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@langgenius/dify

LLM app platform for workflows, RAG, and agents

Dify is a workspace for building LLM apps with visual workflows, RAG pipelines, and agent tools. It connects to many model providers, lets you manage prompts and app behavior, and includes observability so you can tune what ships.

155,349 stars25k forksTypeScriptUpdated 6d ago
Who it's for

Builders who want one place to design, test, and deploy agentic apps with model and tool support.

What it delivers

You can move from prototype to production without rebuilding your LLM app stack.

What it does

Visual workflow builder

Build and test AI workflows on a canvas.

RAG pipeline

Ingest documents and retrieve context from PDFs, PPTs, and other common formats.

Agent support

Define agents with function calling or ReAct and connect built-in or custom tools.

Model management

Work with many hosted and self-hosted model providers and OpenAI-compatible APIs.

Prompt IDE

Create prompts, compare model behavior, and add chat features like text-to-speech.

Observability

Track logs and performance, then improve prompts, datasets, and models from production data.

API access

Use the platform through APIs so it can fit into your own app logic.

How to get it

  1. 1The easiest way to start the Dify server is through Docker Compose. Before running Dify…
    cd dify
    cd docker
    cp .env.example .env
    docker compose up -d

README

cover-v5-optimized

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

Static Badge Static Badge chat on Discord join Reddit follow on X(Twitter) follow on LinkedIn Docker Pulls Commits last month Issues closed Discussion posts LFX Health Score LFX Contributors LFX Active Contributors

README in English 繁體中文文件 简体中文文件 日本語のREADME README en Español README en Français README tlhIngan Hol README in Korean README بالعربية Türkçe README README Tiếng Việt README in Deutsch README in Italiano README em Português do Brasil README Slovenščina README in বাংলা README in हिन्दी

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.

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 capabilities: You can define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools for the agent. Dify provides 50+ built-in tools for AI agents, such as Google Search, DALL·E, Stable Diffusion and WolframAlpha.

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

  • Cloud
    We host a Dify Cloud service for anyone to try with zero setup. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls in the sandbox plan. If you run into issues with Dify Cloud, 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 for enterprise / organizations
    We provide additional enterprise-centric features. Send us an email to discuss your enterprise needs.

Staying ahead

Star Dify on GitHub and be instantly notified of new releases.

star

Advanced Setup

For custom configuration, observability, and deployment options, see Advanced Setup.

Contributing

Dify welcomes contributions of all kinds:

Contributors

Dify contributors

Community & contact

Choose the channel that best fits your question:

  • GitHub Discussions: Get help, share feedback, and propose ideas.
  • GitHub Issues: Report reproducible bugs and track engineering work. Read the Contribution Guide before opening one.
  • Discord: Chat in real time, share your apps, and connect with other Dify users.
  • X: Follow Dify for release news and project updates.

Star History

Star History ChartStar History Chart

Security disclosure

To protect your privacy, please avoid posting security issues on GitHub. Instead, report issues to security@dify.ai, and our team will respond with detailed answer.

License

This repository is licensed under the Dify Open Source License, based on Apache 2.0 with additional conditions.

Files in the repo

Repository payload42 top-level entries
  • .agents
  • .claude
  • .devcontainer
  • .github
  • .vite-hooks
  • .vscode
  • api
  • cli
  • dev
  • dify-agent
  • dify-agent-runtime
  • docker
  • docs
  • e2e
  • images
  • packages
  • scripts
  • sdks
  • web
  • .coveragerc
  • .dockerignore
  • .editorconfig
  • .gitattributes
  • .gitignore
  • AGENTS.md
  • AUTHORS
  • CLAUDE.md
  • codecov.yml
  • CONTRIBUTING.md
  • depot.json
  • eslint.config.mjs
  • knip.config.ts
  • LICENSE
  • lint.config.ts
  • Makefile
  • oxlint-suppressions.json
  • package.json
  • pnpm-lock.yaml
  • pnpm-workspace.yaml
  • README.md
  • SECURITY.md
  • vite.config.ts

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