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RagApp

The easiest way to use Agentic RAG in any enterprise — deployable in your own cloud infrastructure using Docker

★ 4,442 GitHub Apache-2.0 ragrag-appllamaindexdockerenterpriseretrieval-augmented-generationllm RAG & Knowledge

Overview

RagApp is an open-source, Docker-deployable RAG (Retrieval-Augmented Generation) platform built with LlamaIndex. As simple to configure as OpenAI’s custom GPTs, but fully self-hosted in your own infrastructure. It provides an Admin UI for configuration, a Chat UI for end users, and a REST API for programmatic access. Built with TypeScript and Python, RagApp supports hosted AI models from OpenAI and Gemini, as well as local models via Ollama. Deployable via Docker Compose with one-command setup — ideal for enterprises that need private, customizable RAG without vendor lock-in.

Requirements

Min vCPU
1
Min RAM
1024 MB
Min Disk
10 GB
Rec vCPU
2
Rec RAM
2048 MB
Rec Disk
20 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  ragapp:
    image: ragapp/ragapp:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/ragapp:/data

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Guides & articles

How to Deploy RagApp with Docker — A Step-by-Step Tutorial

A hands-on tutorial on deploying RagApp with Docker — from pulling the image to chatting with your documents in under 5 minutes. Includes Ollama setup, Docker Compose, and common pitfalls.

Jul 14, 2026

RagApp: The Simplest Way to Deploy Agentic RAG in Your Own Cloud

RagApp makes RAG deployment simple — one Docker command gives you a full LlamaIndex-powered RAG system with Admin UI, Chat UI, and REST API. Self-hosted, private, and open source.

Jul 14, 2026