Complete Dify Tutorial: Open-Source Platform for Building AI Applications

Dify is an open-source platform that enables developers to build Large Language Model (LLM) powered applications quickly and efficiently. With Dify, you can create chatbots, AI workflows, RAG (Retrieval-Augmented Generation) applications, and AI agents without writing complex infrastructure code from scratch.

The platform provides a visual interface for designing AI workflows, managing prompts, and integrating various LLM models such as OpenAI GPT, Anthropic Claude, Google Gemini, and other open-source models. Dify is ideal for developers who want to focus on the business logic of their AI applications without getting bogged down in infrastructure complexity.

In this tutorial, we will learn how to install Dify, create your first AI application, build complex workflows, implement RAG, and follow best practices for production deployment.

Why Choose Dify?

Before diving into implementation, let's understand why Dify has become a popular choice among AI developers:

Visual Workflow Builder: Design AI workflows with drag-and-drop without writing boilerplate code

Multi-Model Support: Supports 50+ LLM models from various providers in a single platform

Integrated RAG Pipeline: Built-in knowledge base features for building RAG applications

API-First Design: Every application automatically gets an API endpoint ready for use

Self-Hosted: Can be deployed on your own servers for full control over data and privacy

Observability: Complete monitoring and logging for every request and response

Installation and Setup

Prerequisites

Ensure your system has the following:

• Docker and Docker Compose installed
• Minimum 4GB RAM available
• Git for cloning the repository

Installation with Docker Compose

The easiest way to run Dify is using Docker Compose:

# Clone the Dify repository
git clone https://github.com/langgenius/dify.git
cd dify/docker

Copy the environment file
cp .env.example .env

Start all services
docker compose up -d

After all containers are running, open your browser and navigate to http://localhost/install to complete the initial setup. You will be prompted to create an admin account with email and password.

Configuring Model Providers

After logging in, the first step is to configure model providers. Go to Settings > Model Providers and add API keys for the models you want to use:

OpenAI: sk-xxxxx (for GPT-4, GPT-3.5)
Anthropic: sk-ant-xxxxx (for Claude)
Google: AIzaSyxxxxx (for Gemini)

Dify also supports local models through Ollama or vLLM. To use Ollama:

# Make sure Ollama is running
ollama serve

Pull the desired model
ollama pull llama3.1
ollama pull mistral

In Dify, add Ollama as a model provider with the URL http://host.docker.internal:11434.

Creating Your First Chat Application

Application Types in Dify

Dify provides several application types:

Chatbot: Interactive conversational applications

Text Generator: Generate text based on input

Agent: AI that can use tools and make decisions

Workflow: Complex AI workflows with multiple steps

Creating a Simple Chatbot

Click Create App and select Chatbot

Name the application, for example "Customer Support Bot"

Select the model to use (e.g., GPT-4)

Write a system prompt:

You are a friendly and professional customer support assistant for a technology company.
Answer customer questions clearly and concisely.
If you don't know the answer, direct the customer to contact the support team via email.
Always use polite and easy-to-understand language.

Click Publish to deploy the application

Accessing via API

Every Dify application automatically gets an API endpoint. You can access it with:

import requests

APIBASE = "http://localhost/v1"

APIKEY = "app-xxxxxxxxxxxx"  # From Settings > API Access

response = requests.post(