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langgenius dify

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.

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Stars

154,353

Popular Active

Forks

24,402

Watchers: 154,353

Repository Radar Score

66 / 100

Growth

7d
+0
30d
+0
%
0.0%

Not enough metric snapshots yet to chart growth for this repository.

Last observed: 1 week ago

Score breakdown

  • popularity 97
  • growth 0
  • activity 90
  • freshness 100
  • community 90

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README.md
View README on GitHub

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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.

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 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.

Created: Apr 12, 2023

Last push: Sep 3, 2026

Default branch: main

Latest release: 1.17.0

Top contributors

Languages

Share of the codebase by language, based on repository metadata from the host.

  • TypeScript 50.0%
  • Python 46.8%
  • JavaScript 1.9%
  • Go 0.5%
  • CSS 0.3%
  • HTML 0.2%
  • Shell 0.2%
  • Gherkin 0.1%
  • Makefile 0.0%
  • PowerShell 0.0%
  • Dockerfile 0.0%
  • PHP 0.0%
  • Mako 0.0%

Repository Radar analysis

Deterministic insights derived from public metadata and our observations — not personal testing or reviews.

Why this repository is interesting

  • High absolute popularity (154,353 stars) signals broad adoption.
  • Maintained recently (last push 2 weeks ago).

Who should use it

  • Developers working primarily with TypeScript
  • Teams exploring AI tooling, agents, or ML infrastructure
  • Frontend engineers comparing UI frameworks and tools

Potential use cases

  • Reference or evaluate TypeScript open-source approaches in this domain
  • Prototype AI/agent workflows or study reference architectures

Strengths

  • Recent repository activity
  • README present in our index
  • Declared license: Other
  • Substantial fork count (24,402) suggests reuse and contribution interest

Limitations / considerations

  • Insights are derived from public metadata and our observations — not a substitute for code review

What to watch

  • Re-check last push, issues, and releases on GitHub before production adoption

Strong signals: Strong community interest · Active maintenance

Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.

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