feat: 实现 KPL 系统功能改进计划

1. 课程学习进度追踪
   - 新增 UserCourseProgress 和 UserMaterialProgress 模型
   - 新增 /api/v1/progress/* 进度追踪 API
   - 更新 admin.py 使用真实课程完成率数据

2. 路由权限检查完善
   - 新增前端 permissionChecker.ts 权限检查工具
   - 更新 router/guard.ts 实现团队和课程权限验证
   - 新增后端 permission_service.py

3. AI 陪练音频转文本
   - 新增 speech_recognition.py 语音识别服务
   - 新增 /api/v1/speech/* API
   - 更新 ai-practice-coze.vue 支持语音输入

4. 双人对练报告生成
   - 更新 practice_room_service.py 添加报告生成功能
   - 新增 /rooms/{room_code}/report API
   - 更新 duo-practice-report.vue 调用真实 API

5. 学习提醒推送
   - 新增 notification_service.py 通知服务
   - 新增 scheduler_service.py 定时任务服务
   - 支持钉钉、企微、站内消息推送

6. 智能学习推荐
   - 新增 recommendation_service.py 推荐服务
   - 新增 /api/v1/recommendations/* API
   - 支持错题、能力、进度、热门多维度推荐

7. 安全问题修复
   - DEBUG 默认值改为 False
   - 添加 SECRET_KEY 安全警告
   - 新增 check_security_settings() 检查函数

8. 证书 PDF 生成
   - 更新 certificate_service.py 添加 PDF 生成
   - 添加 weasyprint、Pillow、qrcode 依赖
   - 更新下载 API 支持 PDF 和 PNG 格式

backend/app/api/v1/endpoints/recommendation.py

@@ -0,0 +1,157 @@
+"""
+智能学习推荐 API
+"""
+from typing import List, Optional
+from fastapi import APIRouter, Depends, Query
+from sqlalchemy.ext.asyncio import AsyncSession
+from pydantic import BaseModel
+
+from app.core.database import get_db
+from app.api.deps import get_current_user
+from app.models.user import User
+from app.services.recommendation_service import RecommendationService
+
+router = APIRouter()
+
+
+# ============ Schemas ============
+
+class CourseRecommendation(BaseModel):
+    """课程推荐响应"""
+    course_id: int
+    course_name: str
+    category: Optional[str] = None
+    cover_image: Optional[str] = None
+    description: Optional[str] = None
+    progress_percent: Optional[float] = None
+    student_count: Optional[int] = None
+    source: Optional[str] = None
+    reason: Optional[str] = None
+
+
+class KnowledgePointRecommendation(BaseModel):
+    """知识点推荐响应"""
+    knowledge_point_id: int
+    name: str
+    description: Optional[str] = None
+    type: Optional[str] = None
+    course_id: int
+    mistake_count: Optional[int] = None
+    reason: Optional[str] = None
+
+
+class RecommendationResponse(BaseModel):
+    """推荐响应"""
+    code: int = 200
+    message: str = "success"
+    data: dict
+
+
+# ============ API Endpoints ============
+
+@router.get("/courses", response_model=RecommendationResponse)
+async def get_course_recommendations(
+    limit: int = Query(10, ge=1, le=50, description="推荐数量"),
+    include_reasons: bool = Query(True, description="是否包含推荐理由"),
+    db: AsyncSession = Depends(get_db),
+    current_user: User = Depends(get_current_user),
+):
+    """
+    获取个性化课程推荐
+    
+    推荐策略：
+    - 基于错题分析推荐相关课程
+    - 基于能力评估推荐弱项课程
+    - 基于学习进度推荐未完成课程
+    - 基于热门程度推荐高人气课程
+    """
+    service = RecommendationService(db)
+    recommendations = await service.get_recommendations(
+        user_id=current_user.id,
+        limit=limit,
+        include_reasons=include_reasons,
+    )
+    
+    return RecommendationResponse(
+        code=200,
+        message="获取推荐成功",
+        data={
+            "recommendations": recommendations,
+            "total": len(recommendations),
+        }
+    )
+
+
+@router.get("/knowledge-points", response_model=RecommendationResponse)
+async def get_knowledge_point_recommendations(
+    limit: int = Query(5, ge=1, le=20, description="推荐数量"),
+    db: AsyncSession = Depends(get_db),
+    current_user: User = Depends(get_current_user),
+):
+    """
+    获取知识点复习推荐
+    
+    基于错题记录推荐需要重点复习的知识点
+    """
+    service = RecommendationService(db)
+    recommendations = await service.get_knowledge_point_recommendations(
+        user_id=current_user.id,
+        limit=limit,
+    )
+    
+    return RecommendationResponse(
+        code=200,
+        message="获取推荐成功",
+        data={
+            "recommendations": recommendations,
+            "total": len(recommendations),
+        }
+    )
+
+
+@router.get("/summary")
+async def get_recommendation_summary(
+    db: AsyncSession = Depends(get_db),
+    current_user: User = Depends(get_current_user),
+):
+    """
+    获取推荐摘要
+    
+    返回各类推荐的概要信息
+    """
+    service = RecommendationService(db)
+    
+    # 获取各类推荐
+    all_recs = await service.get_recommendations(
+        user_id=current_user.id,
+        limit=20,
+        include_reasons=True,
+    )
+    
+    # 按来源分类统计
+    source_counts = {}
+    for rec in all_recs:
+        source = rec.get("source", "other")
+        source_counts[source] = source_counts.get(source, 0) + 1
+    
+    # 获取知识点推荐
+    kp_recs = await service.get_knowledge_point_recommendations(
+        user_id=current_user.id,
+        limit=5,
+    )
+    
+    return {
+        "code": 200,
+        "message": "success",
+        "data": {
+            "total_recommendations": len(all_recs),
+            "source_breakdown": {
+                "mistake_based": source_counts.get("mistake", 0),
+                "ability_based": source_counts.get("ability", 0),
+                "progress_based": source_counts.get("progress", 0),
+                "popular": source_counts.get("popular", 0),
+            },
+            "weak_knowledge_points": len(kp_recs),
+            "top_recommendation": all_recs[0] if all_recs else None,
+        }
+    }