Dify
Open-source LLM app development platform for building AI workflows, chatbots, and RAG pipelines with a visual editor and 50+ model provider integrations.
Dify is an open-source LLM application development platform founded in 2023 that enables teams to build AI-powered workflows, chatbots, and retrieval-augmented generation applications through a visual editor without writing backend infrastructure code. The project accumulated over 90,000 GitHub stars by 2025 and has been adopted by more than 100,000 teams globally, making it one of the most widely deployed open-source AI platforms available. Dify integrates with 50+ model providers including OpenAI, Anthropic, Llama, Mistral, and Qwen, and includes built-in RAG pipeline management with chunking and vector search, a prompt version control IDE, and one-click REST API publishing. The self-hosted version deploys via Docker Compose for teams with data privacy requirements, while Dify Cloud offers a managed free plan.
Key Features
- Visual workflow builder for multi-step AI pipelines with 50+ model provider integrations in a single canvas
- Built-in RAG pipeline for uploading documents, chunking, embedding, and vector search without custom setup code
- Prompt IDE with version control and A/B testing for iterating prompt templates across model providers
- One-click REST API publishing to expose any chatbot or workflow as a callable endpoint for external apps
- Agent framework with tool use, web search, and code execution for building autonomous task agents
- Self-hosted Docker Compose deployment for complete data control and on-premises infrastructure requirements
- 90,000+ GitHub stars with active community contributing model integrations and workflow template libraries
Use Cases
- Development teams building internal AI tools and knowledge bases without dedicated ML engineering resources
- Companies creating customer-facing AI chatbots with RAG over proprietary product documentation
- Non-technical teams prototyping AI workflows through a visual interface without writing application code
- Enterprises requiring self-hosted AI infrastructure with full data control and no third-party cloud dependency
Pros
- 90,000+ GitHub stars and 100,000+ teams confirm production readiness across a wide range of enterprise use cases
- Self-hosted Docker deployment provides full data control at no cost beyond underlying infrastructure
- Visual workflow builder enables non-developers to build RAG and agent pipelines without engineering support
Cons
- Hosted cloud plans at $59 per month are expensive compared to calling model APIs directly in application code
- Complex workflows generate large visual graphs that are harder to debug than the equivalent written code
- Plugin ecosystem is growing but less mature than LangChain for advanced custom integration requirements
Dify Alternatives
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Flowise
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