Create docker-compose.yml

docker-compose.yml

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+# docker-compose.yml
+
+version: '3.8'
+
+services:
+  postgres:
+    image: postgres:15 # Consider timescale/pgvector image if needed: ankane/pgvector
+    container_name: agent_postgres
+    environment:
+      POSTGRES_USER: user
+      POSTGRES_PASSWORD: password
+      POSTGRES_DB: agentdb
+    volumes:
+      - postgres_data:/var/lib/postgresql/data
+    ports:
+      - "5432:5432" # Expose only if needed externally
+    restart: unless-stopped
+    # For pgvector extension (if using ankane/pgvector image or standard postgres + setup):
+    # command: postgres -c shared_preload_libraries='pg_stat_statements,pgvector' # Example
+
+  redis:
+    image: redis:7
+    container_name: agent_redis
+    ports:
+      - "6379:6379" # Expose only if needed externally
+    restart: unless-stopped
+
+  agent-worker:
+    build: . # Assumes Dockerfile is in the current directory
+    container_name: agent_worker
+    depends_on:
+      - postgres
+      - redis
+    environment:
+      # Override or add environment variables here
+      NUM_WORKERS: 4 # Example: Run 4 workers in this container (or scale replicas)
+      PYTHONUNBUFFERED: 1 # Ensure logs appear immediately
+      # Pass GPU capabilities if learning worker runs here (see Docker Compose GPU support docs)
+    # volumes:
+      # Mount code if needed for development: .:/app
+    command: ["python", "your_main_script.py"] # Command to start workers
+    restart: unless-stopped
+
+  # Optional: Separate Learning Worker Service (if GPU resources are specific)
+  # learning-worker:
+  #   build: . # Or a specific Dockerfile for learning
+  #   container_name: learning_worker
+  #   depends_on:
+  #     - postgres
+  #   environment:
+  #     # ... similar env vars ...
+  #     LEARNING_INTERVAL_HOURS: 6
+  #     DEVICE: cuda
+  #   deploy: # Requires Docker Swarm or Kubernetes for GPU allocation
+  #     resources:
+  #       reservations:
+  #         devices:
+  #           - driver: nvidia
+  #             count: 1 # Request 1 GPU
+  #             capabilities: [gpu]
+  #   command: ["python", "your_learning_script.py"] # Command to start scheduler/learning
+  #   restart: unless-stopped
+
+volumes:
+  postgres_data: