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Changelog

All notable changes to the Earning Robot project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.1.0] - 2025-12-29

Added - Model Optimizer 🎉

  • Model Optimizer System: AI cost optimization tool similar to Google Cloud Vertex AI Model Optimizer
  • Automatic Cost Tracking: Every AI request is automatically logged and analyzed
  • Smart Recommendations: System finds cheaper alternatives with minimal quality impact
  • Pricing Database: 16 models from 6 providers (OpenAI, Anthropic, Mistral, Google, DeepSeek, OpenRouter)
  • REST API: 8 endpoints for optimizer access (/api/optimizer/*)
  • CLI Integration: 3 new menu items for optimizer stats and recommendations
  • Middleware: Decorator-based automatic usage tracking
  • Cost Calculator: Real-time cost calculation for any model
  • Optimization Reports: Detailed markdown reports with savings analysis

Features - Model Optimizer

  • 70-90% Cost Savings: Find cheaper alternatives automatically
  • Multi-Provider Support: Compare prices across OpenAI, Anthropic, Mistral, Google, DeepSeek, OpenRouter
  • Quality Preservation: Only recommend alternatives with <10 point quality drop
  • Smart Task Matching: Find optimal model for specific task types
  • Usage Analytics: Detailed statistics by model, task type, time period
  • Confidence Scoring: Each recommendation includes confidence level
  • Monthly Projections: Estimate savings based on actual usage patterns

Technical - Model Optimizer

  • backend/model_optimizer.py: Core optimization engine
  • backend/optimizer_api.py: REST API endpoints
  • backend/optimizer_middleware.py: Auto-tracking middleware
  • SQLite database with 3 tables (pricing, usage, recommendations)
  • 16 unit tests (all passing)
  • <1ms overhead per request
  • Asynchronous logging

Documentation - Model Optimizer

  • docs/MODEL_OPTIMIZER.md: Complete guide (50+ pages)
  • OPTIMIZER_QUICKSTART.md: Quick start guide
  • MODEL_OPTIMIZER_REPORT.md: Implementation report
  • examples/optimizer_examples.py: 7 usage examples
  • Updated README.md and docs/INDEX.md

Example Results

Comparing 1000 input + 500 output tokens:
- google/gemini-1.5-flash:    $0.00022 (cheapest)
- openai/gpt-4o:              $0.00750 (expensive)
- Potential savings:          97.0%

[1.0.0] - 2025-01-15

Added

  • Initial release of Earning Robot
  • Flask REST API server for task execution
  • Telegram bot interface for mobile control
  • OpenAI and Mistral AI integration
  • Stripe payment processing (subscriptions and micro-payments)
  • SQLite database for data persistence
  • Automated financial reporting system
  • Daily, weekly, and monthly report generation
  • Task scheduler for automated operations
  • Health monitoring and alerts
  • CLI interface for manual operations
  • Comprehensive documentation
  • Installation and deployment guides
  • API documentation
  • Basic test suite

Features

  • AI Integration: Support for OpenAI and Mistral AI APIs
  • Payment Processing: Stripe integration for monetization
  • Telegram Control: Full bot interface for remote management
  • REST API: HTTP endpoints for programmatic access
  • Automated Reporting: Daily financial reports via Telegram
  • Task Tracking: Complete audit trail of all operations
  • User Management: Support for multiple users and subscriptions
  • Expense Tracking: Automatic recording of API costs
  • Income Tracking: Subscription and payment tracking
  • Statistics: Detailed analytics and insights

Technical

  • Python 3.8+ support
  • SQLAlchemy ORM for database operations
  • APScheduler for task automation
  • Flask web framework
  • python-telegram-bot for Telegram integration
  • Comprehensive error handling and logging
  • Environment-based configuration
  • Virtual environment support
  • Cross-platform compatibility (Linux, macOS, Windows)

Documentation

  • Complete README with usage instructions
  • API documentation with examples
  • Installation guide
  • Deployment instructions
  • Code comments and docstrings
  • Example configurations

[Unreleased]

Planned Features

  • Web dashboard UI
  • More AI provider integrations (Claude, Gemini)
  • Multi-language support
  • Advanced analytics and charts
  • Docker containerization
  • Kubernetes deployment support
  • User authentication and permissions
  • Rate limiting
  • API versioning
  • WebSocket support for real-time updates
  • Email notifications
  • Database migrations
  • Enhanced security features
  • Performance optimizations
  • Extended test coverage