README

!cover-v5-optimized


  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. Install Docker with a running daemon, Docker Compose v2.35.0 or later, and OpenSSL.

For a new deployment, run the following commands from the repository root. For an existing deployment, preserve your .env and follow the upgrade guidance.

bash
cd docker
cp .env.example .env
openssl rand -hex 32


Open .env and set DIFY_AGENT_LOCAL_SANDBOX_AUTH_TOKEN to the generated value. Keep the default COMPOSE_PROFILES value for the bundled services. Service defaults load automatically; no additional configuration files are required.

From the same docker directory, start the services:

bash
docker compose up -d
docker compose ps --all


Once the services are running, open http://localhost/install to complete the initial setup. The one-time init_permissions service is expected to exit with code 0.

For optional settings and service overrides, see the Docker deployment guide.

 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.

!providers-v5

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

Top issues

Discussions

Latest release

Dify 1.19.0 brings nested workflow tracing to your observability tools. Follow a workflow into the Workflow Tools it calls, inspect the steps inside each invocation, and keep the LLM context alongside the execution tree.

This release also makes Workflow Tools portable with App packages, adds Skill Hub automation, and makes Agent files easier to upload and preview. The bundled plugin daemon is upgraded to 0.6.14-local.

Release highlights · Upgrade guide · Detailed changes



 Release highlights

 Nested workflow tracing

See what happens inside a Workflow Tool, all the way down to