移动端拍照上传、奥数区、学段约束解题与 AI 模型配置。

- 手机/平板响应式布局，支持拍照与相册上传

- 学生详情新增奥数区，按初/高中学段生成解法并禁止超纲

- 系统设置可配置 Ollama 或 OpenAI 兼容 API

- 更新 frontend/dist 与使用说明

backend/app/routers/wrong_questions.py

@@ -8,10 +8,10 @@ from sqlalchemy.orm import Session, joinedload
 from app.core.config import settings
 from app.core.database import SessionLocal, get_db
 from app.core.deps import get_current_user
-from app.models.user import Subject, User, WrongQuestion, WrongQuestionStatus
-from app.schemas import WrongQuestionOut, WrongQuestionUpdate
+from app.models.user import Subject, User, WrongQuestion, WrongQuestionCategory, WrongQuestionStatus
+from app.schemas import WrongQuestionCategoryEnum, WrongQuestionOut, WrongQuestionUpdate
+from app.services import llm as llm_service
 from app.services import ocr as ocr_service
-from app.services import ollama as ollama_service
 from app.services.student_access import get_student_for_user
 
 router = APIRouter(tags=["wrong_questions"])
@@ -23,6 +23,7 @@ def _wq_to_out(wq: WrongQuestion) -> WrongQuestionOut:
         student_id=wq.student_id,
         subject_id=wq.subject_id,
         subject_name=wq.subject.name if wq.subject else None,
+        category=wq.category,
         image_path=wq.image_path,
         ocr_raw_text=wq.ocr_raw_text,
         question_text=wq.question_text,
@@ -60,16 +61,25 @@ def _process_wrong_question(question_id: uuid.UUID):
 
         subject_name = wq.subject.name if wq.subject else "综合"
         school_level = wq.student.school_level if wq.student else None
+        olympiad = wq.category == WrongQuestionCategory.olympiad
+        ai_cfg = llm_service.load_ai_config(db)
+
         import asyncio
 
         loop = asyncio.new_event_loop()
         asyncio.set_event_loop(loop)
         try:
             question_text = loop.run_until_complete(
-                ollama_service.format_question(subject_name, ocr_text, school_level)
+                llm_service.format_question(ai_cfg, subject_name, ocr_text, school_level)
             )
             solution_text = loop.run_until_complete(
-                ollama_service.generate_solution(subject_name, question_text, school_level)
+                llm_service.generate_solution(
+                    ai_cfg,
+                    subject_name,
+                    question_text,
+                    school_level,
+                    olympiad=olympiad,
+                )
             )
             wq.question_text = question_text
             wq.solution_text = solution_text
@@ -88,6 +98,7 @@ def _process_wrong_question(question_id: uuid.UUID):
 def list_wrong_questions(
     student_id: uuid.UUID,
     subject_id: int | None = Query(None),
+    category: WrongQuestionCategoryEnum | None = Query(None),
     q: str | None = Query(None),
     db: Session = Depends(get_db),
     current_user: User = Depends(get_current_user),
@@ -100,6 +111,8 @@ def list_wrong_questions(
     )
     if subject_id is not None:
         query = query.filter(WrongQuestion.subject_id == subject_id)
+    if category is not None:
+        query = query.filter(WrongQuestion.category == category.value)
     if q:
         pattern = f"%{q}%"
         query = query.filter(
@@ -121,6 +134,7 @@ async def upload_wrong_question(
     background_tasks: BackgroundTasks,
     subject_id: int = Form(...),
     file: UploadFile = File(...),
+    category: WrongQuestionCategoryEnum = Form(WrongQuestionCategoryEnum.regular),
     db: Session = Depends(get_db),
     current_user: User = Depends(get_current_user),
 ):
@@ -137,6 +151,7 @@ async def upload_wrong_question(
         student_id=student_id,
         subject_id=subject_id,
         image_path="",
+        category=WrongQuestionCategory(category.value),
         status=WrongQuestionStatus.pending,
     )
     db.add(wq)
@@ -270,21 +285,27 @@ async def regenerate_solution(
 
     subject_name = wq.subject.name if wq.subject else "综合"
     school_level = wq.student.school_level if wq.student else None
+    olympiad = wq.category == WrongQuestionCategory.olympiad
     question_text = wq.question_text or wq.ocr_raw_text or ""
+    ai_cfg = llm_service.load_ai_config(db)
 
     try:
         if not wq.question_text and wq.ocr_raw_text:
-            wq.question_text = await ollama_service.format_question(
-                subject_name, wq.ocr_raw_text, school_level
+            wq.question_text = await llm_service.format_question(
+                ai_cfg, subject_name, wq.ocr_raw_text, school_level
             )
             question_text = wq.question_text
-        wq.solution_text = await ollama_service.generate_solution(
-            subject_name, question_text, school_level
+        wq.solution_text = await llm_service.generate_solution(
+            ai_cfg,
+            subject_name,
+            question_text,
+            school_level,
+            olympiad=olympiad,
         )
         wq.status = WrongQuestionStatus.solved
     except Exception as exc:
         raise HTTPException(
-            status_code=status.HTTP_502_BAD_GATEWAY, detail=f"Ollama 调用失败: {exc}"
+            status_code=status.HTTP_502_BAD_GATEWAY, detail=f"AI 调用失败: {exc}"
         ) from exc
 
     db.commit()