AI Application / RAG Pipeline Builder
6.5k 2026-04-26
run-llama/rags
Build and customize RAG pipelines and chatbots over your data using natural language, powered by Streamlit.
Core Features
Create RAG pipelines from data sources using natural language instructions.
Configure RAG parameters (e.g., top-k, summarization, LLM, embed model) via a UI.
Query the generated RAG agent through an interactive chatbot interface.
Supports various data inputs (local files, web pages) and multiple LLM providers.
Quick Start
poetry install --with dev && streamlit run 1_🏠_Home.pyDetailed Introduction
RAGs is an innovative Streamlit application designed to simplify the creation of Retrieval Augmented Generation (RAG) pipelines. Inspired by OpenAI's GPTs, it allows users to build custom chatbots over their own data using natural language descriptions. The project leverages a 'builder agent' to intelligently set up RAG configurations, which can then be fine-tuned through a user-friendly interface. It integrates with LlamaIndex and supports various LLMs and embedding models, making advanced AI capabilities accessible for personalized data querying.