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blackroad-operating-system/backend
2025-11-17 23:38:17 -06:00
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2025-11-16 03:48:34 -06:00

BlackRoad Operating System - Backend API

A comprehensive FastAPI backend for the BlackRoad Operating System, a Windows 95-inspired web operating system with modern features.

Features

Core Services

  • Authentication - JWT-based user authentication and authorization
  • RoadMail - Full-featured email system with folders and attachments
  • BlackRoad Social - Social media platform with posts, comments, likes, and follows
  • BlackStream - Video streaming service with views and engagement tracking
  • File Storage - File explorer with folder management and sharing
  • RoadCoin Blockchain - Cryptocurrency with mining, transactions, and wallet management
  • AI Chat - Conversational AI assistant with conversation history
  • Chaos Inbox / Identity / Notifications / Creator / Compliance - New v0.2 APIs for capture, profiles, alerts, creative projects, and audit visibility

New v0.2 endpoints

  • /api/capture/* — capture items, clustering, status and tagging
  • /api/identity/profile — canonical user profile for OS apps
  • /api/notifications — create/list/mark notifications
  • /api/creator/projects — manage creator projects and assets
  • /api/compliance/events — surface audit events
  • /api/search?q= — unified search scaffold

Technology Stack

  • FastAPI - Modern, fast Python web framework
  • PostgreSQL - Primary database with async support
  • Redis - Caching and session storage
  • SQLAlchemy - ORM with async support
  • JWT - Secure authentication
  • Docker - Containerization and deployment

Quick Start

The desktop UI is bundled in backend/static/index.html and is served by the FastAPI app at http://localhost:8000/.

Prerequisites

  • Python 3.11+
  • Docker and Docker Compose
  • PostgreSQL 15+ (if running locally)
  • Redis 7+ (if running locally)

Installation

# Clone the repository
cd backend

# Copy environment file
cp .env.example .env

# Edit .env with your configuration
nano .env

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f backend

The API will be available at:

Option 2: Local Development

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Copy environment file
cp .env.example .env

# Edit .env with your configuration
nano .env

# Start PostgreSQL and Redis (using Docker)
docker run -d -p 5432:5432 -e POSTGRES_USER=blackroad -e POSTGRES_PASSWORD=password -e POSTGRES_DB=blackroad_db postgres:15-alpine
docker run -d -p 6379:6379 redis:7-alpine

# Run the application (serves backend/static/index.html at /)
# Run the application (PORT defaults to 8000 if unset)
python run.py

After either setup option finishes booting, browse to http://localhost:8000/ to load the Windows 95 desktop that lives in backend/static/index.html. The API is available at /api/* from the same server, so no extra reverse proxying is required for local or hosted (Railway, GoDaddy, etc.) deployments.

Configuration

Edit the .env file to configure:

# Database
DATABASE_URL=postgresql://blackroad:password@localhost:5432/blackroad_db
DATABASE_ASYNC_URL=postgresql+asyncpg://blackroad:password@localhost:5432/blackroad_db

# Redis
REDIS_URL=redis://localhost:6379/0

# JWT Secret (CHANGE THIS!)
SECRET_KEY=your-very-secret-key-change-this-in-production

# CORS (Add your frontend URLs)
ALLOWED_ORIGINS=http://localhost:3000,https://yourdomain.com

# OpenAI (for AI Chat)
OPENAI_API_KEY=your-openai-api-key

API Documentation

Authentication Endpoints

POST /api/auth/register
POST /api/auth/login
GET  /api/auth/me
POST /api/auth/logout

Email (RoadMail) Endpoints

GET    /api/email/folders
GET    /api/email/inbox
GET    /api/email/sent
POST   /api/email/send
GET    /api/email/{email_id}
DELETE /api/email/{email_id}

Social Media Endpoints

GET  /api/social/feed
POST /api/social/posts
POST /api/social/posts/{post_id}/like
GET  /api/social/posts/{post_id}/comments
POST /api/social/posts/{post_id}/comments
POST /api/social/users/{user_id}/follow

Video Streaming Endpoints

GET  /api/videos
POST /api/videos
GET  /api/videos/{video_id}
POST /api/videos/{video_id}/like

File Storage Endpoints

GET    /api/files/folders
POST   /api/files/folders
GET    /api/files
POST   /api/files/upload
GET    /api/files/{file_id}
DELETE /api/files/{file_id}
POST   /api/files/{file_id}/share

Blockchain Endpoints

GET  /api/blockchain/wallet
GET  /api/blockchain/balance
POST /api/blockchain/transactions
GET  /api/blockchain/transactions
GET  /api/blockchain/transactions/{tx_hash}
GET  /api/blockchain/blocks
GET  /api/blockchain/blocks/{block_id}
POST /api/blockchain/mine
GET  /api/blockchain/stats

AI Chat Endpoints

GET    /api/ai-chat/conversations
POST   /api/ai-chat/conversations
GET    /api/ai-chat/conversations/{id}
GET    /api/ai-chat/conversations/{id}/messages
POST   /api/ai-chat/conversations/{id}/messages
DELETE /api/ai-chat/conversations/{id}

Database Schema

The backend uses PostgreSQL with the following main tables:

  • users - User accounts with authentication and wallet info
  • emails - Email messages
  • email_folders - Email folder organization
  • posts - Social media posts
  • comments - Post comments
  • likes - Like tracking
  • follows - Follow relationships
  • videos - Video metadata
  • video_views - Video view tracking
  • video_likes - Video engagement
  • files - File metadata
  • folders - Folder structure
  • blocks - Blockchain blocks
  • transactions - Blockchain transactions
  • wallets - User wallets
  • conversations - AI chat conversations
  • messages - AI chat messages

Testing

# Install test dependencies
pip install pytest pytest-asyncio httpx

# Run tests
pytest

# Run with coverage
pytest --cov=app --cov-report=html

Deployment

Production Checklist

  • Change SECRET_KEY to a strong random value
  • Set DEBUG=False
  • Set ENVIRONMENT=production
  • Configure proper CORS origins
  • Use strong database passwords
  • Set up SSL/TLS certificates
  • Configure AWS S3 for file storage
  • Set up proper logging
  • Enable rate limiting
  • Set up monitoring and alerts

Docker Production Deployment

# Build production image
docker build -t blackroad-backend:latest .

# Run with production settings
docker run -d \
  -p 8000:8000 \
  -e DATABASE_URL=postgresql://user:pass@db:5432/blackroad \
  -e SECRET_KEY=your-production-secret \
  -e ENVIRONMENT=production \
  -e DEBUG=False \
  blackroad-backend:latest

Architecture

┌─────────────────────────────────────────────────────────┐
│                    Frontend (HTML/JS)                    │
└─────────────────────────────────────────────────────────┘
                            │
                            ↓
┌─────────────────────────────────────────────────────────┐
│                     FastAPI Backend                      │
├─────────────────────────────────────────────────────────┤
│  Routers:                                                │
│  • Authentication    • Email        • Social             │
│  • Videos           • Files        • Blockchain          │
│  • AI Chat                                               │
└─────────────────────────────────────────────────────────┘
                            │
                ┌───────────┴───────────┐
                ↓                       ↓
┌───────────────────────┐   ┌──────────────────┐
│   PostgreSQL DB       │   │   Redis Cache    │
│   • User data         │   │   • Sessions     │
│   • Emails            │   │   • API cache    │
│   • Posts             │   │   • Rate limits  │
│   • Files metadata    │   └──────────────────┘
│   • Blockchain        │
│   • Conversations     │
└───────────────────────┘

Security

  • Authentication: JWT tokens with expiration
  • Password Hashing: bcrypt with salt
  • Input Validation: Pydantic schemas
  • SQL Injection: SQLAlchemy ORM protection
  • CORS: Configurable origins
  • Rate Limiting: Redis-based (TODO)

Performance

  • Async/Await: Full async support with asyncio
  • Connection Pooling: SQLAlchemy and Redis pools
  • Caching: Redis for frequently accessed data
  • Database Indexing: Optimized queries with indexes

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests
  5. Submit a pull request

License

MIT License - see LICENSE file for details

Support

For issues and questions: