What VPS configuration does Dify need?

Dify requires at least 4 GB of RAM and 2 vCPU. It starts PostgreSQL, Redis and a vector database — plan for 8 GB of RAM for comfortable production use.

Dify vs n8n: what's the difference?

Dify specializes in LLM applications (RAG, AI agents). n8n is a general-purpose automation tool that can also integrate LLMs. They are complementary.

Can Dify be used with local models?

Yes. Dify supports Ollama — you can connect local models (Llama, Mistral, Gemma) running on the same VPS or on a separate server.

Yes. Dify Community Edition is open source (Apache 2.0). There is a Cloud version hosted by Dify.ai, but self-hosting on a VPS is free.

Build, host and run AI solutions.

Dify

Build LLM applications with drag-and-drop — chatbots, agents, RAG pipelines — no backend required.

4 GB (8 GB recommended) RAM 2 vCPU Port 80 Available

Source code

Tech stack

DockerPythonPostgreSQLRedisWeaviate

Minimum RAM4 GB (8 GB recommended)

Minimum CPU2 vCPU

Default port80

Compatible OSubuntu-24.04

Dify is an open-source LLM application development platform that lets you build chatbots, autonomous agents and RAG pipelines without writing any backend code. Its visual interface lets you connect data sources, define conversational flows and deploy APIs in just a few minutes.

Self-hosted on a VPS, Dify gives you full control over your data, your prompts and your models. You can connect any LLM (OpenAI, Anthropic, Mistral, local Ollama models) and build professional AI applications without depending on third-party cloud infrastructure.

Key features

Visual studio to build LLM workflows without code

Native RAG: connect vector databases, PDFs, websites

Multi-model support: OpenAI, Claude, Gemini, Mistral, Ollama

One-click REST API deployment

LLM call monitoring and cost management

User and workspace management

When to use this solution?

1

Business chatbot

Build an intelligent assistant connected to your internal data — documentation, FAQs, CRM — without a single line of backend code.

2

Document processing pipeline

Automate the analysis, classification and summarization of documents by building a visual workflow.

3

Rapid AI prototype

Test your LLM application idea in a few hours before investing in custom development.

Deploy Dify on your VPS

Guide optimized for ServOrbit Cloud VPS.

01

Prepare the VPS

VPS with at least 4 GB RAM, Ubuntu 22.04. Install Docker and Docker Compose.

02

Clone and configure

Clone the Dify repository. Copy .env.example to .env and configure your secret key and your database connections.

03

Start the services

Run docker compose up -d from the docker/ folder. Dify starts up with PostgreSQL, Redis and Weaviate (vector database).

04

Expose over HTTPS

Configure Nginx as a reverse proxy to Dify's port 80. Obtain an SSL certificate with Certbot.

05

Connect your LLMs

In the settings, add your API keys (OpenAI, Anthropic…) or the URL of your Ollama instance. Create your first application from the studio.

Frequently asked questions

Dify is an open-source platform that lets you build LLM applications (chatbots, agents, RAG pipelines) through a visual interface, without coding a backend.

Complementary solutions

Artificial Intelligence

Activate Dify on your infrastructure.

Dedicated Cloud VPS — IPv4 included, European datacenter, support included. Your data never leaves your server.

Recommended configuration: 4 GB (8 GB recommended) RAM · 2 vCPU