Dify

Dify Cloud · Self-hosting · Documentation · Dify edition overview

Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features:

Quick start

Before installing Dify, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4 GiB

The easiest way to start the Dify server is through Docker Compose. Before running Dify with the following commands, make sure that Docker and Docker Compose v2.24.0 or later are installed on your machine:

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

After running, you can access the Dify dashboard in your browser at http://localhost/install and start the initialization process.

Seeking help

Please refer to our FAQ if you encounter problems setting up Dify. Reach out to the community and us if you are still having issues.

If you'd like to contribute to Dify or do additional development, refer to our guide to deploying from source code

Key features

1. Workflow: Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.

2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama3, and any OpenAI API-compatible models. A full list of supported model providers can be found here.

3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app.

4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats.

5. Agent: Autonomous agents with a sandbox of their own: they run commands, install software, and handle files to get open-ended tasks done. Describe the agent you want and it builds itself. Give it skills, connect tools from Dify Marketplace, MCP servers, or your own APIs, and put it to work as a chat app or as a step in any workflow.

6. LLMOps: Monitor and analyze application logs and performance over time. You could continuously improve prompts, datasets, and models based on production data and annotations.

7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.

Using Dify