Fss-Rag-Mini

BobAi/Fss-Rag-Mini

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Author	SHA1	Message	Date
BobAi	e6d5f20f7d	Improve installer experience and beginner-friendly features - Replace slow full-project test with fast 3-file sample - Add beginner guidance and welcome messages - Add sample questions to combat prompt paralysis - Add intelligent follow-up question suggestions - Improve TUI with contextual next steps Installer improvements: - Create minimal sample project (3 files) for testing - Add helpful tips and guidance for new users - Better error messaging and progress indicators TUI enhancements: - Welcome message for first-time users - Sample search questions (authentication, error handling, etc.) - Pattern-based follow-up question generation - Contextual suggestions based on search results These changes address user feedback about installation taking too long and beginners not knowing what to search for.	2025-08-14 08:26:22 +10:00
BobAi	a96ddba3c9	MAJOR: Remove all Claude references and rename to Mini-RAG Complete rebrand to eliminate any Claude/Anthropic references: Directory Changes: - claude_rag/ → mini_rag/ (preserving git history) Content Changes: - Replaced 930+ Claude references across 40+ files - Updated all imports: from claude_rag → from mini_rag - Updated all file paths: .claude-rag → .mini-rag - Updated documentation and comments - Updated configuration files and examples Testing Changes: - All tests updated to use mini_rag imports - Integration tests verify new module structure This ensures complete independence from Claude/Anthropic branding while maintaining all functionality and git history.	2025-08-12 19:21:30 +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

e6d5f20f7d

Improve installer experience and beginner-friendly features

- Replace slow full-project test with fast 3-file sample
- Add beginner guidance and welcome messages
- Add sample questions to combat prompt paralysis
- Add intelligent follow-up question suggestions
- Improve TUI with contextual next steps

Installer improvements:
- Create minimal sample project (3 files) for testing
- Add helpful tips and guidance for new users
- Better error messaging and progress indicators

TUI enhancements:
- Welcome message for first-time users
- Sample search questions (authentication, error handling, etc.)
- Pattern-based follow-up question generation
- Contextual suggestions based on search results

These changes address user feedback about installation taking too long
and beginners not knowing what to search for.

2025-08-14 08:26:22 +10:00

BobAi

a96ddba3c9

MAJOR: Remove all Claude references and rename to Mini-RAG

Complete rebrand to eliminate any Claude/Anthropic references:

Directory Changes:
- claude_rag/ → mini_rag/ (preserving git history)

Content Changes:
- Replaced 930+ Claude references across 40+ files
- Updated all imports: from claude_rag → from mini_rag
- Updated all file paths: .claude-rag → .mini-rag
- Updated documentation and comments
- Updated configuration files and examples

Testing Changes:
- All tests updated to use mini_rag imports
- Integration tests verify new module structure

This ensures complete independence from Claude/Anthropic
branding while maintaining all functionality and git history.

2025-08-12 19:21:30 +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