🚀 ARCGen v2.0 - Enterprise Edition Release

I'm thrilled to announce the major v2.0 release of Automated Reverse Code Generation (ARCGen)! This enterprise-grade rewrite introduces revolutionary AI-powered features, intelligent scaling, and multi-provider support that transforms how developers optimize and analyze code.
🎉 What's New in v2.0

🧠 Multi-Provider AI Support
DeepSeek Integration: Latest V3-0324 and R1-0528 models for enhanced code optimization
OpenAI Support: GPT-4 integration for advanced reasoning tasks
Claude Ready: Extensible architecture for future AI providers

⚡ Intelligent Scaling System
Adaptive Rate Limiting: Exponential backoff with automatic API limit handling
Dynamic Memory Management: Real-time memory monitoring and automatic cleanup
Smart Concurrency Control: Automatically scales worker threads based on system resources
Adaptive Chunking: Dynamic chunk sizing based on performance and memory constraints

🛡️ Enterprise Security & Compliance
Path Validation: Prevents directory traversal attacks
Security Scanning: Detects potentially malicious code patterns
Audit Trail: Complete processing logs and comprehensive reporting
Timeout Protection: Prevents infinite processing loops

🎯 Advanced Configuration Management
YAML-Based Profiles: Conservative, Balanced, and Aggressive optimization modes
Environment Variables: Secure API key management with .env support
Custom Configurations: Fully customizable processing parameters

📊 Performance & Reliability
Parallel Processing: Multi-threaded file processing with intelligent scaling
Progress Tracking: Real-time progress bars with ETA calculations
Error Recovery: Graceful error handling and automatic fallback mechanisms
Comprehensive Backup: Automatic backups with compression and retention policies

🎨 Enhanced User Experience
Rich Console Output: Beautiful progress bars and color-coded status messages
Detailed Reporting: JSON reports with processing statistics and performance metrics
Verbose Logging: Structured logging with multiple levels for debugging

📋 System Requirements
Python 3.8+ (3.9+ recommended)
4GB RAM minimum (8GB recommended for large projects)
Windows 10/11, Linux, or macOS
1GB free disk space