b876f13fac
- FastAPI backend with JWT auth, roles (admin/moderator/user) - PDF upload (up to 500MB) with streaming, PyMuPDF text extraction - ChromaDB vectorization per page with metadata - LiteLLM AI question extraction from PDF (not generation) - Image extraction from PDF pages, graceful fallback - Quiz modes: timed (countdown timer) + learning (answers shown inline) - Page-by-page question navigation with dot navigator - TTS endpoint using LiteLLM (Google Vertex / OpenAI voices) - Admin dashboard: AI model management per task, user role management - Moderator role: upload PDFs, create sections, generate quizzes - Spaced repetition reminders via SMTP email (SM-2 intervals) - APScheduler daily reminder jobs - Celery + Redis for background PDF processing - React frontend with all pages - Docker Compose deployment (nginx + backend + celery + redis) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
24 lines
1 KiB
Python
24 lines
1 KiB
Python
from datetime import datetime
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from sqlalchemy import Column, Integer, String, DateTime, ForeignKey
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from sqlalchemy.orm import relationship
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from app.database import Base
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class Quiz(Base):
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__tablename__ = "quizzes"
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id = Column(Integer, primary_key=True, index=True)
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section_id = Column(Integer, ForeignKey("sections.id"), nullable=False)
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user_id = Column(Integer, ForeignKey("users.id"), nullable=False)
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title = Column(String, nullable=False)
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questions_count = Column(Integer, default=0)
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time_limit_minutes = Column(Integer, nullable=True) # null = no limit
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mode = Column(String, default="timed") # timed, learning
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created_at = Column(DateTime, default=datetime.utcnow)
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section = relationship("Section", back_populates="quizzes")
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user = relationship("User", back_populates="quizzes")
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questions = relationship("Question", back_populates="quiz", cascade="all, delete-orphan")
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attempts = relationship("QuizAttempt", back_populates="quiz", cascade="all, delete-orphan")
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