#44th of 48 in Agent platforms
Dify
Visual builder for LLM workflows, RAG pipelines and agents, with APIs
- Stars
- 159.4k
- License
- custom license
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
132,593 on 26 Mar 2026159,400 on 22 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Dify is an LLM app development platform with a visual workflow canvas, a prompt IDE, a RAG pipeline that extracts text from PDFs and PPTs, and agents that run in their own sandbox. Every app is exposed through an API. Model providers include GPT, Mistral, Llama3 and any OpenAI-compatible endpoint. It runs via Docker Compose or as the hosted Dify Cloud.
Who it is for: Teams building and self-hosting LLM apps, RAG and agent workflows
Ranked among open-source alternatives to Copilot Studio (#4 of 10).
Strengths
- Visual workflow canvas, prompt IDE and RAG pipeline in one platform
- Every app exposes an API, so it works as a backend service
- Supports hundreds of LLMs plus any OpenAI API-compatible model
- Agents can use Marketplace tools, MCP servers or your own APIs
Weaknesses
- License is the Dify Open Source License (Apache 2.0 plus extra conditions)
- SSO, RBAC and support SLAs are in the Enterprise edition
- Docker Compose self-hosting needs at least 2 CPU cores and 4 GiB RAM
- Observability relies on external tools such as Opik, Langfuse and Arize Phoenix
What it needs
- RAM ≥ 4 GB
- no GPU
- Docker + Compose
- Needs Docker, Docker Compose v2.24.0+
- Models: GPT, Mistral, Llama3, OpenAI API-compatible models
- port 80
Quick answers
Is Dify open source?
Its code is public on GitHub under its own license terms; read them before you use it at work.
Can you run Dify with Docker?
Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.
Does Dify need a GPU?
No, it runs without one. Plan for at least 4 GB of RAM.
Head to head
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|---|---|---|
| 1 | AutoGPTRole-based AI agents coordinated by one lead agent, plus a visual workflow builder | 94 out of 100 |
| 2 | daily_stock_analysisLLM-driven daily analysis of watchlist stocks across six markets, pushed to chat apps | 94 out of 100 |
| 3 | LangflowVisual builder for AI agents and workflows, exposed as API or MCP server | 93 out of 100 |
| #5 | deer-flowAgent harness running sub-agents, memory and sandboxes with pluggable skills | 88 out of 100 |
| #6 | MulticaIssue board where coding agent CLIs are assigned work like teammates | 88 out of 100 |