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.

156.1k
Stars
+37.5k
Gained
31.7%
Growth
TypeScript
Language

💡 Why It Matters

Dify addresses the challenge of building and deploying complex AI workflows by providing a collaborative workspace that supports various AI models and tools. This open source tool for engineering teams is particularly beneficial for ML and AI teams looking to streamline their processes from prototype to production without the need to rebuild their stack. With a maturity level that indicates it is production-ready, Dify has gained significant traction, evidenced by its impressive growth of 31.7% in stars over 311 days. However, it may not be the right choice for teams with very specific or niche requirements that are not covered by its framework.

🎯 When to Use

Dify is a strong choice when teams need a versatile platform for building agentic workflows and RAG pipelines quickly and efficiently. Teams should consider alternatives if they require highly specialised features that Dify does not support or if they prefer a different architectural approach.

👥 Team Fit & Use Cases

This tool is ideal for roles such as ML engineers, data scientists, and AI developers who need to collaborate on complex projects. It is commonly integrated into products and systems that involve automation, AI-driven decision-making, and workflow management.

🎭 Best For

⚖️ Compare With

🏷️ Topics & Ecosystem

agent agentic-ai agentic-framework agentic-workflow ai automation claude deepseek genai gpt llm low-code mcp nextjs no-code openai python skills workflow

📊 Activity

Latest commit: 2026-09-17. Over the past 310 days, this repository gained 37.5k stars (+31.7% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.