3 Commits

Author SHA1 Message Date
a1f84e2bd5 Update model recommendations to Qwen3 4B and fix status command
- Changed primary model recommendation from qwen3:1.7b to qwen3:4b
- Added Q8 quantization info in technical docs for production users
- Fixed method name error: get_embedding_info() -> get_status()
- Updated all error messages and test files with new recommendations
- Maintained beginner-friendly options (1.7b still very good, 0.6b surprisingly good)
- Added explanation of why small models work well with RAG context
- Comprehensive testing completed - system ready for clean release
2025-08-12 20:01:16 +10:00
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
3363171820 🎓 Complete beginner-friendly polish with production reliability
 BEGINNER-FRIENDLY ENHANCEMENTS:
- Add comprehensive glossary explaining RAG, embeddings, chunks in plain English
- Create detailed troubleshooting guide covering installation, search issues, performance
- Provide preset configs (beginner/fast/quality) with extensive helpful comments
- Enhanced error messages with specific solutions and next steps

🔧 PRODUCTION RELIABILITY:
- Add thread-safe caching with automatic cleanup in QueryExpander
- Implement chunked processing for large batches to prevent memory issues
- Enhanced concurrent embedding with intelligent batch size management
- Memory leak prevention with LRU cache approximation

🏗️ ARCHITECTURE COMPLETENESS:
- Maintain two-mode system (synthesis fast, exploration thinking + memory)
- Preserve educational value while removing intimidation barriers
- Complete testing coverage for mode separation and context memory
- Full documentation reflecting clean two-mode architecture

Perfect balance: genuinely beginner-friendly without compromising technical sophistication
2025-08-12 18:59:24 +10:00