RLAMA
What is RLAMA?
RLAMA is a powerful local assistant tool designed for document question answering by employing Retrieval-Augmented Generation (RAG) systems. It connects to local Ollama models to index and process documents efficiently. Users can create, manage, and interact with their document knowledge bases securely on their local machines.
How to use RLAMA?
To use RLAMA, first index your document folder using a command like 'rlama rag [model] [rag-name] [folder-path]'. Then, start an interactive session with 'rlama run [rag-name]' to query your documents.
RLAMA's Core Features
Document indexing for intelligent retrieval
Multi-format support (text, code, PDF, DOCX)
Interactive query sessions
Local processing with privacy
RLAMA's Use Cases
Query project documentation and manuals
Study research papers and textbooks
Create secure knowledge bases for sensitive documents
FAQ from RLAMA
What formats of documents does RLAMA support?
Is my data secure when using RLAMA?
RLAMA Company
RLAMA Company name: RLAMA .
RLAMA Twitter
RLAMA Twitter Link: https://x.com/LeDonTizi
RLAMA Github
RLAMA Github Link: https://github.com/dontizi/rlama
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RLAMA Playground
Introducing rlama Playground: Build Local AI Solutions in Minutes! In today's demo, I'll guide you through rlama Playground, a groundbreaking tool that simplifies the complexity of AI optimization into a clean, user-friendly interface. In less than two minutes, you'll see how easy it is to create your very own fully-local Retrieval-Augmented Generation (RAG) system directly from your website content—no cloud required! We'll cover: - Naming your first local RAG project - Selecting powerful AI models from Hugging Face and Ollama (featuring Google’s latest gemma3 model!) - Easily configuring your website as a data source - Customizing chunking and reranking settings, with built-in guidelines to optimize performance - Launching your entire AI solution instantly with a single generated command line After setup, we'll immediately test our solution by asking it directly: "What features does rlama Pro have?" Join thousands of developers and users who rely on rlama every day for creating secure, local, and tailored AI solutions—faster and easier than ever before. Website: rlama.dev #AI #LocalAI #RAG #OpenSource #rlama #ArtificialIntelligence #DeveloperTools
Integrating Snowflake Data for RAG Processing with rlama
Exciting Update! 🎉 We’ve successfully integrated RLAMA with Snowflake! This powerful combination allows users to seamlessly retrieve and manage data from Snowflake, either by adding it to existing RAGs or creating new ones with Snowflake-stored data. This enhances flexibility in managing RAGs alongside other sources, enabling seamless integration of documentation from various platforms and improving Retrieval-Augmented Generation (RAG) systems. Stay tuned for more updates! 🚀 repo: github.com/dontizi/rlama website: rlama.dev
Introducing Rlama Chat an AI-powered assistant designed to help you with your RAG implementations
🚀 Exciting Update! 🚀 Our documentation, including all available commands and detailed examples, is now live on our website! 📖✨ But that’s not all—we’ve also introduced Rlama Chat, an AI-powered assistant designed to help you with your RAG implementations. Whether you have questions, need guidance, or are brainstorming new RAG use cases, Rlama Chat is here to support your projects. 💡 Have an idea for a specific RAG? Let’s build it together! Check out the docs and start exploring today! rlama.dev/documentation