Document AndyTranscribe setup and transcription engines.
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# AndyTranscribe
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Upload pocket-recorder MP3s, extract ID3 metadata, and transcribe them with OpenAI Whisper, a local faster-whisper server, or a remote OpenAI-compatible endpoint.
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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 MP3s (up to 100 MB) and store them on the local disk
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- Automatic ID3 metadata extraction (title, artist, album, duration, recorded date)
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- Search recordings by title, artist, or transcript
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- Queued transcription with three engines:
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- **Cloud** — OpenAI Whisper (`whisper-1`)
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- **Local** — confidential; OpenAI-compatible [faster-whisper-server](https://github.com/fedirz/faster-whisper-server) (e.g. Docker on this machine)
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- **Ollama host** — user-supplied host URL exposing `/v1/audio/transcriptions`
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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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- For cloud transcription: an OpenAI API key
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- For local transcription: a running faster-whisper-server
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- For remote transcription: a host with an OpenAI-compatible transcription API
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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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## 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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| `OPENAI_API_KEY` | Required for cloud Whisper |
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| `OPENAI_URL` | OpenAI API base URL (default `https://api.openai.com/v1`) |
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| `LOCAL_WHISPER_URL` | Local faster-whisper base URL (default `http://localhost:8000/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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| `REMOTE_WHISPER_MODEL` | Model name for Ollama-host transcription |
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| `TRANSCRIPTION_TIMEOUT` | Job/HTTP timeout in seconds (default `600`) |
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| `QUEUE_CONNECTION` | Use `database` (default) so transcription runs in the background |
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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 the app, queue worker, and Vite together:
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```bash
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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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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** an MP3 from Recordings → Upload (optional title override).
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2. Open the recording and choose a transcription engine.
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3. Wait for the queue job to finish, then refresh to view or copy the transcript.
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4. Search the list by title, artist, or transcript text.
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## Transcription engines
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| Driver | When to use | Needs |
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| --- | --- | --- |
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| `cloud` | Fastest path; audio leaves your machine | `OPENAI_API_KEY` |
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| `local` | Confidential; audio stays on this machine | faster-whisper-server at `LOCAL_WHISPER_URL` |
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| `ollama` | Another machine on your network | Host URL + OpenAI-compatible `/v1/audio/transcriptions` |
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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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