big update

backend/app/api/endpoints/preferences.py

@@ -0,0 +1,158 @@
+from typing import List
+
+from fastapi import APIRouter, Depends, HTTPException, Query, status
+from sqlalchemy.exc import IntegrityError
+from sqlalchemy.orm import Session
+
+from app.api.dependencies import get_current_user, get_db
+from app.models.models import AppUser, UserTopicPreference
+from app.schemas.preference_schema import (
+    MatchedEventResponse,
+    UserPreferenceRecommendationResponse,
+    UserTopicPreferenceCreate,
+    UserTopicPreferenceResponse,
+)
+from app.services.matching_service import recommend_events_for_user
+
+router = APIRouter()
+
+
+def _ensure_self_access(path_user_id: int, current_user: AppUser) -> None:
+    """校验路径 user_id 是否为当前登录用户本人。"""
+    if path_user_id != current_user.id:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="You can only operate your own resources",
+        )
+
+
+@router.get(
+    "/users/{user_id}/preferences",
+    response_model=List[UserTopicPreferenceResponse],
+)
+def list_user_preferences(
+    user_id: int,
+    db: Session = Depends(get_db),
+    current_user: AppUser = Depends(get_current_user),
+):
+    """获取用户已设置的兴趣关键词。"""
+    _ensure_self_access(user_id, current_user)
+    preferences = (
+        db.query(UserTopicPreference)
+        .filter(UserTopicPreference.user_id == user_id)
+        .order_by(UserTopicPreference.created_at.desc())
+        .all()
+    )
+    return preferences
+
+
+@router.post(
+    "/users/{user_id}/preferences",
+    response_model=UserTopicPreferenceResponse,
+    status_code=status.HTTP_201_CREATED,
+)
+def create_user_preference(
+    user_id: int,
+    payload: UserTopicPreferenceCreate,
+    db: Session = Depends(get_db),
+    current_user: AppUser = Depends(get_current_user),
+):
+    """新增一个用户兴趣关键词。"""
+    _ensure_self_access(user_id, current_user)
+
+    keyword = payload.interested_keyword.strip()
+    if not keyword:
+        raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Keyword cannot be empty")
+
+    db_obj = UserTopicPreference(
+        user_id=user_id,
+        interested_keyword=keyword,
+    )
+    db.add(db_obj)
+    try:
+        db.commit()
+    except IntegrityError:
+        db.rollback()
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="Preference keyword already exists for this user",
+        )
+
+    db.refresh(db_obj)
+    return db_obj
+
+
+@router.delete(
+    "/users/{user_id}/preferences/{preference_id}",
+    status_code=status.HTTP_204_NO_CONTENT,
+)
+def delete_user_preference(
+    user_id: int,
+    preference_id: int,
+    db: Session = Depends(get_db),
+    current_user: AppUser = Depends(get_current_user),
+):
+    """删除一个用户兴趣关键词。"""
+    _ensure_self_access(user_id, current_user)
+    preference = (
+        db.query(UserTopicPreference)
+        .filter(
+            UserTopicPreference.id == preference_id,
+            UserTopicPreference.user_id == user_id,
+        )
+        .first()
+    )
+    if not preference:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Preference not found")
+
+    db.delete(preference)
+    db.commit()
+    return None
+
+
+@router.get(
+    "/users/{user_id}/recommended-events",
+    response_model=UserPreferenceRecommendationResponse,
+)
+def recommend_events(
+    user_id: int,
+    min_hot: int = Query(3, ge=1, description="最小热度阈值"),
+    hours: int = Query(72, ge=1, le=24 * 30, description="仅匹配最近多少小时的事件"),
+    limit: int = Query(20, ge=1, le=50, description="最多返回多少条推荐"),
+    semantic_threshold: float = Query(0.78, ge=0.0, le=1.0, description="语义匹配相似度阈值"),
+    db: Session = Depends(get_db),
+    current_user: AppUser = Depends(get_current_user),
+):
+    """基于用户兴趣词推荐事件（精确匹配 + 语义匹配）。"""
+    _ensure_self_access(user_id, current_user)
+
+    matched = recommend_events_for_user(
+        db,
+        user_id=user_id,
+        min_hot=min_hot,
+        hours=hours,
+        limit=limit,
+        semantic_threshold=semantic_threshold,
+    )
+
+    result_data: list[MatchedEventResponse] = []
+    for item in matched:
+        result_data.append(
+            MatchedEventResponse(
+                event_id=item.event.id,
+                unified_title=item.event.unified_title,
+                summary=item.event.ai_comprehensive_summary,
+                hot_score=item.event.hot_score,
+                created_at=item.event.created_at,
+                tags=item.tags,
+                match_score=item.match_score,
+                exact_hits=item.exact_hits,
+                semantic_hits=item.semantic_hits,
+            )
+        )
+
+    return UserPreferenceRecommendationResponse(
+        user_id=user_id,
+        total=len(result_data),
+        data=result_data,
+    )