149 lines
No EOL
5.4 KiB
Markdown
149 lines
No EOL
5.4 KiB
Markdown
<div align="center">
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# OpenRAG
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<div align="center">
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<a href="https://github.com/langflow-ai/openrag/releases"><img src="https://img.shields.io/github/v/release/langflow-ai/openrag?style=flat" alt="Release"></a>
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<a href="https://github.com/langflow-ai/langflow"><img src="https://img.shields.io/badge/Langflow-1C1C1E?style=flat&logo=langflow" alt="Langflow"></a>
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<a href="https://github.com/opensearch-project/OpenSearch"><img src="https://img.shields.io/badge/OpenSearch-005EB8?style=flat&logo=opensearch&logoColor=white" alt="OpenSearch"></a>
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<a href="https://github.com/encode/starlette"><img src="https://img.shields.io/badge/Starlette-009639?style=flat&logo=fastapi&logoColor=white" alt="Starlette"></a>
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<a href="https://github.com/vercel/next.js"><img src="https://img.shields.io/badge/Next.js-000000?style=flat&logo=next.js&logoColor=white" alt="Next.js"></a>
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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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</div>
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<div align="center">
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<a href="#quick-start" style="color: #0366d6;">Quick Start</a> |
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<a href="#tui-interface" style="color: #0366d6;">TUI Interface</a> |
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<a href="#docker-deployment" style="color: #0366d6;">Docker Deployment</a> |
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<a href="#development" style="color: #0366d6;">Development</a> |
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<a href="#troubleshooting" style="color: #0366d6;">Troubleshooting</a>
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</div>
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## Quick Start
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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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### 1. Environment Setup
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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 Environment
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Edit `.env` 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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See extended configuration, including ingestion and optional variables: [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/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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```bash
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# Install dependencies first
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uv sync
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# Launch the TUI
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uv run openrag
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```
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For the full TUI guide, see [docs/get-started/tui.mdx](docs/docs/get-started/tui.mdx)
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## Docker Deployment
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The repository includes two Docker Compose files.
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They deploy the same applications and containers, but to different environments.
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- [`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.
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- [`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.
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1. Clone the OpenRAG repository.
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```bash
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git clone https://github.com/langflow-ai/openrag.git
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cd openrag
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```
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2. Build and start all services.
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For the GPU-accelerated deployment, run:
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```bash
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docker compose build
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docker compose up -d
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```
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For environments without GPU support, run:
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```bash
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docker compose -f docker-compose-cpu.yml up -d
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```
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For more information, see [docs/get-started/docker.mdx](docs/docs/get-started/docker.mdx)
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## Troubleshooting
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For common issues and fixes, see [docs/support/troubleshoot.mdx](docs/docs/support/troubleshoot.mdx).
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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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``` |