tui-quickstart
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Mendon Kissling
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2 changed files with 44 additions and 75 deletions
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@ -11,20 +11,48 @@ Thank you for your interest in contributing to OpenRAG! This guide will help you
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- Python 3.13+ with uv package manager
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- Node.js 18+ and npm
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### Environment Setup
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### Set up OpenRAG for development
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1. Set up your development environment.
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```bash
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# Clone the repository
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git clone <repository-url>
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# Clone and setup environment
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git clone https://github.com/langflow-ai/openrag.git
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cd openrag
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# Setup development environment
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make setup # Creates .env and installs dependencies
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```
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### Configuration
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2. Configure the `.env` file with your API keys and credentials.
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Edit `.env` with your API keys and credentials. See the main README for required environment variables.
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```bash
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# Required
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OPENAI_API_KEY=your_openai_api_key
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OPENSEARCH_PASSWORD=your_secure_password
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LANGFLOW_SUPERUSER=admin
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LANGFLOW_SUPERUSER_PASSWORD=your_secure_password
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LANGFLOW_CHAT_FLOW_ID=your_chat_flow_id
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LANGFLOW_INGEST_FLOW_ID=your_ingest_flow_id
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NUDGES_FLOW_ID=your_nudges_flow_id
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```
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For extended configuration, including ingestion and optional variables, see [docs/reference/configuration.mdx](docs/docs/reference/configuration.mdx).
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3. Start OpenRAG.
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```bash
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# Full stack with GPU support
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make dev
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# Or CPU only
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make dev-cpu
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```
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Access the services:
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- **Frontend**: http://localhost:3000
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- **Backend API**: http://localhost:8000
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- **Langflow**: http://localhost:7860
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- **OpenSearch**: http://localhost:9200
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- **OpenSearch Dashboards**: http://localhost:5601
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## 🔧 Development Commands
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77
README.md
77
README.md
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@ -14,7 +14,8 @@
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<a href="https://deepwiki.com/phact/openrag"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
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</div>
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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.
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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.
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</div>
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<div align="center">
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<a href="#quickstart" style="color: #0366d6;">Quickstart</a> |
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@ -26,67 +27,17 @@ OpenRAG is a comprehensive Retrieval-Augmented Generation platform that enables
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## Quickstart
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To get started quickly, use the OpenRAG Terminal User Interface (TUI) to manage your OpenRAG installation without complex command-line operations.
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### Prerequisites
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- Docker or Podman with Compose installed
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- Make (for development commands)
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### Install and start OpenRAG
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1. Set up development environment.
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To launch OpenRAG with the TUI, do the following:
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1. Clone the OpenRAG repository.
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```bash
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# Clone and setup environment
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git clone https://github.com/langflow-ai/openrag.git
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cd openrag
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make setup # Creates .env and installs dependencies
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```
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2. Configure the `.env` file with your API keys and credentials.
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```bash
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# Required
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OPENAI_API_KEY=your_openai_api_key
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OPENSEARCH_PASSWORD=your_secure_password
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LANGFLOW_SUPERUSER=admin
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LANGFLOW_SUPERUSER_PASSWORD=your_secure_password
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LANGFLOW_CHAT_FLOW_ID=your_chat_flow_id
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LANGFLOW_INGEST_FLOW_ID=your_ingest_flow_id
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NUDGES_FLOW_ID=your_nudges_flow_id
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```
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For extended configuration, including ingestion and optional variables, see [docs/reference/configuration.mdx](docs/docs/reference/configuration.mdx)
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3. Start OpenRAG.
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```bash
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# Full stack with GPU support
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make dev
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# Or CPU only
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make dev-cpu
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```
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Access the services:
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- **Frontend**: http://localhost:3000
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- **Backend API**: http://localhost:8000
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- **Langflow**: http://localhost:7860
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- **OpenSearch**: http://localhost:9200
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- **OpenSearch Dashboards**: http://localhost:5601
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With OpenRAG started, ingest and retrieve documents with the [OpenRAG Quickstart](docs/docs/get-started/quickstart.mdx).
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## TUI interface
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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.
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### Launch OpenRAG with the TUI
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From the repository root, run:
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2. To start the TUI, from the repository root, run:
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```bash
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# Install dependencies first
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uv sync
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@ -95,6 +46,8 @@ uv sync
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uv run openrag
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```
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The TUI opens and guides you through OpenRAG setup.
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For the full TUI guide, see [TUI](docs/docs/get-started/tui.mdx).
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## Docker Deployment
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@ -133,16 +86,4 @@ For common issues and fixes, see [Troubleshoot](docs/docs/support/troubleshoot.m
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## Development
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For developers wanting to contribute to OpenRAG or set up a development environment, please see our comprehensive development guide:
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**[📚 See CONTRIBUTING.md for detailed development instructions](CONTRIBUTING.md)**
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### Quick Development Commands
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```bash
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make help # See all available commands
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make setup # Initial development setup
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make infra # Start infrastructure services
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make backend # Run backend locally
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make frontend # Run frontend locally
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```
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For developers wanting to contribute to OpenRAG or set up a development environment, see [CONTRIBUTING.md](CONTRIBUTING.md).
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