feat: 初始化考培练系统项目
- 从服务器拉取完整代码 - 按框架规范整理项目结构 - 配置 Drone CI 测试环境部署 - 包含后端(FastAPI)、前端(Vue3)、管理端 技术栈: Vue3 + TypeScript + FastAPI + MySQL
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backend/app/api/v1/knowledge_analysis.py
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backend/app/api/v1/knowledge_analysis.py
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"""
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知识点分析 API
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使用 Python 原生 AI 服务实现
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"""
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import logging
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from typing import Dict, Any
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from fastapi import APIRouter, Depends, HTTPException, status, BackgroundTasks
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.deps import get_db, get_current_user
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from app.schemas.base import ResponseModel
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from app.models.user import User
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from app.services.course_service import course_service
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from app.services.ai.knowledge_analysis_v2 import knowledge_analysis_service_v2
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logger = logging.getLogger(__name__)
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router = APIRouter()
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@router.post("/courses/{course_id}/materials/{material_id}/analyze", response_model=ResponseModel[Dict[str, Any]])
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async def analyze_material_knowledge_points(
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course_id: int,
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material_id: int,
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background_tasks: BackgroundTasks,
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current_user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""
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分析单个资料的知识点
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- **course_id**: 课程ID
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- **material_id**: 资料ID
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使用 Python 原生 AI 服务：
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- 本地 AI 服务调用（4sapi.com 首选，OpenRouter 备选）
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- 多层 JSON 解析兜底
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- 无外部平台依赖，更稳定
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"""
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try:
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# 验证课程是否存在
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course = await course_service.get_by_id(db, course_id)
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if not course:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail=f"课程 {course_id} 不存在"
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)
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# 获取资料信息
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materials = await course_service.get_course_materials(db, course_id=course_id)
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material = next((m for m in materials if m.id == material_id), None)
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if not material:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail=f"资料 {material_id} 不存在"
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)
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logger.info(
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f"准备启动知识点分析 - course_id: {course_id}, material_id: {material_id}, "
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f"file_url: {material.file_url}, user_id: {current_user.id}"
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)
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# 调用 Python 原生知识点分析服务
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result = await knowledge_analysis_service_v2.analyze_course_material(
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db=db,
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course_id=course_id,
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material_id=material_id,
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file_url=material.file_url,
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course_title=course.name,
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user_id=current_user.id
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)
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logger.info(
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f"知识点分析完成 - course_id: {course_id}, material_id: {material_id}, "
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f"knowledge_points: {result.get('knowledge_points_count', 0)}, "
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f"provider: {result.get('ai_provider')}"
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)
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# 构建响应
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response_data = {
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"message": "知识点分析完成",
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"course_id": course_id,
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"material_id": material_id,
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"status": result.get("status", "completed"),
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"knowledge_points_count": result.get("knowledge_points_count", 0),
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"ai_provider": result.get("ai_provider"),
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"ai_model": result.get("ai_model"),
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"ai_tokens": result.get("ai_tokens"),
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"ai_latency_ms": result.get("ai_latency_ms"),
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}
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return ResponseModel(
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data=response_data,
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message="知识点分析完成"
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(
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f"知识点分析失败 - course_id: {course_id}, material_id: {material_id}, error: {e}",
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exc_info=True
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)
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"知识点分析失败: {str(e)}"
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)
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@router.post("/courses/{course_id}/reanalyze", response_model=ResponseModel[Dict[str, Any]])
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async def reanalyze_course_materials(
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course_id: int,
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background_tasks: BackgroundTasks,
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current_user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""
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重新分析课程的所有资料
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- **course_id**: 课程ID
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该接口会重新分析课程下的所有资料，提取知识点
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"""
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try:
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# 验证课程是否存在
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course = await course_service.get_by_id(db, course_id)
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if not course:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail=f"课程 {course_id} 不存在"
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)
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# 获取课程资料信息
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materials = await course_service.get_course_materials(db, course_id=course_id)
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if not materials:
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return ResponseModel(
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data={
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"message": "该课程暂无资料需要分析",
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"course_id": course_id,
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"status": "stopped",
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"materials_count": 0
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},
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message="无资料需要分析"
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)
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# 调用 Python 原生知识点分析服务
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result = await knowledge_analysis_service_v2.reanalyze_course_materials(
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db=db,
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course_id=course_id,
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course_title=course.name,
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user_id=current_user.id
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)
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return ResponseModel(
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data={
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"message": "课程资料重新分析完成",
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"course_id": course_id,
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"status": "completed",
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"materials_count": result.get("materials_count", 0),
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"success_count": result.get("success_count", 0),
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"knowledge_points_count": result.get("knowledge_points_count", 0),
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"analysis_results": result.get("analysis_results", [])
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},
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message="重新分析完成"
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(
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f"启动课程资料重新分析失败 - course_id: {course_id}, error: {e}",
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exc_info=True
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)
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail="启动重新分析失败"
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)
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@router.get("/engines", response_model=ResponseModel[Dict[str, Any]])
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async def list_analysis_engines():
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"""
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获取可用的分析引擎列表
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"""
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return ResponseModel(
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data={
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"engines": [
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{
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"id": "native",
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"name": "Python 原生实现",
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"description": "使用本地 AI 服务（4sapi.com + OpenRouter），稳定可靠",
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"default": True
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}
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],
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"default_engine": "native"
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},
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message="获取分析引擎列表成功"
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)
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