slashinchi/ragflow repository overview

RAGFlow ARM64 Optimized Docker Image

This repository provides Docker images for the RAGFlow project, specifically optimized and built for the Linux ARM64 (aarch64) architecture. This image is ideal for deployment on ARM64-based cloud instances, such as Oracle Cloud Infrastructure (OCI) Arm Ampere A1 Compute, offering efficient and native performance.

What is RAGFlow?

RAGFlow is an innovative Retrieval-Augmented Generation (RAG) engine designed to streamline the development of large language model (LLM) applications. It excels at deep document understanding, intelligent chunking, and providing grounded citations, significantly reducing hallucinations in AI-generated responses.

Key Features of This Image:

Linux ARM64 Compatibility: Pre-built and rigorously tested for ARM64 environments, ensuring seamless operation and optimal performance on compatible hardware.

Automated CI/CD Workflow: Leverages GitHub Actions for fully automated builds and pushes to Docker Hub. This ensures that the images are always up-to-date with the latest changes from the forked repository, providing consistent and reliable updates.

Streamlined Deployment: Simplifies the process of deploying RAGFlow on ARM64-based servers, reducing manual setup and configuration efforts.

Cost-Effective Hosting: Enables efficient utilization of ARM64 instances, which often offer a more cost-effective solution for running LLM-powered applications.

How to Use:

To pull the latest ARM64-optimized RAGFlow image, use the following Docker command:

docker pull slashinchi/ragflow:nightly-arm64-slim

Contributing & Support:

This repository is a fork aimed at extending RAGFlow's compatibility to ARM64 architectures.

Original Project: For more details on RAGFlow, please visit the official RAGFlow GitHub repository.

Issues/Feedback: If you encounter any issues specific to the ARM64 build or have suggestions, please open an issue on this GitHub repository.

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RAGFlow ARM64 优化 Docker 镜像

本仓库提供 RAGFlow 项目的 Docker 镜像，专门为 Linux ARM64 (aarch64) 架构进行了优化和构建。此镜像非常适合部署在基于 ARM64 的云实例上，例如 Oracle Cloud Infrastructure (OCI) Arm Ampere A1 计算实例，可提供高效的本地性能。

RAGFlow 是什么？

RAGFlow 是一个创新的检索增强生成 (RAG) 引擎，旨在简化大型语言模型 (LLM) 应用程序的开发。它擅长深度文档理解、智能分块，并提供有依据的引用，显著减少了 AI 生成响应中的幻觉。

此镜像的主要特点：

Linux ARM64 兼容性： 针对 ARM64 环境预构建并经过严格测试，确保在兼容硬件上无缝运行并发挥最佳性能。

自动化 CI/CD 工作流： 利用 GitHub Actions 实现完全自动化的构建和推送到 Docker Hub。这确保了镜像始终与 fork 仓库中的最新更改保持同步，提供一致可靠的更新。

简化部署： 简化了在基于 ARM64 的服务器上部署 RAGFlow 的过程，减少了手动设置和配置工作。

经济高效的托管： 有助于高效利用 ARM64 实例，这些实例通常为运行由 LLM 驱动的应用程序提供更具成本效益的解决方案。

如何使用：

要拉取最新的 ARM64 优化 RAGFlow 镜像，请使用以下 Docker 命令：

docker pull slashinchi/ragflow:nightly-arm64-slim

贡献与支持：

本仓库是一个旨在将 RAGFlow 兼容性扩展到 ARM64 架构的 fork。

原始项目： 有关 RAGFlow 的更多详情，请访问 RAGFlow 官方 GitHub 仓库。

问题/反馈： 如果您遇到任何与 ARM64 构建相关的问题或有任何建议，请在本 GitHub 仓库 中提出 issue。