Fss-Rag-Mini

2 Commits 7 Branches 0 Tags

Author	SHA1	Message	Date
BobAi	ba28246178	Add LLM synthesis feature with smart model selection and increase default results to 10 🧠 NEW: LLM Synthesis Feature - Intelligent analysis of RAG search results using Ollama LLMs - Smart model selection: Qwen3 → Qwen2.5 → Mistral → Llama3.2 - Prioritizes efficient models (1.5B-3B parameters) for best performance - Structured output: summary, key findings, code patterns, suggested actions - Confidence scoring for result reliability - Graceful fallback with setup instructions if Ollama unavailable 📊 Enhanced Search Experience - Increased default search results from 5 to 10 across all components - Updated demo script to show all 8 results with richer previews - Better user experience with more comprehensive result sets 🎯 New CLI Options - Added --synthesize/-s flag: rag-mini search project "query" --synthesize - Zero-configuration setup - automatically detects best available model - Never downloads models - only uses what's already installed 🧪 Tested with qwen3:1.7b - Confirmed excellent performance with 1.7B parameter model - Professional-grade analysis including security recommendations - Fast response times with quality RAG context Perfect for users who already have Ollama - transforms FSS-Mini-RAG from search tool into AI-powered code assistant\!	2025-08-12 17:12:51 +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

ba28246178

Add LLM synthesis feature with smart model selection and increase default results to 10

🧠 NEW: LLM Synthesis Feature
- Intelligent analysis of RAG search results using Ollama LLMs
- Smart model selection: Qwen3 → Qwen2.5 → Mistral → Llama3.2
- Prioritizes efficient models (1.5B-3B parameters) for best performance
- Structured output: summary, key findings, code patterns, suggested actions
- Confidence scoring for result reliability
- Graceful fallback with setup instructions if Ollama unavailable

📊 Enhanced Search Experience
- Increased default search results from 5 to 10 across all components
- Updated demo script to show all 8 results with richer previews
- Better user experience with more comprehensive result sets

🎯 New CLI Options
- Added --synthesize/-s flag: rag-mini search project "query" --synthesize
- Zero-configuration setup - automatically detects best available model
- Never downloads models - only uses what's already installed

🧪 Tested with qwen3:1.7b
- Confirmed excellent performance with 1.7B parameter model
- Professional-grade analysis including security recommendations
- Fast response times with quality RAG context

Perfect for users who already have Ollama - transforms FSS-Mini-RAG
from search tool into AI-powered code assistant\!

2025-08-12 17:12:51 +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