MCPFast / Tools / Lilbee: Terminal-based local RAG and AI chat for your documents
Lilbee provides terminal-based local RAG and AI chat with semantic/hybrid search, OCR, auto-built wiki, and GGUF model catalog.
View on GitHub→Lilbee is a powerful, terminal-based tool designed for developers to integrate Retrieval Augmented Generation (RAG) and AI chat capabilities directly with their local documents. It offers a streamlined workflow for building AI-powered applications without relying on external cloud services, ensuring data privacy and control. Lilbee leverages semantic and hybrid search to efficiently query your document corpus, making it an indispensable asset for developers working with large datasets or sensitive information.
Lilbee enables you to create a local RAG system that can understand and converse with your personal or project-specific documents. It processes your files, builds an index for fast retrieval, and allows you to interact with an AI model that has access to this indexed information. This means you can ask questions about your code, documentation, notes, or any other text-based content, and receive contextually relevant answers generated by the AI. The tool also includes Optical Character Recognition (OCR) capabilities, extending its utility to image-based documents.
Lilbee is specifically built for developers, AI engineers, and data scientists who need a robust, local solution for RAG and AI chat. If you are working on projects that require private data processing, want to build custom AI assistants for your documentation, or need to quickly prototype RAG applications without cloud dependencies, Lilbee is an ideal tool. Its terminal-centric design and comprehensive feature set make it suitable for those comfortable with command-line interfaces and seeking efficient, on-premises AI capabilities.