trading/app_idea/backend-documentation.md

Backend Documentation

Backend Framework and Language

Framework: Node.js with Express.js Language: JavaScript/TypeScript Architecture: RESTful API with layered architecture

Node.js with Express.js is chosen for:

• Excellent performance for real-time applications
• Rich ecosystem of packages for financial data processing
• Good compatibility with React frontend
• Efficient handling of asynchronous operations (important for LLM API calls)
• Seamless integration with Supabase

API Design

API Structure

The API follows RESTful principles with the following main resources:

1. Auth

   • /api/auth/login - Social login with Google
   • /api/auth/logout - User logout
   • /api/auth/refresh - Token refresh

2. Users

   • /api/users/profile - User profile management
   • /api/users/api-keys - Secure API key management
   • /api/users/credits - Credit management

3. Indicators

   • /api/indicators - CRUD operations for indicators
   • /api/indicators/categories - Get indicators by category
   • /api/indicators/trending - Get trending indicators

4. Strategies

   • /api/strategies - CRUD operations for strategies
   • /api/strategies/generate - AI strategy generation
   • /api/strategies/export - Generate PineScript code
   • /api/strategies/versions - Strategy version management

5. Community

   • /api/community/strategies - Shared strategies
   • /api/community/users - User profiles

API Versioning

The API will be versioned using URL path versioning:

• /api/v1/... - Initial version

Authentication and Authorization

1. Authentication

   • JWT (JSON Web Tokens) for session management
   • Google OAuth for social login
   • Refresh token rotation for security

2. Authorization

   • Role-based access control (Free user vs. Paid user)
   • Resource-based permissions

LLM Integration

Supported Providers

• OpenAI
• Anthropic
• OpenRouter.ai

Integration Architecture

1. Provider Adapter Pattern

   • Abstract interface for LLM providers
   • Concrete implementations for each provider
   • Fallback mechanism if primary provider fails

2. Prompt Engineering

   • Structured prompts for strategy generation
   • Context management for complex strategies
   • Response validation and error handling

3. Security Considerations

   • Encrypted storage of API keys
   • No persistence of full strategy responses
   • Rate limiting to prevent abuse

Error Handling

1. Standardized Error Responses

   {
     "status": "error",
     "code": "ERROR_CODE",
     "message": "User-friendly error message",
     "details": { /* Additional error details */ }
   }
   

2. Error Categories

   • Authentication errors (401)
   • Authorization errors (403)
   • Resource not found (404)
   • Validation errors (422)
   • Server errors (500)
   • LLM provider errors (502)

3. Graceful Degradation

   • Fallback options when services are unavailable
   • Detailed user instructions for recovery

Third-Party Integrations

1. Payment Processing

   • Stripe integration for subscription management
   • PayPal as alternative payment method
   • Coupon code functionality

2. Email Service

   • Transactional emails for account verification
   • Subscription notifications
   • Strategy export delivery

Caching Strategy

1. Redis Cache

   • Cache common indicator configurations
   • Store frequently accessed strategy templates
   • Temporary storage for generated strategies

2. Cache Invalidation

   • Time-based expiration for market data
   • Event-based invalidation for user-specific data

Security Measures

1. Data Protection

   • Encryption of sensitive data at rest
   • Secure transmission with TLS
   • API key encryption with AES-256

2. API Security

   • Rate limiting to prevent abuse
   • CORS configuration for frontend access
   • Input validation and sanitization
   • Protection against common attacks (XSS, CSRF, injection)

3. Monitoring and Logging

   • Structured logging for operations
   • Error tracking and alerting
   • Audit trail for sensitive operations

Performance Optimization

1. Query Optimization

   • Efficient database queries
   • Pagination for large result sets
   • Eager loading of related data

2. Asynchronous Processing

   • Background jobs for resource-intensive tasks
   • Queuing system for LLM requests

3. Scaling Considerations

   • Horizontal scaling readiness
   • Stateless API design
   • Connection pooling for database access