Aleksey Razorvin
9a0b3ba92c
- Страница /settings: ввод и проверка API ключа DeepSeek - POST /api/llm/generate — генерация вопросов по названию теста - POST /api/llm/improve — улучшение формулировки вопроса + ответов (модал с галочками) - POST /api/llm/distractors — генерация дистракторов - POST /api/llm/review — рецензия теста + кнопка «Предложить вариант» - POST /api/llm/improve_all — улучшение всего теста с постатейным сравнением - Миграция 004: таблица settings (key-value) - Шапка приложения с навигацией на /settings Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
130 lines
3.9 KiB
Python
130 lines
3.9 KiB
Python
from fastapi import APIRouter, Depends, HTTPException
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from pydantic import BaseModel
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.database import get_db
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from app.services import llm as llm_service
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router = APIRouter(tags=["llm"])
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class CheckResponse(BaseModel):
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ok: bool
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message: str
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class GenerateRequest(BaseModel):
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topic: str
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count: int = 7
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class GenerateResponse(BaseModel):
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questions: list[dict]
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class ImproveRequest(BaseModel):
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question: str
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answers: list[str]
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class ImproveResponse(BaseModel):
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improved_question: str
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improved_answers: list[str]
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class DistractorsRequest(BaseModel):
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question: str
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answers: list[str]
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class DistractorsResponse(BaseModel):
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distractors: list[str]
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class ReviewRequest(BaseModel):
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title: str
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questions: list[dict]
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class ReviewResponse(BaseModel):
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review: str
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class ImproveAllRequest(BaseModel):
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title: str
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questions: list[dict]
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class ImproveAllResponse(BaseModel):
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questions: list[dict]
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@router.post("/api/llm/check", response_model=CheckResponse)
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async def check_connection(db: AsyncSession = Depends(get_db)):
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try:
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result = await llm_service.check_connection(db)
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return {"ok": True, "message": f"Подключение успешно: {result}"}
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except ValueError as e:
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return {"ok": False, "message": str(e)}
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except Exception as e:
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return {"ok": False, "message": f"Ошибка подключения: {str(e)}"}
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@router.post("/api/llm/generate", response_model=GenerateResponse)
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async def generate_questions(req: GenerateRequest, db: AsyncSession = Depends(get_db)):
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try:
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questions = await llm_service.generate_questions(db, req.topic, req.count)
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return {"questions": questions}
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Ошибка AI: {str(e)}")
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@router.post("/api/llm/improve", response_model=ImproveResponse)
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async def improve_question(req: ImproveRequest, db: AsyncSession = Depends(get_db)):
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try:
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data = await llm_service.improve_question(db, req.question, req.answers)
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return {"improved_question": data["question"], "improved_answers": data["answers"]}
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Ошибка AI: {str(e)}")
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@router.post("/api/llm/distractors", response_model=DistractorsResponse)
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async def generate_distractors(
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req: DistractorsRequest, db: AsyncSession = Depends(get_db)
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):
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try:
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distractors = await llm_service.generate_distractors(
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db, req.question, req.answers
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)
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return {"distractors": distractors}
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Ошибка AI: {str(e)}")
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@router.post("/api/llm/review", response_model=ReviewResponse)
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async def review_test(req: ReviewRequest, db: AsyncSession = Depends(get_db)):
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try:
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review = await llm_service.review_test(db, req.title, req.questions)
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return {"review": review}
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Ошибка AI: {str(e)}")
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@router.post("/api/llm/improve_all", response_model=ImproveAllResponse)
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async def improve_all(req: ImproveAllRequest, db: AsyncSession = Depends(get_db)):
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try:
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questions = await llm_service.improve_all(db, req.title, req.questions)
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return {"questions": questions}
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Ошибка AI: {str(e)}")
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