Initial commit

docker-compose.yml

@@ -0,0 +1,74 @@
+version: "3.8"
+
+services:
+  llm-asyncio:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    shm_size: "1000gb"
+    volumes:
+      - ./workspace:/opt/workspace/
+      - ./cache:/root/.cache/
+      - ../model:/opt/model/
+    environment:
+      PYTORCH_CUDA_ALLOC_CONF: expandable_segments:True
+      PYTHONPATH: /opt/workspace/
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: "all"
+              capabilities: [gpu]
+    container_name: llm-asyncio
+    ports:
+      - "8000:8000"
+    networks:
+      - llm-network
+    entrypoint: >
+      /bin/bash -c "
+      uvicorn main:app --reload --host 0.0.0.0 --port 8000
+      "
+    tty: true
+
+  redis:
+    image: redis:latest
+    container_name: redis-server
+    ports:
+      - "6380:6380"
+    restart: always
+    networks:
+      - llm-network
+
+  worker:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    shm_size: "1000gb"
+    volumes:
+      - ./workspace:/opt/workspace/
+      - ./cache:/root/.cache/
+      - ../model:/opt/model/
+    environment:
+      PYTORCH_CUDA_ALLOC_CONF: expandable_segments:True
+      PYTHONPATH: /opt/workspace/
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: "all"
+              capabilities: [gpu]
+    networks:
+      - llm-network
+    entrypoint: >
+      /bin/bash -c "
+      python /opt/workspace/worker.py
+      "
+    restart: always
+    tty: true
+    scale: 2
+
+networks:
+  llm-network:
+    driver: bridge