Initial release: DictIA v0.8.14-alpha (fork de Speakr, AGPL-3.0)

deployment/docker/docker-compose.local-gpu.yml

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+# DictIA — Local GPU deployment (WhisperX on NVIDIA GPU + DictIA)
+#
+# Usage:
+#   docker compose -f deployment/docker/docker-compose.local-gpu.yml up -d
+#
+# Prerequisites:
+#   - NVIDIA GPU with CUDA support
+#   - nvidia-container-toolkit installed
+#   - Docker configured with nvidia runtime
+
+services:
+  whisperx-asr:
+    image: ghcr.io/jim60105/whisperx-asr:latest-cuda
+    container_name: whisperx-asr
+    restart: unless-stopped
+    ports:
+      - "9000:9000"
+    environment:
+      - ASR_MODEL=${ASR_MODEL:-large-v3}
+      - ASR_ENGINE=whisperx
+      - DEVICE=cuda
+      - COMPUTE_TYPE=float16
+      - HF_TOKEN=${HF_TOKEN:-}
+    volumes:
+      - whisperx-cache:/root/.cache
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    networks:
+      - dictia-network
+
+  dictia:
+    build:
+      context: ../..
+      dockerfile: Dockerfile
+    image: innova-ai/dictia:latest
+    container_name: dictia
+    restart: unless-stopped
+    ports:
+      - "8899:8899"
+    env_file:
+      - ../../.env
+    environment:
+      - LOG_LEVEL=${LOG_LEVEL:-ERROR}
+      - ASR_BASE_URL=http://whisperx-asr:9000
+    volumes:
+      - ../../data/uploads:/data/uploads
+      - ../../data/instance:/data/instance
+    depends_on:
+      - whisperx-asr
+    healthcheck:
+      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8899/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 30s
+    networks:
+      - dictia-network
+
+volumes:
+  whisperx-cache:
+
+networks:
+  dictia-network:
+    driver: bridge