
Open-source LLMOps platform for building and deploying AI applications visually
Dify is an open-source LLMOps platform that combines a visual workflow builder, RAG pipeline engine, AI agent framework, and model management into a single interface. It lets developers and teams go from AI prototype to production without boilerplate code, supporting self-hosting for full data control. Built by LangGenius, Dify powers over 130,000 AI applications across its cloud and self-hosted deployments.
Design AI pipelines by connecting nodes on a canvas — LLM calls, knowledge base retrievals, conditional branches, code execution blocks, HTTP requests, and more — without writing boilerplate code.
Built-in Retrieval-Augmented Generation pipelines let you ingest documents, chunk and clean text, and query your knowledge base to build grounded chatbots and internal assistants.
The Agent Node enables autonomous decision-making — choosing which tools to call, when to retrieve context, and when to respond — supporting both Function Calling and ReAct reasoning strategies.
Connect to and switch between any LLM including OpenAI, Anthropic, Llama, Azure OpenAI, Hugging Face, Replicate, and more from a unified interface.
Generate a production-ready API from any workflow in one click, with built-in logs showing inputs, outputs, token consumption, and per-node durations for monitoring.
Expand capabilities with plugins from the marketplace, and publish Dify workflows and agents as standard MCP servers for broad client accessibility.
Build customer support or internal knowledge assistants that retrieve answers from your documents, manuals, or ticket history with built-in RAG pipelines.
Create autonomous AI agents that call external APIs, query databases, run code, and make decisions without human intervention using the Agent Node.
Rapidly prototype AI-powered product features and internal tools in hours using prebuilt workflow patterns, then deploy to production via one-click API generation.
Test and compare outputs from multiple LLMs (OpenAI, Anthropic, open-source) side-by-side to pick the best model for each use case without code changes.
Best overall no-code AI framework for teams building RAG applications, chatbots, and AI agents — especially with the free self-hosted option
Best open-source AI agent framework — the complete LLMOps platform for developer teams building knowledge-grounded AI applications
Full activity logging with version control for AI logic, cost tracking, usage auditing, and the ability to replay and compare past runs for debugging and experimentation.
Deploy Dify on your own infrastructure using Docker for full data control, or use the managed cloud service — both options support the same feature set.
Automate content generation workflows — ad copy, summaries, script assistants — by combining LLM nodes with conditional logic and external data sources.
Deploy Dify on private infrastructure to build and manage AI applications while maintaining full data sovereignty and meeting enterprise compliance requirements.

AI-powered low-code backend and workflow builder