dify
https://github.com/langgenius/dify
📊 Stats
⭐ Stars: 134,758
📝 Language: TypeScript
📝 Description: Production-ready platform for agentic workflow development.
⭐ Star Growth (12 months)
🔬 Research Notes
Stats
Description
Production-ready platform for agentic workflow development.
Topics
agent, agentic-ai, agentic-framework, agentic-workflow, ai, automation, gemini, genai, gpt, gpt-4, llm, low-code, mcp, nextjs, no-code, openai, orchestration, python, rag, workflow
Research Summary
Key Features
Architecture
Use Cases
Assessment
README Excerpt
```
alt="chat on Discord">
alt="join Reddit">
alt="follow on X(Twitter)">
alt="follow on LinkedIn">
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](https://www.comet.com/docs/opik/integrations/dify), [Langfuse](https://docs.langfuse.com), and [Arize Phoenix](https://docs.arize.com/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](docker/docker-compose.yaml). Before running Dify with the following commands, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine:
```bash
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](http://localhost/install) and start the initialization process.
Seeking help
Please refer to our [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs) if you encounter problems setting up Dify. Reach out to [the community and us](#community--contact) 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](https://docs.dify.ai/getting-started/install-self-hosted/local-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](https://docs.dify.ai/getting-started/readme/model-providers).
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:
```
---
*Researched: 2026-03-28*