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>
26 lines
635 B
Mako
26 lines
635 B
Mako
"""${message}
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Revision ID: ${up_revision}
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Revises: ${down_revision | comma,n}
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Create Date: ${create_date}
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"""
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from typing import Sequence, Union
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from alembic import op
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import sqlalchemy as sa
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${imports if imports else ""}
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# revision identifiers, used by Alembic.
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revision: str = ${repr(up_revision)}
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down_revision: Union[str, None] = ${repr(down_revision)}
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branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
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depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
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def upgrade() -> None:
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${upgrades if upgrades else "pass"}
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def downgrade() -> None:
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${downgrades if downgrades else "pass"}
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