Use local faster-whisper only for transcription.

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.

README.md

@@ -1,6 +1,6 @@
 # AndyTranscribe
 
-Upload pocket-recorder audio (MP3, WAV, OGG, and more), extract embedded metadata, and transcribe with OpenAI Whisper, a local faster-whisper server, or a remote OpenAI-compatible endpoint.
+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.
 
 Built with Laravel 13, Blade, Tailwind CSS 4, and [Laravel AI](https://github.com/laravel/ai).
 
@@ -9,11 +9,9 @@ Built with Laravel 13, Blade, Tailwind CSS 4, and [Laravel AI](https://github.co
 - Upload common audio formats (MP3, WAV, OGG, FLAC, M4A, AAC, WebM, WMA, AIFF — up to 100 MB)
 - Automatic metadata extraction when tags are present (title, artist, album, duration, recorded date)
 - Search recordings by title, artist, or transcript
-- Queued transcription with three engines:
-  - **Cloud** — OpenAI Whisper (`whisper-1`)
-  - **Local** — confidential; OpenAI-compatible [faster-whisper-server](https://github.com/fedirz/faster-whisper-server) via Docker
-  - **Ollama host** — user-supplied host URL exposing `/v1/audio/transcriptions`
+- Queued local transcription (faster-whisper in Docker)
 - Live transcription progress (stage, %, elapsed time)
+- Stop or restart a run anytime
 - Copy finished transcripts from the recording detail page
 
 ## Requirements
@@ -22,9 +20,7 @@ Built with Laravel 13, Blade, Tailwind CSS 4, and [Laravel AI](https://github.co
 - Composer
 - Node.js & npm
 - SQLite (default) or another supported database
-- For **cloud** transcription: an OpenAI API key
-- For **local** transcription: [Docker](https://docs.docker.com/get-docker/) (runs Whisper in a container)
-- For **remote** transcription: a host with an OpenAI-compatible transcription API
+- [Docker](https://docs.docker.com/get-docker/) for the Whisper container
 
 ## Setup
 
@@ -48,7 +44,7 @@ npm run build
 
 ## Local Whisper (Docker)
 
-The **Local** engine does not run Whisper inside PHP. It calls an OpenAI-compatible HTTP API. This project ships Compose for that:
+Transcription calls an OpenAI-compatible HTTP API. This project ships Compose for that:
 
 ```bash
 # CPU (works everywhere; slower on long files)
@@ -74,20 +70,15 @@ Stop:
 docker compose down
 ```
 
-Without this container, **Cloud** and **Ollama host** still work; only **Local** needs Docker.
-
 ## Configuration
 
 Copy values from `.env.example`. The transcription-related settings are:
 
 | Variable | Purpose |
 | --- | --- |
-| `OPENAI_API_KEY` | Required for cloud Whisper |
-| `OPENAI_URL` | OpenAI API base URL (default `https://api.openai.com/v1`) |
 | `LOCAL_WHISPER_URL` | Local faster-whisper base URL (default `http://127.0.0.1:8090/v1`) |
 | `LOCAL_WHISPER_API_KEY` | API key for local server (often unused) |
 | `LOCAL_WHISPER_MODEL` | Model name for local transcription |
-| `REMOTE_WHISPER_MODEL` | Model name for Ollama-host transcription |
 | `WHISPER_HOST_PORT` | Host port published by Compose (default `8090`) |
 | `TRANSCRIPTION_TIMEOUT` | Job/HTTP timeout in seconds (default `600`) |
 | `DB_QUEUE_RETRY_AFTER` | Database queue retry window; must exceed `TRANSCRIPTION_TIMEOUT` (default `660`) |
@@ -99,21 +90,17 @@ Ensure `APP_URL` matches how you access the app (default `http://localhost:8000`
 
 ## Running locally
 
-Start the app, queue worker, and Vite together:
-
-```bash
-composer run dev
-```
-
-For confidential local transcription, also start Whisper:
+Start Whisper, then the app stack:
 
 ```bash
 docker compose up -d whisper
+composer run dev
 ```
 
 Or separately:
 
 ```bash
+docker compose up -d whisper
 php artisan serve
 php artisan queue:work
 npm run dev
@@ -126,18 +113,10 @@ Transcription jobs are queued — keep a queue worker running or jobs will stay
 ## Usage
 
 1. **Upload** audio from Recordings → Upload (optional title override).
-2. Open the recording and choose a transcription engine.
-3. Watch live progress on the recording page until the transcript appears.
+2. Open the recording and start transcription.
+3. Watch live progress until the transcript appears (or stop and restart).
 4. Search the list by title, artist, or transcript text.
 
-## Transcription engines
-
-| Driver | When to use | Needs |
-| --- | --- | --- |
-| `cloud` | Fastest path; audio leaves your machine | `OPENAI_API_KEY` |
-| `local` | Confidential; audio stays on this machine | `docker compose up -d whisper` |
-| `ollama` | Another machine on your network | Host URL + OpenAI-compatible `/v1/audio/transcriptions` |
-
 ## Tests
 
 ```bash