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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
The recommended way to get started with OpenRAG is through the official documentation quickstart guide, which contains up-to-date installation steps, prerequisites, and usage examples:
👉 https://docs.openr.ag/quickstart
The GitHub repository focuses on the source code. Please refer to the documentation for setup and usage instructions.
Install Python package
OpenRAG can be installed as a Python package. For detailed installation steps, environment requirements, and environment setup guidance (e.g., managing virtual environments), see the official documentation:
👉 https://docs.openr.ag/install
👉 https://docs.astral.sh/uv/pip/environments
This ensures you are following the most current and supported setup.
Docker or Podman installation
By default, OpenRAG automatically starts the required containers and helps you manage them. To install OpenRAG with self-managed containers, see the OpenRAG installation guide.
Development
For developers wanting to contribute to OpenRAG or set up a development environment, see CONTRIBUTING.md.
Troubleshooting
For common issues and fixes, see Troubleshoot OpenRAG.