Privacy-first document tagger using local AI. Automatically tags your files with up to 10 relevant tags.

• 🔒 100% Private - All AI processing happens locally
• 🏷️ Smart Tagging - Up to 10 tags per file
• 🔍 Search - Find files by name or tags
• 💼 Financial Docs - Detects I797, bank statements, tax forms, etc.
• 💾 Local Storage - Tags saved in JSON database
• 🌐 Modern Web UI - Clean, responsive interface using HTML/CSS/JS
• 🎯 Intelligent Filtering - Only processes text-based documents with AI, uses heuristics for binary files

Modern, responsive web interface with real-time updates:

python web_ui.py # Then open http://localhost:5000 in your browser

Traditional tkinter-based desktop application:

python docsifter.py

python setup.py # Interactive setup python web_ui.py # Run the web app

1. Choose between Web UI (recommended) or Desktop UI
2. Select folder (Documents, Desktop, Downloads)
3. Click "Scan & Tag Files"
4. Search your tagged files

Important Notes:

• Text-based documents (PDF, Word, Excel, etc.) are analyzed by AI for intelligent tagging
• Binary files (images, videos, audio, archives) get basic heuristic tags only - AI doesn't guess content it can't see
• AI is conservative and only tags based on clear evidence in filenames and extensions

Tags include:

• Document type (pdf, image, spreadsheet)
• Category (financial, immigration, legal)
• Specific forms (I797, W2, bank-statement)
• Year (2024, 2025)

• Python 3.7+
• Ollama (installed by setup script)

# Install Ollama brew install ollama # macOS# or visit ollama.ai# Download model ollama pull llama3.2 # Install dependencies pip install -r requirements.txt # Run python docsifter.py

MIT