Rlama
Open-source tool for building document question-answering systems with local AI models.
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RLAMA (Retrieval-Augmented Local Assistant Model Agent) is an open-source AI solution that integrates with local AI models to create, manage, and interact with Retrieval-Augmented Generation (RAG) systems. It allows users to build powerful document question-answering systems with multiple document formats, advanced semantic chunking, and local storage and processing.
RLAMA can be installed and used via the command line. Users can create RAG systems by indexing folders of documents, query documents in an interactive session, and manage RAG systems with commands like `rlama rag`, `rlama run`, `rlama list`, and `rlama delete`. RLAMA Unlimited offers a visual interface for building RAG systems without coding.
Choosing this is a no-brainer if you want full control over your document Q&A systems with local AI models. It’s perfect for privacy-conscious users who want powerful, customizable AI without sending data to the cloud.
Visual interface - no coding needed. Create RAGs in minutes not weeks. Supports development of open source ecosystem.
Visual interface - no coding needed. Create RAGs in minutes not weeks. Supports development of open source ecosystem.
