- About
- LLMOps platform to create, deploy, and manage AI-native applications.
- Catalogue
- No. 021
- Category
- Development
- Founded
- 2023, San Francisco, California, USA
- GitHub stars
- ★ 158k

Overview
Dify is an open-source LLMOps platform that enables developers to create, deploy, and manage AI-native applications with ease. It provides tools for prompt engineering, visual workflow design, and seamless integration with various AI models, making it simpler to build and operate production-ready AI applications.
What it does well
Dify offers a user-friendly interface for prompt engineering and AI application development. It supports multiple LLM providers, provides built-in prompts and plugins, and offers features like conversation management and dataset creation. The platform also includes analytics and monitoring tools to help optimize AI application performance.
Why it’s in the collection
Dify stands out for its comprehensive approach to AI application development. It bridges the gap between prompt engineering and application deployment, offering a full-stack solution for LLMOps. Its visual interface makes it accessible to both developers and non-technical users, while its extensibility and support for multiple AI models provide the flexibility needed for diverse use cases. As an open-source platform, it benefits from community contributions and ensures transparency in AI development.
On GitHub
- Stars
- 158,388
- Forks
- 25,043
- Commits
- 14,127
- Repository
- langgenius/dify
Languages
- TypeScript 50.8%
- Python 44.5%
- MDX 2.6%
- Other 2.1%
Compared with
LangchainPopular framework for developing LLM applications, but requires more coding and lacks a visual interface.
OpenAI GPTPowerful language model, but more focused on API access rather than full application development.
Hugging FaceOffers a wide range of models and tools, but can be more complex for building complete applications.
Anthropic ClaudeAdvanced AI model with strong capabilities, but less focused on the application development lifecycle.



