Show HN: Loft – offline Q&A over your local files, with citations (llama.cpp) (github.com)

Loft, an innovative offline Q&A tool, has been introduced to facilitate local file inquiries without the need for internet connectivity, built on the llama.cpp architecture. Designed for various operating systems—including Windows, macOS, and Linux—it enables users to ask questions about files stored in selected folders, utilizing Natural Language Processing (NLP) combined with local processing power. Notably, it incorporates a real-time indexing feature to manage file changes and offers Optical Character Recognition (OCR) capabilities for Windows, allowing users to query images and scanned documents. This development is significant for the AI/ML community as it minimizes reliance on cloud-based AI services, ensuring user data remains private and secure while enhancing accessibility to personal files. Loft's architecture smoothly integrates local llama-server processes for handling chat and embedding tasks, with an intuitive user interface that supports various file types, including text, code, PDFs, and images. The emphasis on local processing, advanced citation management, and real-time file monitoring underscores its potential impact on how users interact with AI tools in offline environments, opening new avenues for personalized AI solutions.