Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
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:
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.
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:
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.
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
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.
Cloud
We host Dify Cloud so you can try Dify without managing a server. See the pricing page for current plans and usage allowances. If you run into issues, contact our Cloud support team.
Self-hosting Dify Community Edition
Quickly get Dify running in your environment with this starter guide.
Use our documentation for further references and more in-depth instructions.
Dify Enterprise
For organizations requiring self-hosting, SSO, RBAC Security and Enterprise Support SLAs, please fill out this form to speak to a solution representative.
Star Dify on GitHub and be instantly notified of new releases.
For custom configuration, observability, and deployment options, see Advanced Setup.
Dify welcomes contributions of all kinds:
Choose the channel that best fits your question:
Report vulnerabilities privately through GitHub Security Advisories, following our security policy. Do not disclose them in public issues, discussions, or pull requests.
This repository is licensed under the Dify Open Source License, based on Apache 2.0 with additional conditions.
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New version available.
