Add live transcription progress and Docker Whisper.

Surface stage, percent, and elapsed time while jobs run, and ship Compose so local confidential transcription can use faster-whisper on port 8090.

docker-compose.yml

@@ -0,0 +1,43 @@
+services:
+  whisper:
+    image: fedirz/faster-whisper-server:latest-cpu
+    container_name: andytranscribe-whisper
+    ports:
+      # Host 8090 avoids clashing with `php artisan serve` on 8000
+      - "${WHISPER_HOST_PORT:-8090}:8000"
+    volumes:
+      - whisper-huggingface-cache:/root/.cache/huggingface
+    environment:
+      # OpenAI-compatible API; model is also passed per request from Laravel
+      WHISPER__MODEL: ${LOCAL_WHISPER_MODEL:-Systran/faster-whisper-base}
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health')"]
+      interval: 15s
+      timeout: 5s
+      retries: 10
+      start_period: 30s
+
+  # GPU variant (NVIDIA). Start with:
+  #   docker compose --profile gpu up -d whisper-gpu
+  whisper-gpu:
+    profiles: ["gpu"]
+    image: fedirz/faster-whisper-server:latest-cuda
+    container_name: andytranscribe-whisper-gpu
+    ports:
+      - "${WHISPER_HOST_PORT:-8090}:8000"
+    volumes:
+      - whisper-huggingface-cache:/root/.cache/huggingface
+    environment:
+      WHISPER__MODEL: ${LOCAL_WHISPER_MODEL:-Systran/faster-whisper-base}
+    restart: unless-stopped
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+volumes:
+  whisper-huggingface-cache: