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.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
4 releases in the last 90 days, the latest 1 day ago, with 457 contributors on GitHub.
Peaked at #1 in the weekly ranking the week of Dec 21, its best in the past year.
Use Cases & Benefits
- Build agentic AI workflows and retrieval-augmented generation pipelines with rich model and tool integrations on a collaborative workspace.
- Enables seamless transition from prototype to production with cloud, VPC, or self-hosted deployment without rebuilding the stack.
- Use for creating complex AI workflows combining multiple LLMs and tools with a visual canvas interface.
- Use for deploying scalable LLM applications in enterprise environments with observability and model management features.
- Use for integrating AI agents with pre-built tools like Google Search and DALL·E into custom business logic via APIs.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Other
GitHub could not identify this license; read the LICENSE file before depending on it.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
- License not identified by GitHub; read the LICENSE file before depending on it.
General guidance from repository metadata, not legal advice. How we score
From the README
Dify is an open-source platform for developing LLM applications. Its intuitive interface combines agentic AI workflows, RAG pipelines, agent capabilities, model management, observability features, and more—allowing you to quickly move from prototype to production.
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 are installed on your machine:
After running, you can access the Dify dashboard in your browser at http://localhost/install and start the initialization process.
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
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+7,704 stars over 80 days across 13 snapshot days; best day +105 on Sep 14.
Forks
25.4K+1.3K
Open issues
1.2K+246
Compared with peers in AI Agents
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| morluto/rea | 450.0K | +22.9K | 75 | 16 days ago |
| vercel-labs/agent-desktop | 21.4K | +8.7K | 75 | 5 days ago |
| milind-soni/OpenMausBot | 20.6K | +8.4K | 75 | today |
| stablyai/orca | 121.4K | +6.7K | 75 | today |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| langgenius/dify | 160.5K | — | 65 | 1 day ago |
| Category median | 115.8K | +8.4K | 75 | — |
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