Dify
Visual platform for building LLM apps, RAG chatbots, agents and workflows.
Activity data comes from GitHub and was last refreshed Oct 22, 2026.
What it does
Dify is a web console where you design chatbots, knowledge-base Q&A apps, agents and multi-step AI workflows, then publish them for your team or call them through an API. It connects to hosted model providers or self-hosted models, so the AI itself can stay outside or inside your network.
Where it fits in a 10–200 person business
- Customer-support bot answering from your product manuals and FAQ
- Internal assistant that drafts quotes or emails from a template workflow
- One central place where non-developers build and share small AI tools
These use cases are our editorial suggestions, not claims made by the project.
License: can a business use it?
| License | Dify Open Source License (modified Apache-2.0) |
|---|---|
| Type | Custom / conditional: Apache- or BSD-based with extra conditions (branding, multi-tenant SaaS, derivatives). |
| Internal business use | Allowed under the license text |
| What to watch | Commercial use is allowed, including as a backend for your own apps. Extra conditions: you may not run a multi-tenant service (one tenant = one workspace) without written permission, and you may not remove or modify the Dify logo or copyright in the frontend. |
This is a plain-English summary of the license text, not legal advice. Third-party models you run with it have their own licenses.
Hardware requirements
| Minimum | 2 vCPU · 4 GB RAM |
|---|---|
| Recommended | Not published |
On macOS, Dify asks for a Docker VM with at least 2 vCPUs and 8 GiB of memory.
Source: docs.dify.ai/en/self-host/deploy/quick-start/docker-compose
Estimated monthly hosting cost
| Minimum spec | 2 vCPU · 4 GB RAM → CPX22 (2 vCPU, 4 GB, 80 GB disk) €19.99/mo |
|---|
How we got this: we took the cheapest Hetzner Cloud Regular Performance (shared AMD vCPU) plan with at least the RAM and vCPU the project lists, using prices read from www.hetzner.com/cloud/regular-performance on 2026-10-22. "From" monthly price cap shown by Hetzner, excluding VAT. Prices vary by location. Covers the server only; it excludes LLM API usage, backups, extra storage, GPUs and your time. Disk is not matched; add a volume if you need more than the plan includes.
How to deploy
Method: Docker Compose
git clone https://github.com/langgenius/dify.git
cd dify/docker
cp .env.example .env
docker compose up -d
# then open http://localhost/installFrom the official instructions: github.com/langgenius/dify#quick-start. Always check the source for the current version before you run it.
Known gotchas
Alternatives in AI app & agent builders
- Langflow Visual builder for AI agents and RAG flows that you can deploy as APIs or MCP servers. Compare Dify vs Langflow
- Flowise Drag-and-drop builder for LLM agents and chatflows (archived August 2026).
- Coze Studio Open-source edition of ByteDance's Coze agent-building platform. Compare Coze Studio vs Dify
Facts on this page were checked against the project's own repository and docs on 2026-10-22. Spotted something out of date? Tell us.