Add production deployment infrastructure

.github/workflows/deploy.yml

@@ -0,0 +1,92 @@
+name: Deploy ASI Application
+
+on:
+  push:
+    branches:
+      - main
+      - master
+  pull_request:
+    branches:
+      - main
+      - master
+  workflow_dispatch:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.11'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+
+    - name: Verify Python files syntax
+      run: |
+        python -m py_compile asi.py
+        python -m py_compile aeon.py
+
+    - name: Run basic import test
+      run: |
+        python -c "import asi; import aeon; print('Imports successful')"
+
+  build-docker:
+    runs-on: ubuntu-latest
+    needs: test
+    permissions:
+      contents: read
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+
+    - name: Set up Docker Buildx
+      uses: docker/setup-buildx-action@v3
+
+    - name: Build Docker image
+      run: |
+        docker build -t asi-app:latest .
+
+    - name: Test Docker image
+      run: |
+        docker run --rm asi-app:latest python -c "import asi; print('Docker image works')"
+
+    - name: Save Docker image
+      if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/master'
+      run: |
+        docker save asi-app:latest | gzip > asi-app.tar.gz
+
+    - name: Upload Docker image artifact
+      if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/master'
+      uses: actions/upload-artifact@v4
+      with:
+        name: asi-docker-image
+        path: asi-app.tar.gz
+        retention-days: 7
+
+  deploy:
+    runs-on: ubuntu-latest
+    needs: build-docker
+    if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/master'
+    permissions:
+      contents: read
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+
+    - name: Deployment ready
+      run: |
+        echo "Application is ready for deployment"
+        echo "Docker image has been built and tested successfully"
+        echo "Use docker-compose up -d to deploy locally"

.gitignore

@@ -0,0 +1,57 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual environments
+venv/
+ENV/
+env/
+.venv
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+.DS_Store
+
+# Data and memory files
+genesis_memory.pkl
+data/
+*.pkl
+
+# Docker
+.dockerignore
+
+# Logs
+*.log
+
+# Testing
+.pytest_cache/
+.coverage
+htmlcov/
+
+# OS
+Thumbs.db

DEPLOYMENT.md

@@ -0,0 +1,205 @@
+# ASI Application Deployment Guide
+
+This guide provides instructions for deploying the ASI (Artificial Super Intelligence) application.
+
+## Prerequisites
+
+- Docker and Docker Compose installed
+- Python 3.11 or higher (for local development)
+- Git
+
+## Quick Start with Docker
+
+### 1. Build and Run with Docker Compose
+
+The easiest way to deploy is using Docker Compose:
+
+```bash
+# Clone the repository
+git clone https://github.com/DOUGLASDAVIS08161978/asi.git
+cd asi
+
+# Build and start the application
+docker-compose up -d
+
+# View logs
+docker-compose logs -f
+
+# Stop the application
+docker-compose down
+```
+
+### 2. Build and Run with Docker
+
+Alternatively, you can use Docker directly:
+
+```bash
+# Build the image
+docker build -t asi-app:latest .
+
+# Run the container
+docker run -d \
+  --name asi-app \
+  -v $(pwd)/data:/app/data \
+  asi-app:latest
+
+# View logs
+docker logs -f asi-app
+
+# Stop the container
+docker stop asi-app
+docker rm asi-app
+```
+
+## Local Development Deployment
+
+### 1. Set up Python environment
+
+```bash
+# Create virtual environment
+python3 -m venv venv
+
+# Activate virtual environment
+source venv/bin/activate  # On Linux/Mac
+# or
+venv\Scripts\activate  # On Windows
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+### 2. Run the application
+
+```bash
+# Run the main ASI script
+python asi.py
+
+# Or run AEON script
+python aeon.py
+```
+
+## CI/CD Pipeline
+
+The repository includes a GitHub Actions workflow that:
+
+1. **Tests** - Validates Python syntax and imports
+2. **Builds** - Creates Docker image
+3. **Deploys** - Prepares artifacts for deployment
+
+The workflow runs automatically on:
+- Push to main/master branch
+- Pull requests to main/master branch
+- Manual trigger via workflow_dispatch
+
+## Environment Variables
+
+- `PYTHONUNBUFFERED=1` - Ensures Python output is not buffered
+- `GENESIS_MEMORY_PATH=/app/data/genesis_memory.pkl` - Path for persistent memory storage
+
+## Data Persistence
+
+The application stores persistent memory in a pickle file. When using Docker:
+- Data is stored in `./data` directory on the host
+- This directory is mounted to `/app/data` in the container
+- Memory persists across container restarts
+
+## Deployment Options
+
+### Option 1: Local Docker
+Use Docker Compose for local deployment (recommended for development and testing).
+
+### Option 2: Cloud Deployment
+
+#### AWS
+- Use AWS ECS or EKS to deploy the Docker container
+- Store data in EFS or S3
+
+#### Google Cloud
+- Use Google Cloud Run or GKE
+- Store data in Cloud Storage or Persistent Disks
+
+#### Azure
+- Use Azure Container Instances or AKS
+- Store data in Azure Blob Storage or Azure Files
+
+#### DigitalOcean
+- Use DigitalOcean App Platform or Kubernetes
+- Store data in Spaces or Volume storage
+
+### Option 3: VPS Deployment
+Deploy to any VPS (DigitalOcean, Linode, etc.):
+
+```bash
+# SSH into your server
+ssh user@your-server
+
+# Install Docker and Docker Compose
+curl -fsSL https://get.docker.com -o get-docker.sh
+sh get-docker.sh
+sudo curl -L "https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
+sudo chmod +x /usr/local/bin/docker-compose
+
+# Clone and deploy
+git clone https://github.com/DOUGLASDAVIS08161978/asi.git
+cd asi
+docker-compose up -d
+```
+
+## Monitoring
+
+### View Application Logs
+
+```bash
+# Docker Compose
+docker-compose logs -f
+
+# Docker
+docker logs -f asi-app
+```
+
+### Check Container Status
+
+```bash
+# Docker Compose
+docker-compose ps
+
+# Docker
+docker ps
+```
+
+## Troubleshooting
+
+### Container won't start
+- Check logs: `docker-compose logs`
+- Verify dependencies: `pip install -r requirements.txt`
+- Check disk space: `df -h`
+
+### Memory persistence issues
+- Ensure `./data` directory exists and is writable
+- Check volume mounts: `docker inspect asi-app`
+
+### Python errors
+- Verify Python version: `python --version` (should be 3.11+)
+- Reinstall dependencies: `pip install --upgrade -r requirements.txt`
+
+## Security Considerations
+
+1. **Data Protection** - Ensure the data directory has appropriate permissions
+2. **Network Security** - Use firewalls to restrict access if deploying publicly
+3. **Updates** - Regularly update dependencies and base Docker images
+
+## Scaling
+
+For production deployments:
+1. Use orchestration tools like Kubernetes
+2. Implement health checks
+3. Set up monitoring and alerting
+4. Use external data stores (databases, object storage)
+5. Implement logging aggregation
+
+## Support
+
+For issues or questions:
+- Open an issue on GitHub
+- Check existing documentation
+- Review logs for error messages

Dockerfile

@@ -0,0 +1,24 @@
+# Use Python 3.11 slim image as base
+FROM python:3.11-slim
+
+# Set working directory
+WORKDIR /app
+
+# Copy requirements first for better caching
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application files
+COPY *.py ./
+
+# Create directory for persistent memory
+RUN mkdir -p /app/data
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV GENESIS_MEMORY_PATH=/app/data/genesis_memory.pkl
+
+# Default command - run the main ASI script
+CMD ["python", "asi.py"]