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>
54 lines
1.1 KiB
Python
54 lines
1.1 KiB
Python
from datetime import datetime
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from pydantic import BaseModel
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class QuizCreate(BaseModel):
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section_id: int
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title: str
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mode: str = "timed" # timed, learning
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time_limit_minutes: int | None = None
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class QuestionResponse(BaseModel):
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id: int
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question_text: str
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question_type: str
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options: list[str] | None
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image_path: str | None = None
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class Config:
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from_attributes = True
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class QuestionWithAnswer(QuestionResponse):
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correct_answer: str
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explanation: str | None
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page_reference: int | None
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class QuizResponse(BaseModel):
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id: int
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section_id: int
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user_id: int
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title: str
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questions_count: int
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mode: str
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time_limit_minutes: int | None
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created_at: datetime
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class Config:
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from_attributes = True
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class QuizDetail(QuizResponse):
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questions: list[QuestionResponse] = []
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class QuizLearningDetail(QuizResponse):
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"""Learning mode — includes answers and explanations."""
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questions: list[QuestionWithAnswer] = []
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class QuizReview(QuizResponse):
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questions: list[QuestionWithAnswer] = []
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