Verba is an open-source application designed to offer an end-to-end, streamlined, and user-friendly interface for Retrieval-Augmented Generation (RAG) out of the box. It supports various RAG techniques, data types, LLM providers, and offers Docker support and a fully-customizable frontend.
This is a local LLM chatbot project with RAG for processing PDF input files
In this tutorial, we will build a RAG system with a self-querying retriever in the LangChain framework. This will enable us to filter the retrieved movies using metadata, thus providing more meaningful movie recommendations.
Ragna is an open source RAG orchestration framework.
With an intuitive API for quick experimentation and built-in tools for creating production-ready application, you can quickly leverage Large Language Models (LLMs) for your work.
With an intuitive API for quick experimentation and built-in tools for creating production-ready application, you can quickly leverage Large Language Models (LLMs) for your work.
pip install 'ragna builtin » ' # Install ragna with all extensions
ragna config # Initialize configuration
ragna ui # Launch the web app
ragna config # Initialize configuration
ragna ui # Launch the web app
