# 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, Next.js, OpenSearch, and Langflow integration.

Quick Start | TUI Interface | Docker Deployment | Development | Troubleshooting

## Quick Start ### Prerequisites - Docker or Podman with Compose installed - Make (for development commands) ### 1. Environment Setup ```bash # Clone and setup environment git clone https://github.com/langflow-ai/openrag.git cd openrag make setup # Creates .env and installs dependencies ``` ### 2. Configure Environment Edit `.env` with your API keys and credentials: ```bash # Required OPENAI_API_KEY=your_openai_api_key OPENSEARCH_PASSWORD=your_secure_password LANGFLOW_SUPERUSER=admin LANGFLOW_SUPERUSER_PASSWORD=your_secure_password LANGFLOW_CHAT_FLOW_ID=your_chat_flow_id LANGFLOW_INGEST_FLOW_ID=your_ingest_flow_id NUDGES_FLOW_ID=your_nudges_flow_id ``` See extended configuration, including ingestion and optional variables: [docs/reference/configuration.mdx](docs/docs/reference/configuration.mdx) ### 3. Start OpenRAG ```bash # Full stack with GPU support make dev # Or CPU only make dev-cpu ``` Access the services: - **Frontend**: http://localhost:3000 - **Backend API**: http://localhost:8000 - **Langflow**: http://localhost:7860 - **OpenSearch**: http://localhost:9200 - **OpenSearch Dashboards**: http://localhost:5601 With OpenRAG started, ingest and retrieve documents with the [OpenRAG Quickstart](/docs/get-started/quickstart.mdx). ## TUI interface OpenRAG includes a powerful Terminal User Interface (TUI) for easy setup, configuration, and monitoring. The TUI provides a user-friendly way to manage your OpenRAG installation without complex command-line operations. ![OpenRAG TUI Interface](assets/OpenRAG_TUI_2025-09-10T13_04_11_757637.svg) ### Launch OpenRAG with the TUI From the repository root, run: ```bash # Install dependencies first uv sync # Launch the TUI uv run openrag ``` For the full TUI guide, see [docs/get-started/tui.mdx](docs/docs/get-started/tui.mdx) ## Docker Deployment The repository includes two Docker Compose files. They deploy the same applications and containers, but to different environments. - [`docker-compose.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment with GPU support for accelerated AI processing. - [`docker-compose-cpu.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml) is a CPU-only version of OpenRAG for systems without GPU support. Use this Docker compose file for environments where GPU drivers aren't available. 1. Clone the OpenRAG repository. ```bash git clone https://github.com/langflow-ai/openrag.git cd openrag ``` 2. Build and start all services. For the GPU-accelerated deployment, run: ```bash docker compose build docker compose up -d ``` For environments without GPU support, run: ```bash docker compose -f docker-compose-cpu.yml up -d ``` For more information, see [docs/get-started/docker.mdx](docs/docs/get-started/docker.mdx) ## Troubleshooting For common issues and fixes, see [docs/support/troubleshoot.mdx](docs/docs/support/troubleshoot.mdx). ## Development For developers wanting to contribute to OpenRAG or set up a development environment, please see our comprehensive development guide: **[📚 See CONTRIBUTING.md for detailed development instructions](CONTRIBUTING.md)** ### Quick Development Commands ```bash make help # See all available commands make setup # Initial development setup make infra # Start infrastructure services make backend # Run backend locally make frontend # Run frontend locally ```