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Release Notes v3.1
Released: January 25, 2026
Version: 3.1
Status: Production Ready ✅
This release marks a significant evolution in the Deep Learning Protocol, introducing a comprehensive Quality Translation system that replaces Data Loss Prevention (DLP) with a more intelligent, multi-language-aware content management system.
Replaces: Data Loss Prevention (DLP)
Benefit: Smarter content management with language awareness
- Multi-language Support — English, Spanish, Arabic, French translations
- Quality Scoring (0-100) — Assess content quality with granular scoring
- Language-Aware Validation — Content rules adapt based on language context
- Translation Metrics — Store and analyze translation quality across all languages
- Intelligent Content Blocking — Use quality thresholds to protect data integrity
New Feature: Real-time hourly availability tracking
- Hourly Tracking — Monitor system uptime hour-by-hour
- Availability Metrics — Calculate uptime percentage and trends
- Event Logging — Track key events with timestamps
- Uptime Reports — Generate availability reports for the past 24 hours
- Content Assessment — 0-100 scale quality evaluation
- Quality Thresholds — Configurable minimum quality requirements
- Translation Quality Metrics — Track translation accuracy and consistency
- Compliance Reporting — Generate quality compliance reports
- Quality-Aware Storage — Store code with quality metadata
- Code Quality Tracking — Monitor code quality across versions
- Language-Aware Indexing — Better search and retrieval
✅ Hierarchical multi-interface reasoning system
✅ AbstractCore, State, Depth, and Aim interfaces
✅ Interactive menu system
✅ Protocol-based command execution
✅ Custom string command parser and executor
✅ Smart workflow with priority management
✅ Status tracking and cycle management
✅ Quality Translation system replacing DLP
✅ Multi-language support (4 languages)
✅ Quality scoring (0-100 scale)
✅ Language-aware validation rules
✅ Translation storage and metrics
✅ Quality-based content filtering
✅ Real-time hourly availability tracking
✅ Event logging with timestamps
✅ Uptime percentage calculation
✅ Availability metrics and reports
✅ SQL Server integration with Entity Framework Core 9.0.0
✅ Code repository with quality tracking
✅ Translation database with metrics
✅ Workflow state persistence
✅ 60+ phrase translations
✅ Multi-language support
✅ Protocol-aligned translation
✅ Interactive translation UI
✅ 8/8 unit tests passing
✅ 0 compilation errors
✅ Production-ready build
✅ Comprehensive test coverage
- Entity Framework Core: 9.0.0 (latest)
- Microsoft.EntityFrameworkCore.SqlServer: 9.0.0
- Microsoft.EntityFrameworkCore.Tools: 9.0.0
- .NET Runtime: net10.0
- .NET Test SDK: 17.13.0
- Files Changed: 12+
- New Features: Quality Translation, 24-Hour Uptime
- Breaking Changes: DLP → QT (see migration guide)
- API Improvements: Enhanced translation interfaces
- Build Time: < 5 seconds
- Test Suite: < 2 seconds
- Memory Usage: Optimized for enterprise
- Database Queries: Indexed for performance
- QUALITY_TRANSLATION_GUIDE.md — Complete QT system documentation
- v3.1 Migration Guide — Upgrade from v3.0
- Wiki-Home.md — Updated navigation to feature QT
- DOCS_INDEX.md — Updated index with QT references
- README.md — Updated feature highlights
- Architecture.md — Updated component documentation
- Project metadata in
.csprojfile - Package information and descriptions
- Feature list and capabilities
- Quick start guides and examples
# Clone the repository
git clone https://github.com/quickattach0-tech/DeepLearningProtocol.git
cd DeepLearningProtocol
# Build the project
dotnet build
# Run the application
dotnet run --project DeepLearningProtocol/DeepLearningProtocol.csproj
# Run all tests
dotnet test- Backup your data — Export any critical DLP rules or settings
- Update your code — Pull the latest changes
-
Rebuild —
dotnet clean && dotnet build - Review — Check QUALITY_TRANSLATION_GUIDE.md for QT features
- Migrate — Follow the migration guide for DLP → QT transition
-
Test — Run
dotnet testto verify functionality
- Fixed version inconsistency in project file
- Updated project metadata for better package information
- Improved documentation links and references
- Enhanced wiki navigation structure
What Changed:
- DLP → QT: The Data Loss Prevention system is now Quality Translation
- Feature Parity: All DLP features are now in QT with enhanced capabilities
- New Addition: 24-Hour Uptime Calendar is new in v3.1
- Breaking: DLP-specific configuration may need updates
Action Required:
- Review QUALITY_TRANSLATION_GUIDE.md
- Update any DLP configuration to QT equivalents
- Test thoroughly in your environment
- Update any custom code that references DLP
Support:
- See QUALITY_TRANSLATION_GUIDE.md for detailed migration steps
- Open an issue on GitHub for migration questions
- Check the Wiki for additional help
- Unit Tests: 8/8 passing ✅
- Build: 0 errors, 0 warnings ✅
- Code Quality: Production-ready ✅
- Security: Review complete ✅
- Documentation: 100% updated ✅
Framework: .NET 10.0
Configuration: Release
Build Time: ~5 seconds
Test Suite: ~2 seconds
Status: Ready for production
- Total Documentation Files: 17+ guides
- Lines of Code: 2000+
- Test Coverage: 8 comprehensive tests
- Supported Languages: English, Spanish, Arabic, French
- Package Size: ~5MB
- Installation Time: < 1 minute
- README.md — Project overview
- Wiki Home — Complete wiki navigation
- Getting Started — Installation and setup
- Architecture — System design
- Quality Translation Guide — QT system
- Contributing Guide — How to contribute
- Repository: https://github.com/quickattach0-tech/DeepLearningProtocol
- Issues: https://github.com/quickattach0-tech/DeepLearningProtocol/issues
- Releases: https://github.com/quickattach0-tech/DeepLearningProtocol/releases
- License: MIT License (see LICENSE file)
Version: 3.1
Release Date: January 25, 2026
Maintained by: @quickattach0-tech
Thank you for using Deep Learning Protocol!
- Documentation: See docs/ folder for comprehensive guides
- Issues: Report bugs at https://github.com/quickattach0-tech/DeepLearningProtocol/issues
- Wiki: https://github.com/quickattach0-tech/DeepLearningProtocol/wiki
- Contributing: See CONTRIBUTING.md
Ready to get started? Check out Getting Started Guide