aibo/TASKS.md

AI Trading Bot - Implementation Tasks

Task 1: Project Infrastructure and Docker Setup

Objectives

• Set up project structure and development environment
• Configure Docker Compose with all required services
• Implement environment variable management
• Create basic README with setup instructions

Deliverables

• Complete directory structure following specification
• docker-compose.yml with backend, frontend, PostgreSQL, Redis, Celery
• .env.example with all required environment variables
• README.md with step-by-step setup instructions

Acceptance Criteria

• Docker Compose successfully starts all services
• Backend and frontend containers build without errors
• PostgreSQL and Redis containers are accessible
• Environment variables properly configured via .env file
• Services communicate correctly (backend can reach database/Redis)
• README provides working setup for new developer

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Task 2: Backend API Structure and Authentication

Objectives

• Implement FastAPI application structure
• Create user authentication system with JWT
• Set up API routing and middleware
• Implement security utilities (password hashing, encryption)

Deliverables

• FastAPI main application with proper CORS configuration
• User registration and login endpoints
• JWT token authentication middleware
• Password hashing with bcrypt
• API key encryption/decryption utilities
• Pydantic schemas for request/response validation

Acceptance Criteria

• POST /api/auth/register creates user with encrypted API keys
• POST /api/auth/login returns valid JWT token
• Protected endpoints require valid JWT token
• Passwords are properly hashed (cannot be reversed)
• API keys are AES-256 encrypted before database storage
• CORS configured for frontend development
• All endpoints have proper OpenAPI documentation

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Task 3: Database Setup and Core Models

Objectives

• Configure PostgreSQL with TimescaleDB extension
• Implement database models using SQLAlchemy
• Create database migration system
• Set up async database connection and session management

Deliverables

• User, Bot, Order, Trade, and Price models
• Database connection configuration with async SQLAlchemy
• TimescaleDB hypertable setup for price data
• Database migrations (Alembic or similar)
• Repository classes for database operations
• Database connection pooling and error handling

Acceptance Criteria

• All tables created successfully in PostgreSQL
• TimescaleDB hypertable created for prices table
• Foreign key relationships properly configured
• Database migrations run without errors
• Async database operations work correctly
• Connection pool properly configured
• Database models include all required fields from schema

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Task 4: Binance Integration Service

Objectives

• Implement Binance API client using ccxt
• Create WebSocket connection manager for real-time prices
• Handle Binance authentication and rate limiting
• Implement order placement, cancellation, and status checking

Deliverables

• Binance service class with testnet and mainnet support
• WebSocket connection manager with auto-reconnect
• Order management methods (place, cancel, get status)
• Balance and position querying methods
• Rate limiting and error handling
• Health check endpoint for exchange connectivity

Acceptance Criteria

• Successfully connects to Binance testnet API
• Places and cancels limit orders via ccxt
• WebSocket connection provides real-time price updates
• Handles network failures and reconnects automatically
• Rate limiting respects Binance API limits
• Balance queries return correct account information
• Order status updates correctly reflect on exchange

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Task 5: Grid Trading Strategy Implementation

Objectives

• Implement core grid trading algorithm
• Calculate optimal grid levels based on support/resistance
• Create order management and grid rebalancing logic
• Implement P&L calculation and tracking

Deliverables

• Grid strategy class implementing trading strategy interface
• Grid level calculation algorithms (support/resistance based)
• Order placement logic (buy orders lower half, sell orders upper half)
• Grid monitoring and rebalancing on order fills
• P&L calculation (realized and unrealized)
• Risk management (stop loss, daily limits)

Acceptance Criteria

• Grid orders placed correctly based on current price and bounds
• Grid levels automatically calculated from market data
• Order fills trigger appropriate counter-order placement
• P&L calculated accurately for each completed trade pair
• Grid rebalancing maintains proper order distribution
• Stop loss and daily limits enforced
• Strategy works for at least 24 hours without intervention

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Task 6: AI Optimization Service

Objectives

• Integrate Claude API for market analysis
• Create market data collection and formatting
• Implement AI prompt engineering for grid parameter optimization
• Handle AI response processing and validation

Deliverables

• AI service class with Claude API integration
• Market data collection (current price, volatility, volume, indicators)
• Structured prompts for grid parameter optimization
• JSON response parsing and validation
• Confidence scoring and reasoning extraction
• API endpoint for AI optimization requests

Acceptance Criteria

• Successfully calls Claude API with market data
• Returns structured JSON with grid parameters
• AI suggestions are reasonable based on market conditions
• Response includes confidence score and reasoning
• Invalid AI responses handled gracefully
• API endpoint accepts market data and returns suggestions
• Rate limiting prevents excessive API calls

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Task 7: Real-time WebSocket Implementation

Objectives

• Implement WebSocket endpoints for real-time updates
• Create WebSocket connection management
• Set up Redis pub/sub for cross-process messaging
• Implement real-time price feed broadcasting

Deliverables

• WebSocket endpoints for bot updates and market data
• Connection manager with automatic cleanup
• Redis pub/sub integration for multi-process communication
• Real-time price broadcasting service
• Frontend WebSocket client integration
• Connection state management and error handling

Acceptance Criteria

• WebSocket connections established successfully
• Real-time price updates broadcast to connected clients
• Bot status changes sent via WebSocket
• Order updates transmitted in real-time
• Multiple clients can connect simultaneously
• WebSocket connections handle network interruptions
• Redis pub/sub correctly distributes messages across processes

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Task 8: Frontend Dashboard Setup and Layout

Objectives

• Set up Vue 3 project with Vite and TailwindCSS
• Implement routing and main dashboard layout
• Create authentication flow and protected routes
• Set up Pinia store management

Deliverables

• Vue 3 project with TypeScript support
• Vue Router configuration with authentication guards
• Login and registration pages
• Main dashboard layout with navigation
• Pinia stores for authentication and application state
• TailwindCSS configuration and design system
• Responsive design for desktop and tablet

Acceptance Criteria

• Vue application runs successfully in development
• Routing works for login, register, and dashboard pages
• Authentication guards protect dashboard routes
• User can register, login, and access dashboard
• Dashboard layout displays correctly on desktop
• TailwindCSS styling applied consistently
• Pinia stores manage application state properly

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Task 9: Bot Management UI Components

Objectives

• Create bot configuration form and validation
• Implement bot status card with real-time updates
• Create bot list and management interface
• Integrate with backend bot management endpoints

Deliverables

• Bot configuration form with all required parameters
• Real-time bot status card component
• Bot list/grid view for multiple bots
• Start/stop bot controls with confirmation dialogs
• Bot creation and editing interface
• Form validation with real-time feedback
• Integration with bot management API endpoints

Acceptance Criteria

• Configuration form validates all inputs correctly
• Bot creation saves configuration to database
• Status card shows real-time bot information
• Start/stop bot works with confirmation dialogs
• Multiple bots can be created and managed
• Form prevents submission with invalid data
• UI updates reflect backend bot changes immediately

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Task 10: Trading UI Components and Charts

Objectives

• Implement real-time price charts with grid overlay
• Create order book and trade history displays
• Implement P&L tracking and statistics panels
• Create emergency stop functionality

Deliverables

• Real-time candlestick chart with TradingView Lightweight Charts
• Grid levels overlay on price chart
• Order book showing active grid orders
• Trade history table with pagination
• P&L statistics panel (realized/unrealized, win rate, etc.)
• Emergency stop button with confirmation
• Buy/sell markers on price chart

Acceptance Criteria

• Price chart displays real-time candlestick data
• Grid levels correctly overlaid on chart
• Order book shows all active grid orders
• Trade history displays completed trades with P&L
• Statistics panel shows accurate performance metrics
• Emergency stop button immediately halts all trading
• Chart updates smoothly without performance issues

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Task 11: Security Features and Safety Mechanisms

Objectives

• Implement comprehensive input validation
• Create trading safety features (paper/live mode, limits)
• Add rate limiting and DDoS protection
• Implement audit logging and monitoring

Deliverables

• Comprehensive input validation on all endpoints
• Paper trading mode enforcement
• Daily loss limits and stop loss mechanisms
• Rate limiting middleware for all endpoints
• Audit logging for all trading actions
• API key management with encryption
• Confirmation dialogs for live trading activation
• Health check endpoints for all services

Acceptance Criteria

• All inputs validated and sanitized before processing
• Paper trading mode prevents real money trading
• Daily loss limits enforced automatically
• Live mode requires explicit confirmation
• Rate limiting prevents API abuse
• All trading actions logged for audit trail
• Health checks return status for all services
• System recovers gracefully from errors

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Task 12: Testing, Integration, and Final Deployment

Objectives

• Implement comprehensive testing (unit, integration, end-to-end)
• Perform full system integration testing
• Create deployment documentation and scripts
• Verify all success criteria from specification

Deliverables

• Unit tests for all backend services and strategies
• Integration tests for API endpoints
• Frontend component tests and E2E testing
• Docker production configuration
• CI/CD pipeline configuration
• Monitoring and logging setup
• Performance testing and optimization
• Final documentation and deployment guide

Acceptance Criteria

• All unit tests pass with >80% code coverage
• Integration tests verify complete user workflows
• End-to-end tests confirm grid trading works end-to-end
• Docker containers deploy successfully to production
• System runs stable for 24+ hours in paper mode
• All success criteria from specification verified:
  • Connects to Binance testnet ✓
  • Places grid orders via UI ✓
  • Dashboard shows live P&L ✓
  • AI suggests parameters ✓
  • Paper trading tracks correctly ✓
  • Start/stop works ✓
  • Runs stable 24h+ ✓
  • WebSocket updates real-time ✓
• README provides complete setup instructions
• .env.example includes all required variables

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Task Dependencies and Flow

Task 1 (Infrastructure) → Task 2 (Backend API) → Task 3 (Database)
                                                          ↓
Task 8 (Frontend) ← Task 7 (WebSocket) ← Task 4 (Binance)    
                       ↓                     ↓
Task 9 (Bot UI) ← Task 6 (AI Service) ← Task 5 (Grid Strategy)
                       ↓
Task 10 (Trading UI) ← Task 11 (Security)
                       ↓
         Task 12 (Testing & Deployment)

Notes

• Paper Trading First: All development must prioritize paper trading mode
• Testnet Only: Use Binance testnet exclusively during development
• Incremental Testing: Test each task independently before proceeding
• Error Handling: Comprehensive error handling required at all levels
• Documentation: Update README and add inline code documentation
• Performance: Monitor performance and optimize bottlenecks early