How to Build and Deploy a Dify LLM Application Platform on CentOS

This guide explains what Dify is, outlines its key features and application scenarios, and provides step‑by‑step instructions for preparing the environment, installing Docker and Docker‑Compose, and deploying Dify on a CentOS 7.9 system, including verification of a successful setup.

MaGe Linux Operations
MaGe Linux Operations
MaGe Linux Operations
How to Build and Deploy a Dify LLM Application Platform on CentOS

Introduction

Dify is an open‑source large language model (LLM) application development platform that combines Backend‑as‑Service and LLMOps to simplify creation and deployment of generative AI applications.

Dify overview
Dify overview

Application Scenarios

Content creation and generation – automated writing, creative inspiration.

Intelligent customer service – chatbots, virtual assistants.

Data analysis and forecasting – data interpretation, predictive models.

Business automation – task automation, workflow optimization.

Personalized recommendation and marketing – user profiling, content recommendation.

Core Features

Multi‑model integration: supports hundreds of proprietary and open‑source LLMs (GPT, Claude, Llama, etc.) and any OpenAI‑compatible model.

Prompt orchestration & IDE: visual prompt editor, comparison tools, text‑to‑speech extensions.

RAG pipeline: built‑in retrieval‑augmented generation for document‑based knowledge.

Agent framework: agents can call over 50 built‑in tools (Google Search, DALL·E, Stable Diffusion, WolframAlpha) and custom tools.

Workflow management: sequential, conditional, and parallel execution.

Model management: upload, configure, train, fine‑tune, and continuous LLMOps iteration.

Low‑code/no‑code UI: drag‑and‑drop design for non‑technical users.

Cloud and self‑hosted deployment: cloud service or Docker‑Compose/self‑hosted options.

API & SDK: easy integration into third‑party systems.

Data security: RAG pipeline and encryption protect private data.

Scalable and extensible architecture.

Dify architecture
Dify architecture

Preparation

Operating system: CentOS 7.9 (or any Linux/Windows). Minimum requirements: CPU ≥ 2 cores, RAM ≥ 4 GiB.

Docker Installation

curl -o /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo
yum install -y yum-utils device-mapper-persistent-data lvm2
yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo
yum install docker-ce -y

Configure Docker registry mirrors in /etc/docker/daemon.json (example JSON omitted for brevity).

systemctl start docker

Docker‑Compose Installation

Download the desired version (e.g., v2.33.1) from the official GitHub releases, rename, add execution permission and move to /usr/bin/:

mv docker-compose-linux-x86_64 docker-compose
chmod +x docker-compose
mv docker-compose /usr/bin/
docker-compose --version

Install Dify

git clone https://github.com/langgenius/dify.git

Enter the Docker directory, copy the example environment file, and start the services:

cd dify/docker/
cp .env.example .env
docker-compose up -d

Verify containers are running with docker ps. Access the web UI via the server’s address to confirm successful installation.

Dify running containers
Dify running containers
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DockerLLMInstallationDifyAI PlatformOpen-source
MaGe Linux Operations
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MaGe Linux Operations

Founded in 2009, MaGe Education is a top Chinese high‑end IT training brand. Its graduates earn 12K+ RMB salaries, and the school has trained tens of thousands of students. It offers high‑pay courses in Linux cloud operations, Python full‑stack, automation, data analysis, AI, and Go high‑concurrency architecture. Thanks to quality courses and a solid reputation, it has talent partnerships with numerous internet firms.

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