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>
77 lines
2.1 KiB
Python
77 lines
2.1 KiB
Python
from logging.config import fileConfig
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from sqlalchemy import engine_from_config
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from sqlalchemy import pool
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from alembic import context
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# this is the Alembic Config object, which provides
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# access to the values within the .ini file in use.
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config = context.config
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# Interpret the config file for Python logging.
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# This line sets up loggers basically.
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if config.config_file_name is not None:
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fileConfig(config.config_file_name)
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from app.models import User, PDFDocument, Section, Quiz, Question, QuizAttempt, AttemptAnswer, ReminderSchedule # noqa
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from app.database import Base
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target_metadata = Base.metadata
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# other values from the config, defined by the needs of env.py,
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# can be acquired:
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# my_important_option = config.get_main_option("my_important_option")
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# ... etc.
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def run_migrations_offline() -> None:
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"""Run migrations in 'offline' mode.
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This configures the context with just a URL
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and not an Engine, though an Engine is acceptable
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here as well. By skipping the Engine creation
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we don't even need a DBAPI to be available.
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Calls to context.execute() here emit the given string to the
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script output.
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"""
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url = config.get_main_option("sqlalchemy.url")
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context.configure(
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url=url,
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target_metadata=target_metadata,
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literal_binds=True,
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dialect_opts={"paramstyle": "named"},
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)
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with context.begin_transaction():
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context.run_migrations()
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def run_migrations_online() -> None:
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"""Run migrations in 'online' mode.
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In this scenario we need to create an Engine
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and associate a connection with the context.
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"""
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connectable = engine_from_config(
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config.get_section(config.config_ini_section, {}),
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prefix="sqlalchemy.",
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poolclass=pool.NullPool,
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)
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with connectable.connect() as connection:
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context.configure(
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connection=connection, target_metadata=target_metadata
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)
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with context.begin_transaction():
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context.run_migrations()
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if context.is_offline_mode():
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run_migrations_offline()
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else:
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run_migrations_online()
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