Dify

Open-source LLMOps platform for building and deploying AI applications visually

Workflow Automation AI & Machine Learning Low-Code & No-Code dify.ai

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Founded

2023

Starting Price

Free

About Dify

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.

Pros & Cons

Pros

Fully open-source and self-hostable for complete data control
Intuitive visual workflow builder with drag-and-drop canvas
Built-in RAG pipeline and knowledge base — no external setup needed
LLM-agnostic: switch between OpenAI, Anthropic, Llama, and more easily
Fast prototyping — go from idea to MVP in hours with prebuilt patterns
One-click API generation for deploying any workflow
Strong observability with full logs, version control for AI logic, and cost tracking
Active open-source community with 34,000+ GitHub stars

Cons

Cloud version has restrictive variable size limits that break real-world workflows
Missing core logic operators (e.g., 'in' / 'includes' list checks) requiring awkward workarounds
No hidden variable injection at chat start, limiting personalization use cases
Limited front-end capabilities — primarily a backend/orchestration platform
Documentation can lag behind rapidly shipping features
Enterprise governance features (RBAC, SSO, audit) still maturing on the cloud version
Advanced agentic workflows have a learning curve for non-technical users

Key Features

Visual Workflow Builder

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.

RAG Pipeline & Knowledge Base

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.

Agentic AI with Agent Node

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.

Multi-Model & LLM-Agnostic

Connect to and switch between any LLM including OpenAI, Anthropic, Llama, Azure OpenAI, Hugging Face, Replicate, and more from a unified interface.

One-Click API Deployment

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.

Plugin Marketplace & MCP Support

Expand capabilities with plugins from the marketplace, and publish Dify workflows and agents as standard MCP servers for broad client accessibility.

Observability & Monitoring

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.

Self-Hosting & Cloud Options

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.

Pricing

Sandbox

Free/month

200 message credits
50 MB knowledge storage
1 workspace
1 team member
Basic app limits
Community support

Best For

RAG Chatbots & Knowledge Base Assistants

Build customer support or internal knowledge assistants that retrieve answers from your documents, manuals, or ticket history with built-in RAG pipelines.

AI Agent Automation

Create autonomous AI agents that call external APIs, query databases, run code, and make decisions without human intervention using the Agent Node.

LLM App Prototyping

Rapidly prototype AI-powered product features and internal tools in hours using prebuilt workflow patterns, then deploy to production via one-click API generation.

Multi-Model Evaluation & Switching

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.

Content & Marketing Automation

Automate content generation workflows — ad copy, summaries, script assistants — by combining LLM nodes with conditional logic and external data sources.

Self-Hosted Enterprise AI Infrastructure

Deploy Dify on private infrastructure to build and manage AI applications while maintaining full data sovereignty and meeting enterprise compliance requirements.