Features
- Visual workflow builder for LLM applications
- RAG pipeline with built-in document processing
- Agent framework with tool integration
- Prompt IDE for testing and iteration
Pros
- No-code/low-code interface for AI applications
- Built-in RAG without external vector store
- Self-hostable with Docker Compose
Cons
- Less flexible than code-first frameworks
- Performance overhead from abstraction layer
- UI-centric approach limits advanced customization
Overview
Dify is an open-source platform for building LLM-powered applications through a visual interface. It combines a workflow builder, RAG pipeline, agent framework, and prompt IDE into a single platform that enables both developers and non-technical users to create AI applications.
The visual workflow builder lets you design complex LLM applications by connecting nodes on a canvas: input processing, LLM calls, conditional logic, tool execution, and output formatting. This visual approach makes it easy to understand and iterate on application logic without writing code.
Dify includes a built-in RAG pipeline that handles document uploading, chunking, embedding, and retrieval without requiring an external vector store. For teams that need custom infrastructure, it also supports external vector stores like Pinecone, Qdrant, and Weaviate.
When to Use
Choose Dify when you need to quickly prototype LLM applications or when non-technical team members need to build and manage AI workflows. For production systems requiring maximum flexibility, code-first frameworks like LangChain may be more appropriate.
Getting Started
git clone https://github.com/langgenius/dify.git
cd dify/docker
docker compose up -d
# Open http://localhost:3000