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

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

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+# DictIA — Local CPU deployment (WhisperX on CPU + DictIA)
+#
+# Usage:
+#   docker compose -f deployment/docker/docker-compose.local-cpu.yml up -d
+#
+# Warning: CPU transcription is significantly slower than GPU.
+# Expect ~10x real-time for large files (e.g., 1h audio = ~10h processing).
+
+services:
+  whisperx-asr:
+    image: ghcr.io/jim60105/whisperx-asr:latest
+    container_name: whisperx-asr
+    restart: unless-stopped
+    ports:
+      - "9000:9000"
+    environment:
+      - ASR_MODEL=${ASR_MODEL:-large-v3}
+      - ASR_ENGINE=whisperx
+      - DEVICE=cpu
+      - COMPUTE_TYPE=float32
+      - HF_TOKEN=${HF_TOKEN:-}
+    volumes:
+      - whisperx-cache:/root/.cache
+    deploy:
+      resources:
+        limits:
+          memory: 18G
+    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