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\!
109 lines
3.1 KiB
Bash
Executable File
109 lines
3.1 KiB
Bash
Executable File
#!/bin/bash
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# Script to record the FSS-Mini-RAG demo as an animated GIF
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set -e
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echo "🎬 FSS-Mini-RAG Demo Recording Script"
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echo "====================================="
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echo
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# Check if required tools are available
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check_tool() {
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if ! command -v "$1" &> /dev/null; then
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echo "❌ $1 is required but not installed."
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echo " Install with: $2"
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exit 1
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fi
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}
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echo "🔧 Checking required tools..."
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check_tool "asciinema" "pip install asciinema"
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echo "✅ asciinema found"
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# Optional: Check for gif conversion tools
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if command -v "agg" &> /dev/null; then
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echo "✅ agg found (for gif conversion)"
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CONVERTER="agg"
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elif command -v "svg-term" &> /dev/null; then
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echo "✅ svg-term found (for gif conversion)"
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CONVERTER="svg-term"
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else
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echo "⚠️ No gif converter found. You can:"
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echo " - Install agg: cargo install --git https://github.com/asciinema/agg"
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echo " - Or use online converter at: https://dstein64.github.io/gifcast/"
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CONVERTER="none"
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fi
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echo
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# Set up recording environment
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export TERM=xterm-256color
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export COLUMNS=80
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export LINES=24
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# Create recording directory
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mkdir -p recordings
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TIMESTAMP=$(date +"%Y%m%d_%H%M%S")
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RECORDING_FILE="recordings/fss-mini-rag-demo-${TIMESTAMP}.cast"
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GIF_FILE="recordings/fss-mini-rag-demo-${TIMESTAMP}.gif"
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echo "🎥 Starting recording..."
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echo " Output: $RECORDING_FILE"
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echo
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# Record the demo
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asciinema rec "$RECORDING_FILE" \
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--title "FSS-Mini-RAG Demo" \
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--command "python3 create_demo_script.py" \
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--cols 80 \
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--rows 24
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echo
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echo "✅ Recording complete: $RECORDING_FILE"
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# Convert to GIF if converter is available
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if [ "$CONVERTER" = "agg" ]; then
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echo "🎨 Converting to GIF with agg..."
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agg "$RECORDING_FILE" "$GIF_FILE" \
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--font-size 14 \
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--line-height 1.2 \
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--cols 80 \
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--rows 24 \
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--theme monokai
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echo "✅ GIF created: $GIF_FILE"
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# Optimize GIF size
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if command -v "gifsicle" &> /dev/null; then
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echo "🗜️ Optimizing GIF size..."
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gifsicle -O3 --lossy=80 -o "${GIF_FILE}.optimized" "$GIF_FILE"
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mv "${GIF_FILE}.optimized" "$GIF_FILE"
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echo "✅ GIF optimized"
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fi
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elif [ "$CONVERTER" = "svg-term" ]; then
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echo "🎨 Converting to SVG with svg-term..."
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svg-term --cast "$RECORDING_FILE" --out "${RECORDING_FILE%.cast}.svg" \
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--window --width 80 --height 24
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echo "✅ SVG created: ${RECORDING_FILE%.cast}.svg"
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echo "💡 Convert SVG to GIF online at: https://cloudconvert.com/svg-to-gif"
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fi
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echo
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echo "🎉 Demo recording complete!"
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echo
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echo "📁 Files created:"
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echo " 📼 Recording: $RECORDING_FILE"
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if [ "$CONVERTER" != "none" ] && [ -f "$GIF_FILE" ]; then
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echo " 🎞️ GIF: $GIF_FILE"
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fi
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echo
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echo "📋 Next steps:"
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echo " 1. Review the recording: asciinema play $RECORDING_FILE"
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if [ "$CONVERTER" = "none" ]; then
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echo " 2. Convert to GIF online: https://dstein64.github.io/gifcast/"
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fi
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echo " 3. Add to README.md after the mermaid diagram"
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echo " 4. Optimize for web (target: <2MB for fast loading)"
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echo
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echo "🚀 Perfect demo for showcasing FSS-Mini-RAG!" |