2e8c2c11d0
Vocabulary study with FSRS spaced repetition, AI tutoring (Ollama/Claude), essay marking, idioms browser, Anki export, and dashboard. 918 vocabulary entries across 39 categories. 41 tests passing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
39 lines
1.3 KiB
Markdown
39 lines
1.3 KiB
Markdown
# Persian Language Tutor
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## Overview
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Gradio-based Persian (Farsi) language learning app for English speakers, using GCSE Persian vocabulary (Pearson spec) as seed data.
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## Tech Stack
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- **Frontend**: Gradio (browser handles RTL natively)
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- **Spaced repetition**: py-fsrs (same algorithm as Anki)
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- **AI**: Ollama (fast, local) + Claude CLI (smart, subprocess)
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- **STT**: faster-whisper via sttlib from tool-speechtotext
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- **Anki export**: genanki for .apkg generation
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- **Database**: SQLite (file-based, data/progress.db)
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- **Environment**: `whisper-ollama` conda env
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## Running
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```bash
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mamba run -n whisper-ollama python app.py
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```
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## Testing
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```bash
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mamba run -n whisper-ollama python -m pytest tests/
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```
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## Key Paths
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- `data/vocabulary.json` — GCSE vocabulary data
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- `data/progress.db` — SQLite database (auto-created)
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- `app.py` — Gradio entry point
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- `db.py` — Database layer with FSRS integration
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- `ai.py` — Dual AI backend (Ollama + Claude)
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- `stt.py` — Persian speech-to-text wrapper
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- `modules/` — Feature modules (vocab, dashboard, essay, tutor, idioms)
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## Architecture
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- Single-process Gradio app with shared SQLite connection
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- FSRS Card objects serialized as JSON in SQLite TEXT columns
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- Timestamps stored as ISO-8601 strings
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- sttlib imported via sys.path from tool-speechtotext project
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