OpenRAG

        

OpenRAG is a comprehensive Retrieval-Augmented Generation platform that enables intelligent document search and AI-powered conversations. Users can upload, process, and query documents through a chat interface backed by large language models and semantic search capabilities. The system utilizes Langflow for document ingestion, retrieval workflows, and intelligent nudges, providing a seamless RAG experience. Built with Starlette and Next.js. Powered by OpenSearch, Langflow, and Docling.

Quickstart   |   TUI Interface   |   Docker Deployment   |   Development   |   Troubleshooting

Quickstart

To quickly run OpenRAG without creating or modifying any project files, use uvx:

uvx openrag

This runs OpenRAG without installing it to your project or globally. To run a specific version of OpenRAG, add the version to the command, such as: uvx --from openrag==0.1.25 openrag.

Install Python package

To first set up a project and then install the OpenRAG Python package, do the following:

1. Create a new project with a virtual environment using uv init.

   uv init YOUR_PROJECT_NAME
   cd YOUR_PROJECT_NAME
   

   The (venv) prompt doesn't change, but uv commands will automatically use the project's virtual environment. For more information on virtual environments, see the uv documentation.

2. Add OpenRAG to your project.

   uv add openrag
   

   To add a specific version of OpenRAG:

   uv add openrag==0.1.25
   

3. Start the OpenRAG TUI.

   uv run openrag
   

4. Continue with the Quickstart.

For the full TUI installation guide, see TUI.

Docker or Podman installation

For more information, see Install OpenRAG containers.

Troubleshooting

For common issues and fixes, see Troubleshoot.

Development

For developers wanting to contribute to OpenRAG or set up a development environment, see CONTRIBUTING.md.