Dify for Cloudron

An open-source LLM app development platform for building AI agents, RAG pipelines, and workflow automations.

NOTE : Dify v1.17 with Agent V2 might be a breaking change if you have previous v1.16 installation

What is Dify?

Dify is a visual platform for developing applications powered by large language models. It provides:

• Visual Workflow Builder — Drag-and-drop interface for creating AI workflows with LLM nodes, RAG pipelines, conditionals, loops, and tool integrations
• Agent Framework — Build autonomous agents with tool use, iterative reasoning, and human-in-the-loop support
• RAG Engine — Built-in retrieval-augmented generation with document upload, chunking strategies, and vector search (powered by pgvector)
• Plugin Ecosystem — Extend functionality with community plugins for tools, models, and integrations
• Multi-Model Support — Connect to OpenAI, Anthropic, Azure, local models (Ollama/LocalAI), and 50+ providers
• Collaboration — Team workspaces, role-based access, version control, and publish/deploy workflows as APIs

Package Features

• Self-Hosted — Full control over data, models, and infrastructure
• PostgreSQL + pgvector — Integrated vector database for RAG workflows
• Redis — Caching and Celery task queues
• Plugin Marketplace — Browse and install community plugins directly from the UI
• Code Execution — Secure sandboxed Python/JavaScript code nodes
• Playwright Integration — Web scraping and browser automation via bundled Playwright server

What's New in v1.17.0

• Agent V2 Enabled — Full support for autonomous agents with tool use, iterative reasoning, and human-in-the-loop workflows
• Workspace Skills — Create reusable, versioned capabilities with code and tool definitions that agents can discover and invoke
• Home Snapshots — Agent builds capture sandbox state for consistent restarts from known configurations
• E2B Sandbox Backend — Optional cloud-based sandbox execution for agent code (local sandbox enabled by default)
• Reusable LLM Variables — Define shared provider/model configurations once and reference from any LLM node
• Conversation Cleanup — Automated background task for managing old conversations
• Context-Aware History Compaction — Long agent conversations stay within model context limits

System Requirements

• Memory: 6GB minimum (8GB+ recommended for Agent V2 workflows)
• Storage: 10GB+ for application data and uploaded documents
• Database: PostgreSQL with pgvector (provisioned automatically via Cloudron addon)
• Cache: Redis (provisioned automatically via Cloudron addon)

Getting Started

1. Install from Cloudron app store
2. Open the app and complete the setup wizard to create your admin account
3. Configure LLM providers in Settings → Model Providers
4. Create your first workflow in Studio → Create from Blank
5. Test with a simple workflow: Start → LLM → End

Documentation

• Dify Official Docs
• Workflow Orchestration Guide
• Plugin Development
• Community Apps Support

Support

• Issues: Report on GitHub or Cloudron forum
• Community: Dify Discord | Cloudron Forum