 1
+        job.updated_at = datetime.utcnow()
+        db.commit()
+    except Exception as exc:
+        db.rollback()
+        db.add(
+            ImportHistory(
+                filename=filename,
+                method=method,
+                question_count=0,
+                status="failed",
+            )
+        )
+        db.commit()
+        item.status = JOB_STATUS_FAILED
+        item.error = str(exc)
+        item.ended_at = datetime.utcnow()
+        job.failed_count += 1
+        job.processed += 1
+        job.updated_at = datetime.utcnow()
+        db.commit()
+
+
+def process_job(db: Session, job_id: int) -> None:
+    """Execute a single job: process all items in order, then set job terminal status."""
+    job = repo.get_job(db, job_id)
+    if not job or job.status != JOB_STATUS_RUNNING:
+        return
+    method = job.method
+    items = sorted(job.items, key=lambda x: x.seq)
+    # Resume: ensure processed/success_count/failed_count reflect already-completed items
+    job.processed = sum(1 for it in items if it.status in (JOB_STATUS_SUCCESS, JOB_STATUS_FAILED))
+    job.success_count = sum(1 for it in items if it.status == JOB_STATUS_SUCCESS)
+    job.failed_count = sum(1 for it in items if it.status == JOB_STATUS_FAILED)
+    db.commit()
+    for item in items:
+        if item.status in (JOB_STATUS_SUCCESS, JOB_STATUS_FAILED):
+            continue
+        _process_one_item(db, job, item, method)
+        db.refresh(job)
+
+    job = repo.get_job(db, job_id)
+    if not job:
+        return
+    if job.failed_count > 0 and job.success_count == 0:
+        job.status = JOB_STATUS_FAILED
+        job.error = "部分或全部文件处理失败"
+    else:
+        job.status = JOB_STATUS_SUCCESS
+        job.error = ""
+    job.ended_at = datetime.utcnow()
+    job.current_file = ""
+    job.updated_at = datetime.utcnow()
+    db.commit()
+
+
+def reset_stale_running_jobs(db: Session) -> int:
+    """On startup: set any job left in 'running' back to 'queued' so worker can pick it up."""
+    count = 0
+    for job in db.query(ImportJob).filter(ImportJob.status == JOB_STATUS_RUNNING).all():
+        job.status = JOB_STATUS_QUEUED
+        count += 1
+    if count:
+        db.commit()
+    return count
+
+
+def run_worker_loop(interval_seconds: float = 1.0) -> None:
+    """
+    Single-consumer FIFO loop. Call from a background thread.
+    Claims oldest queued job, processes it, then repeats. Sleeps when no job.
+    """
+    while True:
+        db = SessionLocal()
+        try:
+            job = repo.claim_oldest_queued(db)
+            if job:
+                process_job(db, job.id)
+            else:
+                time.sleep(interval_seconds)
+        except Exception:
+            if db:
+                db.rollback()
+            time.sleep(interval_seconds)
+        finally:
+            db.close()

backend/services/parser.py

@@ -1,6 +1,8 @@
 import json
 import re
+import shutil
 import subprocess
+import tempfile
 from pathlib import Path
 
 import requests
@@ -8,11 +10,13 @@ import requests
 from backend.config import settings
 
 
-class DMXAPIService:
+
+
+class OpenAICompatibleParserService:
     def __init__(self) -> None:
         self.api_key = settings.api_key
         self.model_name = settings.model_name
-        self.api_url = settings.dmxapi_url
+        self.api_url = settings.openai_api_url
 
     def parse_file(self, file_path: str) -> list[dict]:
         path = Path(file_path)
@@ -51,33 +55,94 @@ class DMXAPIService:
     def _convert_to_pdf(self, path: Path) -> Path:
         pdf_path = path.with_suffix(".pdf")
         pdf_path.unlink(missing_ok=True)
+        source_path = path
+        temp_dir: str | None = None
 
-        cmd = [
-            "pandoc",
-            str(path),
-            "-o",
-            str(pdf_path),
-            "--pdf-engine=xelatex",
-            "-V",
-            "CJKmainfont=PingFang SC",
-        ]
-        result = subprocess.run(cmd, capture_output=True, text=True, timeout=90)
-        if result.returncode != 0:
-            fallback = [
+        if path.suffix.lower() == ".doc":
+            source_path, temp_dir = self._convert_doc_to_docx(path)
+
+        try:
+            cmd = [
                 "pandoc",
-                str(path),
+                str(source_path),
                 "-o",
                 str(pdf_path),
-                "--pdf-engine=weasyprint",
+                "--pdf-engine=xelatex",
+                "-V",
+                "CJKmainfont=PingFang SC",
             ]
-            result = subprocess.run(fallback, capture_output=True, text=True, timeout=90)
+            result = subprocess.run(cmd, capture_output=True, text=True, timeout=90)
             if result.returncode != 0:
-                raise ValueError(f"文件转 PDF 失败: {result.stderr}")
-        return pdf_path
+                fallback = [
+                    "pandoc",
+                    str(source_path),
+                    "-o",
+                    str(pdf_path),
+                    "--pdf-engine=weasyprint",
+                ]
+                result = subprocess.run(fallback, capture_output=True, text=True, timeout=90)
+                if result.returncode != 0:
+                    raise ValueError(f"文件转 PDF 失败: {result.stderr}")
+            return pdf_path
+        finally:
+            if temp_dir:
+                shutil.rmtree(temp_dir, ignore_errors=True)
+
+    def _convert_doc_to_docx(self, path: Path) -> tuple[Path, str]:
+        temp_dir = tempfile.mkdtemp(prefix="pb_doc_convert_")
+        converted_path = Path(temp_dir) / f"{path.stem}.docx"
+        convert_errors: list[str] = []
+
+        if shutil.which("soffice"):
+            result = subprocess.run(
+                [
+                    "soffice",
+                    "--headless",
+                    "--convert-to",
+                    "docx",
+                    "--outdir",
+                    temp_dir,
+                    str(path),
+                ],
+                capture_output=True,
+                text=True,
+                timeout=120,
+            )
+            if result.returncode == 0 and converted_path.exists():
+                return converted_path, temp_dir
+            convert_errors.append(f"soffice: {(result.stderr or result.stdout).strip()}")
+        else:
+            convert_errors.append("soffice: 未安装")
+
+        if shutil.which("textutil"):
+            result = subprocess.run(
+                [
+                    "textutil",
+                    "-convert",
+                    "docx",
+                    "-output",
+                    str(converted_path),
+                    str(path),
+                ],
+                capture_output=True,
+                text=True,
+                timeout=120,
+            )
+            if result.returncode == 0 and converted_path.exists():
+                return converted_path, temp_dir
+            convert_errors.append(f"textutil: {(result.stderr or result.stdout).strip()}")
+        else:
+            convert_errors.append("textutil: 未安装")
+
+        raise ValueError(
+            "检测到 .doc 文件，pandoc 不支持直接转换。"
+            "已尝试自动转换为 .docx 但失败。请先把 .doc 另存为 .docx 后重试。"
+            f" 详细信息: {' | '.join(convert_errors)}"
+        )
 
     def _parse_with_file_url(self, file_url: str, original_filename: str) -> list[dict]:
         if not self.api_key:
-            raise ValueError("未配置 API_KEY，无法调用 DMXAPI")
+            raise ValueError("未配置 API_KEY，无法调用 OpenAI 兼容接口")
 
         payload = {
             "model": self.model_name,
@@ -99,7 +164,7 @@ class DMXAPIService:
             self.api_url, headers=headers, data=json.dumps(payload), timeout=180
         )
         if response.status_code != 200:
-            raise ValueError(f"DMXAPI 请求失败: {response.status_code} {response.text}")
+            raise ValueError(f"OpenAI 兼容接口请求失败: {response.status_code} {response.text}")
         return self._extract_questions(response.json())
 
     def _build_instruction(self, filename: str) -> str:

backend/tests/__init__.py

@@ -0,0 +1 @@
+# Backend tests

backend/tests/conftest.py

@@ -0,0 +1,17 @@
+import pytest
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+
+from backend.database import Base
+
+
+@pytest.fixture
+def db_session():
+    engine = create_engine("sqlite:///:memory:")
+    Base.metadata.create_all(engine)
+    Session = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+    session = Session()
+    try:
+        yield session
+    finally:
+        session.close()

backend/tests/test_import_job_repo.py

@@ -0,0 +1,82 @@
+"""Tests for import job repository: create, get, list, claim FIFO, cancel, failed items."""
+
+import pytest
+
+from backend.models import JOB_STATUS_QUEUED, JOB_STATUS_RUNNING
+from backend.repositories import import_job_repo as repo
+
+
+def test_create_job(db_session):
+    items = [
+        {"filename": "a.xlsx", "stored_path": "/up/1/a.xlsx"},
+        {"filename": "b.xlsx", "stored_path": "/up/1/b.xlsx"},
+    ]
+    job = repo.create_job(db_session, "excel", items)
+    assert job.id is not None
+    assert job.status == JOB_STATUS_QUEUED
+    assert job.method == "excel"
+    assert job.total == 2
+    assert job.processed == 0
+    assert len(job.items) == 2
+    assert job.items[0].filename == "a.xlsx" and job.items[0].seq == 1
+    assert job.items[1].filename == "b.xlsx" and job.items[1].seq == 2
+
+
+def test_get_job(db_session):
+    job = repo.create_job(db_session, "ai", [{"filename": "f.pdf", "stored_path": "/f.pdf"}])
+    loaded = repo.get_job(db_session, job.id)
+    assert loaded is not None
+    assert loaded.id == job.id
+    assert len(loaded.items) == 1
+    assert repo.get_job(db_session, 99999) is None
+
+
+def test_list_jobs(db_session):
+    repo.create_job(db_session, "excel", [{"filename": "a", "stored_path": "/a"}])
+    repo.create_job(db_session, "excel", [{"filename": "b", "stored_path": "/b"}])
+    all_jobs = repo.list_jobs(db_session, limit=10)
+    assert len(all_jobs) >= 2
+    statuses = repo.list_jobs(db_session, statuses=[JOB_STATUS_QUEUED], limit=10)
+    assert all(j.status == JOB_STATUS_QUEUED for j in statuses)
+
+
+def test_claim_oldest_queued_fifo(db_session):
+    j1 = repo.create_job(db_session, "excel", [{"filename": "a", "stored_path": "/a"}])
+    j2 = repo.create_job(db_session, "excel", [{"filename": "b", "stored_path": "/b"}])
+    claimed = repo.claim_oldest_queued(db_session)
+    assert claimed is not None
+    assert claimed.id == j1.id
+    assert claimed.status == JOB_STATUS_RUNNING
+    second = repo.claim_oldest_queued(db_session)
+    assert second is not None
+    assert second.id == j2.id
+    assert repo.claim_oldest_queued(db_session) is None
+
+
+def test_cancel_job(db_session):
+    job = repo.create_job(db_session, "excel", [{"filename": "a", "stored_path": "/a"}])
+    cancelled = repo.cancel_job(db_session, job.id)
+    assert cancelled is not None
+    assert cancelled.status == "cancelled"
+    loaded = repo.get_job(db_session, job.id)
+    assert loaded.status == "cancelled"
+    assert repo.cancel_job(db_session, job.id) is None  # already cancelled
+
+
+def test_get_failed_items(db_session):
+    job = repo.create_job(
+        db_session,
+        "excel",
+        [
+            {"filename": "a", "stored_path": "/a"},
+            {"filename": "b", "stored_path": "/b"},
+        ],
+    )
+    failed = repo.get_failed_items(db_session, job.id)
+    assert len(failed) == 0
+    job.items[0].status = "failed"
+    job.items[0].error = "err"
+    db_session.commit()
+    failed = repo.get_failed_items(db_session, job.id)
+    assert len(failed) == 1
+    assert failed[0].filename == "a"

frontend/src/App.tsx

@@ -1,5 +1,5 @@
 import { Layout, Menu, message } from "antd";
-import { useMemo, useState } from "react";
+import { useEffect, useMemo, useState } from "react";
 import { Navigate, Route, Routes, useLocation, useNavigate } from "react-router-dom";
 import LoginModal from "./components/LoginModal";
 import Categories from "./pages/Categories";
@@ -26,6 +26,14 @@ export default function App() {
   const location = useLocation();
   const [loggedIn, setLoggedIn] = useState(Boolean(localStorage.getItem("pb_token")));
 
+  useEffect(() => {
+    const handleUnauthorized = () => {
+      setLoggedIn(false);
+    };
+    window.addEventListener("pb-auth-unauthorized", handleUnauthorized);
+    return () => window.removeEventListener("pb-auth-unauthorized", handleUnauthorized);
+  }, []);
+
   const selectedKey = useMemo(() => {
     const hit = menuItems.find((m) => location.pathname.startsWith(m.key));
     return hit ? [hit.key] : ["/dashboard"];

frontend/src/api/index.ts

@@ -12,4 +12,80 @@ api.interceptors.request.use((config) => {
   return config;
 });
 
+api.interceptors.response.use(
+  (response) => response,
+  (error) => {
+    if (error?.response?.status === 401) {
+      localStorage.removeItem("pb_token");
+      window.dispatchEvent(new CustomEvent("pb-auth-unauthorized"));
+    }
+    return Promise.reject(error);
+  }
+);
+
+// 导入任务（持久化队列）类型与 API
+export interface ImportJobItemOut {
+  id: number;
+  job_id: number;
+  seq: number;
+  filename: string;
+  stored_path: string;
+  status: string;
+  attempt: number;
+  error: string;
+  question_count: number;
+  started_at: string | null;
+  ended_at: string | null;
+}
+
+export interface ImportJobOut {
+  id: number;
+  status: string;
+  method: string;
+  total: number;
+  processed: number;
+  success_count: number;
+  failed_count: number;
+  current_index: number;
+  current_file: string;
+  error: string;
+  attempt: number;
+  created_at: string;
+  started_at: string | null;
+  ended_at: string | null;
+  updated_at: string;
+  items: ImportJobItemOut[];
+}
+
+export async function createImportJob(files: File[], method: "excel" | "ai"): Promise<ImportJobOut> {
+  const formData = new FormData();
+  formData.append("method", method);
+  files.forEach((file) => formData.append("files", file));
+  const { data } = await api.post<ImportJobOut>("/import/jobs", formData, {
+    headers: { "Content-Type": "multipart/form-data" }
+  });
+  return data;
+}
+
+export async function getImportJob(jobId: number): Promise<ImportJobOut> {
+  const { data } = await api.get<ImportJobOut>(`/import/jobs/${jobId}`);
+  return data;
+}
+
+export async function listImportJobs(status?: string): Promise<ImportJobOut[]> {
+  const params = status ? { status } : {};
+  const { data } = await api.get<ImportJobOut[]>("/import/jobs", { params });
+  return data;
+}
+
+export async function retryImportJob(jobId: number): Promise<ImportJobOut> {
+  const { data } = await api.post<ImportJobOut>(`/import/jobs/${jobId}/retry`);
+  return data;
+}
+
+export async function cancelImportJob(jobId: number): Promise<ImportJobOut> {
+  const { data } = await api.post<ImportJobOut>(`/import/jobs/${jobId}/cancel`);
+  return data;
+}
+
 export default api;

frontend/src/pages/Import.tsx

@@ -1,92 +1,334 @@
-import { Button, Card, Table, Tabs, Upload, message } from "antd";
-import type { UploadProps } from "antd";
-import { useState } from "react";
-import api from "../api";
+import { Button, Card, Progress, Select, Space, Table, Tag, Upload, message } from "antd";
+import type { UploadFile, UploadProps } from "antd";
+import { useCallback, useEffect, useRef, useState } from "react";
+import {
+  createImportJob,
+  getImportJob,
+  listImportJobs,
+  retryImportJob,
+  cancelImportJob,
+  type ImportJobOut
+} from "../api";
+
+type ImportMethod = "excel" | "ai";
+
+const POLL_INTERVAL_MS = 1500;
+const TERMINAL_STATUSES = ["success", "failed", "cancelled"];
+const IMPORT_METHOD_KEY = "pb_import_method";
+
+function isTerminal(status: string) {
+  return TERMINAL_STATUSES.includes(status);
+}
+
+function loadStoredMethod(): ImportMethod {
+  try {
+    const v = sessionStorage.getItem(IMPORT_METHOD_KEY);
+    if (v === "excel" || v === "ai") return v;
+  } catch {
+    /* ignore */
+  }
+  return "ai";
+}
 
 export default function ImportPage() {
-  const [preview, setPreview] = useState<Record<string, string>[]>([]);
+  const [method, setMethod] = useState<ImportMethod>(loadStoredMethod);
+  const [jobs, setJobs] = useState<ImportJobOut[]>([]);
+  const [pendingFiles, setPendingFiles] = useState<UploadFile[]>([]);
   const [loading, setLoading] = useState(false);
+  const pollTimerRef = useRef<ReturnType<typeof setInterval> | null>(null);
 
-  const aiProps: UploadProps = {
-    name: "file",
-    customRequest: async ({ file, onSuccess, onError }) => {
+  // Persist method so remounts (e.g. Strict Mode, route switch) restore selection
+  const setMethodAndStore = useCallback((value: ImportMethod) => {
+    setMethod(value);
+    try {
+      sessionStorage.setItem(IMPORT_METHOD_KEY, value);
+    } catch {
+      /* ignore */
+    }
+  }, []);
+
+
+
+  const activeJobs = jobs.filter((j) => !isTerminal(j.status));
+  const hasActive = activeJobs.length > 0;
+  const pendingCount = pendingFiles.length;
+
+  const fetchJob = useCallback(async (jobId: number) => {
+    try {
+      const job = await getImportJob(jobId);
+      setJobs((prev) => {
+        const next = prev.map((j) => (j.id === jobId ? job : j));
+        if (!next.find((j) => j.id === jobId)) next.unshift(job);
+        return next;
+      });
+      return job;
+    } catch {
+      return null;
+    }
+  }, []);
+
+  const startPolling = useCallback(() => {
+    if (pollTimerRef.current) return;
+    pollTimerRef.current = setInterval(() => {
+      setJobs((prev) => {
+        const toPoll = prev.filter((j) => !isTerminal(j.status));
+        toPoll.forEach((j) => {
+          getImportJob(j.id).then((job) => {
+            setJobs((p) => p.map((x) => (x.id === job.id ? job : x)));
+          }).catch(() => {});
+        });
+        return prev;
+      });
+    }, POLL_INTERVAL_MS);
+  }, []);
+
+  const stopPolling = useCallback(() => {
+    if (pollTimerRef.current) {
+      clearInterval(pollTimerRef.current);
+      pollTimerRef.current = null;
+    }
+  }, []);
+
+  useEffect(() => {
+    if (!hasActive) {
+      stopPolling();
+      return;
+    }
+    startPolling();
+    return () => { stopPolling(); };
+  }, [hasActive, startPolling, stopPolling]);
+
+  useEffect(() => {
+    let cancelled = false;
+    (async () => {
       try {
-        setLoading(true);
-        const formData = new FormData();
-        formData.append("file", file as File);
-        const { data } = await api.post("/import/ai/parse", formData);
-        setPreview(data.preview || []);
-        message.success("AI 解析完成");
-        onSuccess?.({});
-      } catch (err) {
-        onError?.(err as Error);
-      } finally {
-        setLoading(false);
+        const list = await listImportJobs("queued,running");
+        if (!cancelled) {
+          setJobs((prev) => {
+            const byId = new Map(prev.map((j) => [j.id, j]));
+            list.forEach((j) => byId.set(j.id, j));
+            return Array.from(byId.values()).sort((a, b) => b.id - a.id);
+          });
+        }
+      } catch {
+        // ignore
       }
+    })();
+    return () => { cancelled = true; };
+  }, []);
+
+  const uploadProps: UploadProps = {
+    multiple: true,
+    beforeUpload: () => false,
+    fileList: pendingFiles,
+    onChange: (info) => {
+      setPendingFiles(info.fileList.slice(-100));
+    },
+    disabled: loading
+  };
+
+  const startImport = async () => {
+    if (!pendingFiles.length) {
+      message.info("请先添加文档");
+      return;
+    }
+    const files = pendingFiles.map((f) => f.originFileObj).filter(Boolean) as File[];
+    if (!files.length) {
+      message.info("没有可上传的文件");
+      return;
+    }
+    setLoading(true);
+    try {
+      const job = await createImportJob(files, method);
+      setJobs((prev) => [job, ...prev]);
+      setPendingFiles([]);
+      message.success("任务已入队，将按顺序处理");
+      startPolling();
+    } catch (err: unknown) {
+      const detail = err && typeof err === "object" && "response" in err
+        ? (err as { response?: { data?: { detail?: string } } }).response?.data?.detail
+        : "创建任务失败";
+      message.error(String(detail));
+    } finally {
+      setLoading(false);
     }
   };
 
-  const excelProps: UploadProps = {
-    name: "file",
-    customRequest: async ({ file, onSuccess, onError }) => {
-      try {
-        const formData = new FormData();
-        formData.append("file", file as File);
-        const { data } = await api.post("/import/excel", formData);
-        message.success(`Excel 导入成功，共 ${data.length} 题`);
-        onSuccess?.({});
-      } catch (err) {
-        onError?.(err as Error);
-      }
+  const handleRetry = async (jobId: number) => {
+    if (loading) return;
+    setLoading(true);
+    try {
+      const newJob = await retryImportJob(jobId);
+      setJobs((prev) => [newJob, ...prev]);
+      message.success("已创建重试任务");
+      startPolling();
+    } catch (err: unknown) {
+      const detail = err && typeof err === "object" && "response" in err
+        ? (err as { response?: { data?: { detail?: string } } }).response?.data?.detail
+        : "重试失败";
+      message.error(String(detail));
+    } finally {
+      setLoading(false);
     }
   };
 
-  const confirmSave = async () => {
-    await api.post("/import/ai/confirm", preview);
-    message.success(`已保存 ${preview.length} 道题`);
-    setPreview([]);
+  const handleCancel = async (jobId: number) => {
+    if (loading) return;
+    setLoading(true);
+    try {
+      const job = await cancelImportJob(jobId);
+      setJobs((prev) => prev.map((j) => (j.id === jobId ? job : j)));
+      message.success("已取消任务");
+    } catch {
+      message.error("取消失败");
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  const clearFinished = () => {
+    setJobs((prev) => prev.filter((j) => !isTerminal(j.status)));
+  };
+
+  const progressPercent = (job: ImportJobOut) =>
+    job.total ? Number(((job.processed / job.total) * 100).toFixed(2)) : 0;
+
+  const statusTag = (status: string) => {
+    if (status === "queued") return <Tag>排队中</Tag>;
+    if (status === "running") return <Tag color="processing">处理中</Tag>;
+    if (status === "success") return <Tag color="success">成功</Tag>;
+    if (status === "failed") return <Tag color="error">失败</Tag>;
+    if (status === "cancelled") return <Tag>已取消</Tag>;
+    if (status === "retrying") return <Tag color="processing">重试中</Tag>;
+    return <Tag>{status}</Tag>;
   };
 
   return (
-    <Tabs
-      items={[
-        {
-          key: "ai",
-          label: "AI 智能导入",
-          children: (
-            <Card>
-              <Upload {...aiProps} showUploadList={false}>
-                <Button type="primary" loading={loading}>上传 PDF/Word 解析</Button>
-              </Upload>
+    <Card title="导入中心">
+      <Space direction="vertical" size={16} style={{ width: "100%" }}>
+        <Space wrap>
+          <span>导入方式：</span>
+          <Select
+            value={method}
+            onChange={(v) => {
+              setMethodAndStore(v as ImportMethod);
+            }}
+            options={[
+              { value: "excel", label: "Excel 批量导入" },
+              { value: "ai", label: "AI 文档解析导入" }
+            ]}
+            style={{ width: 220 }}
+            disabled={loading}
+          />
+          <Upload {...uploadProps} showUploadList={{ showRemoveIcon: true }}>
+            <Button>添加文档</Button>
+          </Upload>
+          <Button
+            type="primary"
+            onClick={startImport}
+            loading={loading}
+            disabled={!pendingCount}
+          >
+            开始导入（{pendingCount}）
+          </Button>
+          <Button onClick={clearFinished} disabled={loading}>
+            清理已完成
+          </Button>
+        </Space>
+
+        <div>
+          进行中：{activeJobs.length} | 成功/失败/已取消 已折叠，仅保留未完成任务
+        </div>
+
+        <Table
+          rowKey="id"
+          dataSource={jobs}
+          pagination={{ pageSize: 10 }}
+          loading={loading}
+          expandable={{
+            expandedRowRender: (record) => (
               <Table
-                style={{ marginTop: 16 }}
-                rowKey={(_, index) => String(index)}
-                dataSource={preview}
+                size="small"
+                rowKey="id"
+                dataSource={record.items || []}
                 columns={[
-                  { title: "题干", dataIndex: "stem" },
-                  { title: "答案", dataIndex: "answer", width: 120 },
-                  { title: "题型", dataIndex: "question_type", width: 120 }
+                  { title: "序号", dataIndex: "seq", width: 60 },
+                  { title: "文件名", dataIndex: "filename" },
+                  {
+                    title: "状态",
+                    dataIndex: "status",
+                    width: 90,
+                    render: (s: string) => statusTag(s)
+                  },
+                  { title: "题目数", dataIndex: "question_count", width: 80 },
+                  { title: "错误", dataIndex: "error" }
                 ]}
-                pagination={{ pageSize: 10 }}
+                pagination={false}
               />
-              <Button type="primary" onClick={confirmSave} disabled={!preview.length}>
-                确认保存
-              </Button>
-            </Card>
-          )
-        },
-        {
-          key: "excel",
-          label: "Excel 导入",
-          children: (
-            <Card>
-              <Upload {...excelProps} showUploadList={false}>
-                <Button type="primary">上传 Excel 导入</Button>
-              </Upload>
-            </Card>
-          )
-        }
-      ]}
-    />
+            )
+          }}
+          columns={[
+            { title: "任务 ID", dataIndex: "id", width: 80 },
+            {
+              title: "状态",
+              dataIndex: "status",
+              width: 90,
+              render: (s: string) => statusTag(s)
+            },
+            { title: "方式", dataIndex: "method", width: 80 },
+            {
+              title: "进度",
+              key: "progress",
+              width: 120,
+              render: (_: unknown, row: ImportJobOut) =>
+                `${row.processed}/${row.total}`
+            },
+            {
+              title: "进度条",
+              key: "progressBar",
+              width: 160,
+              render: (_: unknown, row: ImportJobOut) => (
+                <Progress
+                  percent={progressPercent(row)}
+                  size="small"
+                  status={row.status === "failed" ? "exception" : undefined}
+                />
+              )
+            },
+            { title: "当前文件", dataIndex: "current_file", ellipsis: true },
+            { title: "成功", dataIndex: "success_count", width: 70 },
+            { title: "失败", dataIndex: "failed_count", width: 70 },
+            { title: "错误", dataIndex: "error", ellipsis: true },
+            {
+              title: "操作",
+              width: 160,
+              render: (_: unknown, row: ImportJobOut) => (
+                <Space size="small">
+                  {row.status === "failed" && row.failed_count > 0 && (
+                    <Button
+                      size="small"
+                      disabled={loading}
+                      onClick={() => handleRetry(row.id)}
+                    >
+                      重试失败项
+                    </Button>
+                  )}
+                  {(row.status === "queued" || row.status === "running") && (
+                    <Button
+                      size="small"
+                      danger
+                      disabled={loading}
+                      onClick={() => handleCancel(row.id)}
+                    >
+                      取消
+                    </Button>
+                  )}
+                </Space>
+              )
+            }
+          ]}
+        />
+      </Space>
+    </Card>
   );
 }