82 lines
No EOL
3.5 KiB
Markdown
82 lines
No EOL
3.5 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/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/docling-project/docling"><img src="https://img.shields.io/badge/Docling-000000?style=flat" alt="Langflow"></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](https://github.com/Kludex/starlette) and [Next.js](https://github.com/vercel/next.js). Powered by [OpenSearch](https://github.com/opensearch-project/OpenSearch), [Langflow](https://github.com/langflow-ai/langflow), and [Docling](https://github.com/docling-project/docling).
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<a href="https://deepwiki.com/langflow-ai/openrag"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
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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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<a href="#install-python-package" style="color: #0366d6;">Python package</a> |
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<a href="#docker-or-podman-installation" style="color: #0366d6;">Docker or Podman</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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## Quickstart
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To run OpenRAG without creating or modifying any project files, use `uvx`:
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```bash
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uvx openrag
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```
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This command runs OpenRAG without installing it to your project or globally.
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To run a specific version of OpenRAG, run `uvx --from openrag==VERSION openrag`.
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## Install Python package
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To add the OpenRAG Python package to a Python project, use `uv`:
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1. Create a new project with a virtual environment using `uv init`:
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```bash
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uv init YOUR_PROJECT_NAME
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cd YOUR_PROJECT_NAME
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```
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The `(venv)` prompt doesn't change, but `uv` commands will automatically use the project's virtual environment.
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For more information on virtual environments, see the [uv documentation](https://docs.astral.sh/uv/pip/environments).
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2. Add OpenRAG to your project:
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```bash
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uv add openrag
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```
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To add a specific version of OpenRAG, run `uv add openrag==VERSION`.
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3. Start the OpenRAG terminal user interface (TUI):
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```bash
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uv run openrag
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```
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4. Continue with the [Quickstart](https://docs.openr.ag/quickstart).
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For all installation options, see the [OpenRAG installation guide](https://docs.openr.ag/install).
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## Docker or Podman installation
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By default, OpenRAG automatically starts the required containers and helps you manage them.
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To install OpenRAG with self-managed containers, see the [OpenRAG installation guide](https://docs.openr.ag/docker).
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## Development
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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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## Troubleshooting
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For common issues and fixes, see [Troubleshoot OpenRAG](https://docs.openr.ag/support/troubleshoot). |