As concerns over data privacy intensify, a developer has launched LocalDocs – a macOS application enabling users to chat with documents entirely offline. Unlike cloud-based alternatives, the tool processes all data locally, eliminating API keys and preventing sensitive information from leaving the device.

Technical Architecture

Built for Apple Silicon, the app combines:
- Electron frontend with a Python backend compiled to native binary
- llama.cpp with GGUF models (initially Gemma/Mistral-class) for local LLM inference
- SentenceTransformers for generating embeddings
- FAISS for vector search operations
- Integrated OCR capabilities for images and scanned PDFs

All components run on-device using CPU or Metal acceleration, with models downloaded automatically upon first launch.

Solving the Privacy Paradox

"I wanted a privacy-first alternative to cloud document chat tools," stated the developer behind the project. Packaging the full pipeline – including OCR, embedding generation, retrieval-augmented generation (RAG), and LLM inference – proved challenging due to macOS constraints like Gatekeeper protections, PyInstaller complexities, dynamic library management, and large model sizes exceeding 4GB.

Execution and Accessibility

The application is available via GitHub release for Apple Silicon macOS devices. As an unsigned build, users must bypass macOS security controls with:

xattr -rd com.apple.quarantine "/Applications/Document Chat.app"

Implications for Local AI

This project highlights growing momentum toward:
1. Privacy-preserving AI that avoids cloud data transmission
2. Hardware optimization leveraging Apple Silicon's on-device capabilities
3. Integrated toolchains combining multiple local AI components (OCR + RAG + LLM)

The developer seeks community feedback on UX design, model performance tradeoffs, and approaches for optimizing local RAG systems. As enterprises increasingly demand confidential AI processing, tools like LocalDocs demonstrate viable paths toward fully offline document intelligence. Source: Hacker News Thread