ben
21b17c7657
Drop cloud and Ollama engine choices so audio stays on-machine via Docker Whisper, and tighten orphan detection plus UI around a single local flow.
131 lines
3.6 KiB
Markdown
131 lines
3.6 KiB
Markdown
# AndyTranscribe
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Upload pocket-recorder audio (MP3, WAV, OGG, and more), extract embedded metadata, and transcribe locally with [faster-whisper-server](https://github.com/fedirz/faster-whisper-server) via Docker. Audio never leaves your machine.
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Built with Laravel 13, Blade, Tailwind CSS 4, and [Laravel AI](https://github.com/laravel/ai).
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## Features
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- Upload common audio formats (MP3, WAV, OGG, FLAC, M4A, AAC, WebM, WMA, AIFF — up to 100 MB)
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- Automatic metadata extraction when tags are present (title, artist, album, duration, recorded date)
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- Search recordings by title, artist, or transcript
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- Queued local transcription (faster-whisper in Docker)
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- Live transcription progress (stage, %, elapsed time)
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- Stop or restart a run anytime
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- Copy finished transcripts from the recording detail page
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## Requirements
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- PHP 8.3+ (8.5 recommended)
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- Composer
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- Node.js & npm
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- SQLite (default) or another supported database
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- [Docker](https://docs.docker.com/get-docker/) for the Whisper container
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## Setup
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```bash
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composer setup
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```
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That installs PHP and JS dependencies, copies `.env` if needed, generates the app key, runs migrations, and builds frontend assets.
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Or step by step:
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```bash
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composer install
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cp .env.example .env
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php artisan key:generate
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touch database/database.sqlite # if using SQLite
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php artisan migrate
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npm install
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npm run build
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```
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## Local Whisper (Docker)
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Transcription calls an OpenAI-compatible HTTP API. This project ships Compose for that:
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```bash
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# CPU (works everywhere; slower on long files)
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docker compose up -d whisper
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# Optional: NVIDIA GPU
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docker compose --profile gpu up -d whisper-gpu
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```
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First start downloads the model into a Docker volume (can take a few minutes).
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Check it:
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```bash
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curl -s http://127.0.0.1:8090/health
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```
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Laravel talks to it at `LOCAL_WHISPER_URL` (default `http://127.0.0.1:8090/v1`). Port **8090** is used so it does not conflict with `php artisan serve` on 8000.
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Stop:
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```bash
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docker compose down
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```
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## Configuration
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Copy values from `.env.example`. The transcription-related settings are:
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| Variable | Purpose |
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| --- | --- |
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| `LOCAL_WHISPER_URL` | Local faster-whisper base URL (default `http://127.0.0.1:8090/v1`) |
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| `LOCAL_WHISPER_API_KEY` | API key for local server (often unused) |
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| `LOCAL_WHISPER_MODEL` | Model name for local transcription |
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| `WHISPER_HOST_PORT` | Host port published by Compose (default `8090`) |
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| `TRANSCRIPTION_TIMEOUT` | Job/HTTP timeout in seconds (default `600`) |
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| `DB_QUEUE_RETRY_AFTER` | Database queue retry window; must exceed `TRANSCRIPTION_TIMEOUT` (default `660`) |
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| `QUEUE_CONNECTION` | Use `database` (default) so transcription runs in the background |
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Finished transcripts are stored on the recording (`transcript` column) and are included in the recordings search box (title, artist, album, filename, and transcript).
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Ensure `APP_URL` matches how you access the app (default `http://localhost:8000`).
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## Running locally
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Start Whisper, then the app stack:
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```bash
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docker compose up -d whisper
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composer run dev
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```
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Or separately:
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```bash
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docker compose up -d whisper
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php artisan serve
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php artisan queue:work
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npm run dev
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```
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Open [http://localhost:8000/recordings](http://localhost:8000/recordings).
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Transcription jobs are queued — keep a queue worker running or jobs will stay pending.
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## Usage
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1. **Upload** audio from Recordings → Upload (optional title override).
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2. Open the recording and start transcription.
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3. Watch live progress until the transcript appears (or stop and restart).
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4. Search the list by title, artist, or transcript text.
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## Tests
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```bash
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composer test
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# or
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php artisan test
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```
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## License
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MIT
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