DifyOpen-source platform for building and orchestrating LLM apps with built-in RAG and agent workflows.

5.0 (5)

Reviewed by Daniel Nikulshyn·Updated May 2026

Open Source LLM Platform RAG Agents Workflow Builder Self-Hosted Developer Tools Observability

Overview

Dify is an open-source development platform designed to simplify how teams build, deploy, and manage applications powered by large language models. It combines a visual workflow builder, prompt engineering tools, and a retrieval-augmented generation (RAG) pipeline so developers can move from prototype to production without stitching together multiple services. The platform supports a wide range of model providers, includes an agent framework for tool use and multi-step reasoning, and offers observability features to monitor usage, costs, and quality. Because it can be self-hosted, Dify appeals to organizations that need control over data, infrastructure, and compliance while still benefiting from a modern LLMOps toolchain. Typical use cases include internal knowledge assistants, customer support bots, content generation pipelines, and custom AI products that need to combine private data with commercial or open-source models.

Key features

Visual LLM workflow builder
Retrieval-augmented generation pipeline
Agent framework with tool integrations
Prompt management and versioning
Multi-model provider support
Usage analytics and observability

Pricing

Model: Free
Category: AI Agents Platform
Rating: 5.0 / 5 (5)

Use cases

Build RAG-powered knowledge assistants

Use the built-in retrieval-augmented generation pipeline and knowledge base tools to create chatbots that answer questions grounded in internal documents.

Prototype and deploy LLM apps visually

Design prompts and multi-step LLM workflows in the visual builder, then move from prototype to production without integrating multiple separate services.

Orchestrate multi-step AI agents

Leverage the agent framework with tool integrations to build assistants that reason across steps and call external tools for complex tasks.

Self-host LLM apps for compliance

Deploy Dify on your own infrastructure to retain control over data and meet compliance needs while still using a wide range of LLM providers.

Pros & Cons

Pros

Open-source with self-hosting options
Visual workflow and prompt orchestration
Built-in RAG and knowledge base tools
Supports many LLM providers and models
Active community and frequent updates

Cons

Self-hosting requires technical setup and maintenance
Advanced features have a learning curve
Some enterprise capabilities are gated behind paid tiers

Reviews

5.0

Average from 5 ratings.

Camille Laurent

May 3, 2026

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on agent framework with tool integrations, and visual workflow and prompt orchestration caught me off guard. Self-hosting requires technical setup and maintenance is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Esther Adeyemi

Mar 14, 2026

Solid for our team

We rolled this out across the team last quarter and open-source with self-hosting options. Usage analytics and observability fits neatly into how we already work, and usage analytics and observability removed a step we used to do by hand. Self-hosting requires technical setup and maintenance, which is the main caveat, but it has held up under daily use.

Pierre Dubois

Dec 9, 2025

Does the job

Pretty happy overall. Multi-model provider support just works and active community and frequent updates. Self-hosting requires technical setup and maintenance can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Nadia Petrova

Jul 24, 2025

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on prompt management and versioning, and built-in RAG and knowledge base tools caught me off guard. Advanced features have a learning curve is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Liam O’Connor

Jun 13, 2025

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on usage analytics and observability, and supports many LLM providers and models caught me off guard. Advanced features have a learning curve is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Q&A

What are common use cases for Dify, and how steep is the learning curve?

Typical use cases include internal knowledge assistants and customer-facing applications built on RAG and agent workflows. Basic prototyping is approachable via the visual builder, but advanced features like agent tool use, prompt versioning, and observability have a learning curve.

Asked by Diego Fernández · Sep 18, 2025

Which LLM providers and models does Dify support?

Dify offers multi-model provider support, allowing you to connect a wide range of LLM providers and switch between models within the same workflows. This flexibility is useful for comparing outputs, optimizing costs, or meeting provider-specific compliance requirements.

Asked by Carlos Mendoza · Aug 21, 2025

Can I self-host Dify, and what trade-offs come with that?

Yes, Dify is open-source and supports self-hosting, which gives you control over data, infrastructure, and compliance. The trade-off is that self-hosting requires technical setup and ongoing maintenance, so teams without DevOps capacity may prefer a managed deployment.

Asked by Camille Laurent · Jul 19, 2025