Dify How-To Guides
Build LLM apps, agents, and RAG chatbots with Dify. Covers cloud versus self-hosting, workflows, knowledge bases, connecting local models, and calling your app from code.
More guides
How to Use Ollama Local Models in Dify
Point a self-hosted Dify at a local Ollama server, register a model like Llama 3.1 or Qwen, and run your apps fully offline with no per-token cost.
How to Build a RAG Knowledge Base in Dify
Create a Knowledge base in Dify, upload and chunk your documents, embed them, and attach retrieval to a Chatflow so the model answers from your own content.
Dify vs n8n: Which Should You Use for AI Workflows
An honest comparison of Dify and n8n: Dify is an LLM app builder with a hosted UI and API, n8n is general automation with hundreds of integrations. When to pick each, and how to combine them.
How to Self-Host Dify in Production with Docker Compose
Clone Dify, bring it up with Docker Compose, set the production env values, put it behind a reverse proxy with HTTPS, and set up backups and upgrades.
Get Started
How to Get Started with Dify AI Platform
Install Dify locally with Docker, connect your first LLM provider, and have a working chatbot running in under fifteen minutes.
Dify Tutorial: Build Your First AI App (Complete Walkthrough)
A beginner walkthrough of Dify: what it is, cloud versus self-host, creating an app, picking an app type, adding a model, writing a prompt with variables, and publishing to get an API or embed.
Build Apps
How to Set Up an AI Code Review Workflow in Dify
Build a Dify workflow that takes a diff or code snippet and returns a structured review covering bugs, security, and style, then call it from CI or a git hook.
How to Build an AI Agent in Dify
Create a Dify agent that can call tools, search the web, and run multi-step tasks without writing orchestration code.
How to Build a RAG Chatbot with Dify
Upload your documents to Dify, configure retrieval-augmented generation, and deploy a chatbot that answers questions from your own knowledge base.