Fss-Rag-Mini

BobAi/Fss-Rag-Mini

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Author	SHA1	Message	Date
BobAi	1a5cc535a1	Restore demo GIFs and clean up README presentation - Added back the two essential demo GIFs showing synthesis and exploration modes - Moved logo to be smaller and inline with title (40x40px) - Removed all demo creation scripts and development artifacts - Clean, professional presentation ready for GitHub release - Repository now contains only production-ready files	2025-08-12 21:55:14 +10:00
BobAi	be488c5a3d	Add new Mini-RAG logo and clean repository structure - Added beautiful new Mini-RAG logo with teal and purple colors - Updated README to use new logo - Cleaned up repository by removing development scripts and artifacts - Repository structure now clean and professional - Ready for GitHub release preparation	2025-08-12 21:14:42 +10:00
BobAi	4166d0a362	Initial release: FSS-Mini-RAG - Lightweight semantic code search system 🎯 Complete transformation from 5.9GB bloated system to 70MB optimized solution ✨ Key Features: - Hybrid embedding system (Ollama + ML fallback + hash backup) - Intelligent chunking with language-aware parsing - Semantic + BM25 hybrid search with rich context - Zero-config portable design with graceful degradation - Beautiful TUI for beginners + powerful CLI for experts - Comprehensive documentation with 8+ Mermaid diagrams - Professional animated demo (183KB optimized GIF) 🏗️ Architecture Highlights: - LanceDB vector storage with streaming indexing - Smart file tracking (size/mtime) to avoid expensive rehashing - Progressive chunking: Markdown headers → Python functions → fixed-size - Quality filtering: 200+ chars, 20+ words, 30% alphanumeric content - Concurrent batch processing with error recovery 📦 Package Contents: - Core engine: claude_rag/ (11 modules, 2,847 lines) - Entry points: rag-mini (unified), rag-tui (beginner interface) - Documentation: README + 6 guides with visual diagrams - Assets: 3D icon, optimized demo GIF, recording tools - Tests: 8 comprehensive integration and validation tests - Examples: Usage patterns, config templates, dependency analysis 🎥 Demo System: - Scripted demonstration showing 12 files → 58 chunks indexing - Semantic search with multi-line result previews - Complete workflow from TUI startup to CLI mastery - Professional recording pipeline with asciinema + GIF conversion 🛡️ Security & Quality: - Complete .gitignore with personal data protection - Dependency optimization (removed python-dotenv) - Code quality validation and educational test suite - Agent-reviewed architecture and documentation Ready for production use - copy folder, run ./rag-mini, start searching\!	2025-08-12 16:38:28 +10:00

Author

SHA1

Message

Date

BobAi

1a5cc535a1

Restore demo GIFs and clean up README presentation

- Added back the two essential demo GIFs showing synthesis and exploration modes
- Moved logo to be smaller and inline with title (40x40px)
- Removed all demo creation scripts and development artifacts
- Clean, professional presentation ready for GitHub release
- Repository now contains only production-ready files

2025-08-12 21:55:14 +10:00

BobAi

be488c5a3d

Add new Mini-RAG logo and clean repository structure

- Added beautiful new Mini-RAG logo with teal and purple colors
- Updated README to use new logo
- Cleaned up repository by removing development scripts and artifacts
- Repository structure now clean and professional
- Ready for GitHub release preparation

2025-08-12 21:14:42 +10:00

BobAi

4166d0a362

Initial release: FSS-Mini-RAG - Lightweight semantic code search system

🎯 Complete transformation from 5.9GB bloated system to 70MB optimized solution

✨ Key Features:
- Hybrid embedding system (Ollama + ML fallback + hash backup)
- Intelligent chunking with language-aware parsing
- Semantic + BM25 hybrid search with rich context
- Zero-config portable design with graceful degradation
- Beautiful TUI for beginners + powerful CLI for experts
- Comprehensive documentation with 8+ Mermaid diagrams
- Professional animated demo (183KB optimized GIF)

🏗️ Architecture Highlights:
- LanceDB vector storage with streaming indexing
- Smart file tracking (size/mtime) to avoid expensive rehashing
- Progressive chunking: Markdown headers → Python functions → fixed-size
- Quality filtering: 200+ chars, 20+ words, 30% alphanumeric content
- Concurrent batch processing with error recovery

📦 Package Contents:
- Core engine: claude_rag/ (11 modules, 2,847 lines)
- Entry points: rag-mini (unified), rag-tui (beginner interface)
- Documentation: README + 6 guides with visual diagrams
- Assets: 3D icon, optimized demo GIF, recording tools
- Tests: 8 comprehensive integration and validation tests
- Examples: Usage patterns, config templates, dependency analysis

🎥 Demo System:
- Scripted demonstration showing 12 files → 58 chunks indexing
- Semantic search with multi-line result previews
- Complete workflow from TUI startup to CLI mastery
- Professional recording pipeline with asciinema + GIF conversion

🛡️ Security & Quality:
- Complete .gitignore with personal data protection
- Dependency optimization (removed python-dotenv)
- Code quality validation and educational test suite
- Agent-reviewed architecture and documentation

Ready for production use - copy folder, run ./rag-mini, start searching\!

2025-08-12 16:38:28 +10:00

3 Commits