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121 lines
4.5 KiB
Markdown
121 lines
4.5 KiB
Markdown
# Tablo
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[Русский](README.md) · **English**
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[](https://github.com/EDeev/tablo/actions/workflows/ci.yml)
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[](https://github.com/EDeev/tablo/actions/workflows/docker.yml)
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[](https://github.com/EDeev/tablo/releases)
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[](LICENSE)
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A web app for students: upload a photo of your timetable, and AI turns it into an editable schedule
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with per-subject progress trackers you can share by link.
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**Status:** personal project that started as coursework (2026) · live at [tablo.deev.su](https://tablo.deev.su)
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**Stack:** Python 3.12 · Flask · SQLAlchemy + Alembic · PostgreSQL · OpenAI-compatible Vision API · Playwright · Jinja2 + vanilla JS
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## Features
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- Timetable recognition from a photo or scan
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- Editing of schedules, subjects and classes; periods may span New Year
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- 11 tracker types (attendance, grades, deadlines, day streaks, etc.) on a drag-and-drop grid
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- Tracker generation from a description such as "8 labs and an exam"
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- Link sharing: view, edit, or copy as a template
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- Merging several schedules into one, with classes of the same subject combined
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- Export to JSON, CSV, PNG and a print-ready version
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## Quick start
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```bash
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git clone https://github.com/EDeev/tablo.git && cd tablo
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cp .env.example .env # set SECRET_KEY and your AI provider key
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docker compose up -d
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```
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Open `http://localhost:8000`. Compose starts the app and PostgreSQL; migrations run on startup.
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Prebuilt image: `docker pull ghcr.io/edeev/tablo` or `docker pull dcr.deev.su/edeev/tablo`.
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## Installing without Docker
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Requires Python 3.11+ and PostgreSQL.
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```bash
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python -m venv .venv && source .venv/bin/activate
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pip install -r requirements.txt
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playwright install --with-deps chromium # for PNG export
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cp .env.example .env
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flask --app run db upgrade
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python run.py
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```
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## Configuration
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| Variable | Purpose |
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|---|---|
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| `SECRET_KEY` | Flask session signing; the app will not start without it |
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| `DATABASE_URL` or `DB_HOST`, `DB_PORT`, `DB_NAME`, `DB_USER`, `DB_PASSWORD` | PostgreSQL connection |
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| `OPENAI_API_KEY` | AI provider key |
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| `OPENAI_BASE_URL` | OpenAI-compatible API URL, if not OpenAI |
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| `OPENAI_MODEL` | model for recognition and trackers, `gpt-4o` by default |
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> [!IMPORTANT]
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> Without `OPENAI_API_KEY`, timetable recognition and tracker generation are disabled. Everything else
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> works: you can create and edit a schedule manually.
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## Screenshots
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| My schedules | Subject and trackers | Phone |
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|---|---|---|
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|  |  |  |
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## How it works
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```mermaid
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flowchart LR
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B[Browser] --> F[Flask: auth · schedules · subjects · shares · export]
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F --> S[Services: ai_scan · ai_metrics · merge · export]
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F --> P[(PostgreSQL)]
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S --> A[OpenAI-compatible API]
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S --> C[Chromium via Playwright]
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```
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Details (in Russian):
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- [docs/architecture.md](docs/architecture.md) — structure, schedule format, trackers, access rules
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- [docs/deploy.md](docs/deploy.md) — Docker and the production setup
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- [docs/explanatory_note.pdf](docs/explanatory_note.pdf) — coursework explanatory note
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## Deployment
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[tablo.deev.su](https://tablo.deev.su) runs on a VPS: gunicorn under systemd behind nginx with a
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Let's Encrypt certificate; PostgreSQL runs on a separate server; AI is Timeweb Cloud AI. GitHub Actions
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builds the Docker image on every `v*` tag and publishes it to GitHub Packages and to `dcr.deev.su`.
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## Development
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```bash
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pip install -r requirements-dev.txt
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export TEST_DATABASE_URL=postgresql://tablo:tablo@localhost:5432/tablo_test
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ruff check . && pytest
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```
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Tests run against a real PostgreSQL: access rules and export, share links, sign-in and open-redirect
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protection, period and time parsing, schedule merging. CI starts the database as a service container
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and runs the same checks on every push.
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## License
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MIT — see [LICENSE](LICENSE).
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## Author
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**Egor Deev** — [GitHub](https://github.com/EDeev) · [Telegram](https://t.me/DeevEgor) · [egor@deev.space](mailto:egor@deev.space)
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---
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<div align="center">
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<sub>⭐ If you find this project useful, give it a star on GitHub!</sub>
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<p><sub>Made with ❤️ — <a href="https://deev.space">deev.space</a></sub></p>
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</div>
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