BobAi
4166d0a362
🎯 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\!
83 lines
2.2 KiB
Markdown
83 lines
2.2 KiB
Markdown
# 🚀 FSS-Mini-RAG: Get Started in 2 Minutes
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## Step 1: Install Everything
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```bash
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./install_mini_rag.sh
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```
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**That's it!** The installer handles everything automatically:
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- Checks Python installation
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- Sets up virtual environment
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- Guides you through Ollama setup
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- Installs dependencies
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- Tests everything works
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## Step 2: Use It
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### TUI - Interactive Interface (Easiest)
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```bash
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./rag-tui
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```
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**Perfect for beginners!** Menu-driven interface that:
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- Shows you CLI commands as you use it
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- Guides you through setup and configuration
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- No need to memorize commands
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### Quick Commands (Beginner-Friendly)
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```bash
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# Index any project
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./run_mini_rag.sh index ~/my-project
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# Search your code
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./run_mini_rag.sh search ~/my-project "authentication logic"
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# Check what's indexed
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./run_mini_rag.sh status ~/my-project
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```
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### Full Commands (More Options)
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```bash
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# Basic indexing and search
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./rag-mini index /path/to/project
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./rag-mini search /path/to/project "database connection"
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# Enhanced search with smart features
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./rag-mini-enhanced search /path/to/project "UserManager"
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./rag-mini-enhanced similar /path/to/project "def validate_input"
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```
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## What You Get
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**Semantic Search**: Instead of exact text matching, finds code by meaning:
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- Search "user login" → finds authentication functions, session management, password validation
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- Search "database queries" → finds SQL, ORM code, connection handling
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- Search "error handling" → finds try/catch blocks, error classes, logging
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## Installation Options
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The installer offers two choices:
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**Light Installation (Recommended)**:
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- Uses Ollama for high-quality embeddings
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- Requires Ollama installed (installer guides you)
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- Small download (~50MB)
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**Full Installation**:
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- Includes ML fallback models
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- Works without Ollama
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- Large download (~2-3GB)
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## Troubleshooting
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**"Python not found"**: Install Python 3.8+ from python.org
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**"Ollama not found"**: Visit https://ollama.ai/download
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**"Import errors"**: Re-run `./install_mini_rag.sh`
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## Next Steps
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- **Technical Details**: Read `README.md`
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- **Step-by-Step Guide**: Read `docs/GETTING_STARTED.md`
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- **Examples**: Check `examples/` directory
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- **Test It**: Run on this project: `./run_mini_rag.sh index .`
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---
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**Questions?** Everything is documented in the README.md file. |