Building AI Applications with Dify Low-Code Platform

Introduction to Dify

Dify is an open-source LLM application development platform that provides a visual orchestration interface and supports core features such as knowledge bases, Agent workflows, and model management. Its goal is to enable AI application development without writing code, simply through drag-and-drop and configuration.

Core Features

• Visual Orchestration: Drag-and-drop workflow designer
• Knowledge Base Management: Supports building knowledge bases from multiple document formats
• Agent Workflows: Build AI Agents that can make autonomous decisions
• Model Management: Supports multiple models like DeepSeek, OpenAI, Claude
• Application Publishing: One-click publishing as a web app or API

Docker Deployment

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

# Copy environment variable configuration
cp .env.example .env

# Edit the .env file to configure key parameters
# DEEPSEEK_API_KEY=your-key
# SECRET_KEY=your-secret

# Start all services
docker compose up -d

# Access http://localhost:3000

Creating Your First AI Application

Steps:

1. Create an Application: In the Dify console, select "Create Application" and choose the "Chat Assistant" type
2. Configure the Model: In "Model Settings", select DeepSeek as the conversation model
3. Write Prompts: In "Prompt Orchestration", write system prompts to define the AI's role and behavior
4. Add a Knowledge Base: Upload documents to create a knowledge base, enabling the AI to answer questions based on your documents
5. Add Tools: In "Tools", configure API calls, code execution, and other tools
6. Test and Debug: Test the application in the preview window on the right
7. Publish: Click "Publish" to get the application link or API endpoint

Building a Knowledge Base Q&A Application

The knowledge base is one of Dify's most powerful features:

1. Create a new knowledge base on the "Knowledge Base" page
2. Upload documents (supports PDF, Word, TXT, Markdown, etc.)
3. Select the embedding model and segmentation strategy
4. Wait for vectorization to complete
5. Associate the knowledge base in the application

Dify supports multiple retrieval modes: high-precision mode (ensures quality), hybrid mode (balances quality and speed), and economical mode (prioritizes speed).

Dify vs. Self-Developed

Summary

Dify is suitable for quickly validating ideas, building internal tools, and MVP products. When deep customization or integration with complex business logic is needed, consider self-developing with frameworks like LangChain.