How Does Dify Handle Multi-Model Switching Across LLM Providers?

Dify supports connecting to multiple LLM providers simultaneously including OpenAI, Anthropic, Azure OpenAI, Hugging Face, and local models. Users can switch, compare, and load-balance between providers directly within the workflow canvas without code changes.

Can Dify Be Fully Self-Hosted On Private Infrastructure?

Yes, Dify offers a complete self-hosted edition deployable via Docker Compose. Teams retain full control over data, model connections, and configurations. The self-hosted version includes nearly all features available on the cloud service.

What Is The Difference Between Chatflow And Workflow In Dify?

Chatflow is designed for conversational AI applications with memory and multi-turn dialogue support. Workflow handles sequential or branching task automation triggered by events, webhooks, or API calls, suitable for backend processing pipelines.

How Does Dify's RAG Knowledge Base Process And Retrieve Documents?

Dify ingests documents via batch upload or website scraping, chunks them, generates embeddings, and stores them in vector databases. It supports hybrid search combining semantic and full-text retrieval, plus a semantic rerank model for improved answer accuracy.

Does Dify Support Plugin Extensions And Third-Party Tool Integration?

Dify features a dedicated Marketplace where users can install plugins for tools, model providers, and external services. Developers can also build custom plugins and share them with the community through the Marketplace ecosystem.

Dify

Name: Dify
Availability: InStock
Author: LangGenius, Inc.

by LangGenius, Inc. • Menlo Park, CA, USA • Founded 2023

Open-Source Platform for Building Production-Ready Agentic AI Workflows

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4.1 /5

28 reviews

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Pricing

From $59/mo

What is Dify?

Dify is an open-source LLM application development platform built by LangGenius, Inc. It enables teams to build, deploy, and manage production-ready AI agents and agentic workflows through a visual drag-and-drop interface. The platform supports RAG (Retrieval-Augmented Generation) pipelines, multi-model orchestration across providers like OpenAI and Anthropic, and Backend-as-a-Service deployment.

Dify also includes built-in observability with LangSmith and Langfuse integration, a plugin marketplace, and full self-hosting capability via Docker. With over 100K GitHub stars, it is one of the most adopted open-source LLMOps platforms globally.

Dify — Open-Source Platform for Building Production-Ready Agentic AI Workflows Whether you're evaluating Dify for your team or comparing it to alternatives in the AI Development Tools category, this in-depth review covers everything: features, pricing, real user reviews, pros and cons, integrations, and direct comparisons against competitors.

Dify Demo Video

Key Features 8

Open-Source LLM App Development Platform With Visual Drag-and-Drop Workflow Builder

Build Production-Ready AI Agents With Multi-Step Reasoning and Tool Use

Built-In RAG Pipeline With Document Upload, Chunking, and Vector Search

Supports 300+ LLMs Including OpenAI, Anthropic, Google, and Local Models

No-Code Agentic Workflow Creation With Conditional Logic and Branching Nodes

Self-Hosting Support With Docker for Full Data Privacy and Control

Backend-as-a-Service With Ready-to-Use APIs for Quick App Deployment

Real-Time Observability Dashboard for Monitoring Model Performance and Logs

Who Is Dify For

1 Backend Developers Building LLM-Powered Applications

2 AI Engineers Orchestrating Multi-Agent Workflows

3 DevOps Teams Self-Hosting AI Infrastructure

4 Product Managers Prototyping Chatbots and AI Tools

5 Enterprise IT Teams Deploying Internal AI Assistants

6 Data Scientists Building RAG-Based Knowledge Systems

Pros & Cons

Pros 4 benefits

Fully Open-Source Codebase
Strong Multi-Model Provider Support
Active GitHub Community Contributions
Self-Hosting With Full Control

Cons 3 limitations

Cloud Variable Size Limitations
Steep Learning Curve Initially
Limited Priority Support Responsiveness

Frequently Asked Questions

5 questions

How Dify works

Dify is positioned as open-Source Platform for Building Production-Ready Agentic AI Workflows. Under the hood it ships 8 headline capabilities, including Open-Source LLM App Development Platform With Visual Drag-and-Drop Workflow Builder, Build Production-Ready AI Agents With Multi-Step Reasoning and Tool Use, Built-In RAG Pipeline With Document Upload, Chunking, and Vector Search, Supports 300+ LLMs Including OpenAI, Anthropic, Google, and Local Models, No-Code Agentic Workflow Creation With Conditional Logic and Branching Nodes and Self-Hosting Support With Docker for Full Data Privacy and Control. Together these features cover the core workflows most teams expect from a modern ai development tools, from initial setup through day-to-day production use.

Dify runs as a self-contained product, so you can adopt it without touching the rest of your stack — useful when you want to evaluate the tool in isolation before wiring up integrations.

Who is Dify for?

Dify is most useful for Backend Developers Building LLM-Powered Applications, AI Engineers Orchestrating Multi-Agent Workflows, DevOps Teams Self-Hosting AI Infrastructure and Product Managers Prototyping Chatbots and AI Tools. If your team falls into one of those buckets, the feature set lines up well with how you already work — you won't be forcing a square peg into a round hole.

Beyond the obvious use case, the product tends to attract users who want a low-friction starting point option in the ai development tools space.

Dify pricing explained

Dify runs on a freemium model. You get a usable free tier to evaluate the product, and you only pay when you outgrow the limits — usage volume, seat count, or premium features. Headline pricing: From $59/mo.

Across the AI Gear Base rubric, we score freemium pricing models on transparency, rate-limit honesty, and how predictable spend is at scale. Dify's freemium approach is standard for the category — useful for evaluation, but always re-check tier limits before you depend on the free plan.

Our verdict on Dify

Dify hasn't been rated by enough reviewers yet to publish an aggregate score. The strongest signal in those reviews is that fully open-source codebase. The most common complaint is that cloud variable size limitations — worth knowing before you commit, but rarely a deal-breaker for teams that already match the use case.

If you're evaluating Dify against alternatives, weigh it on the same 7-criteria rubric we apply to every tool: capability, integrations, pricing transparency, support, security posture, roadmap velocity, and community signal. Built by LangGenius, Inc., founded in 2023, the product has a clear track record you can verify before adopting it. The bottom line: Dify is a solid pick in the ai development tools category, and it deserves a spot on your shortlist if your workflow matches what it was built for.

Trusted Reviews

Verified Platforms

4.1 G2 (20) 4.8 Product Hunt

What's New

weekly

Workflow Stability and Knowledge Retrieval Fixes 1.13.3

Added variable-reference support for model parameters in LLM nodes, fixed streaming reliability issues, and preserved citation metadata in knowledge retrieval.

Mar 27

Hologres Support, Security Hardening, and Workflow Improvements 1.13.1

Added Hologres as a vector and full-text search backend, introduced edge context menu in workflow canvas, prevented SQL injection in vector-store queries, and added configurable send-key behavior for embedded chat.

Mar 10

View all updates

User Base

500K+ developers

Active Users

Security & Privacy

US, Global (Self-hosted anywhere)

SOC 2 Type I SOC 2 Type II ISO 27001:2022 GDPR Compliant

End-to-end encryption for data in transit and at rest Role-based access control (RBAC) Parameterized SQL to prevent injection attacks Credential clearing on plugin uninstall Ownership checks for conversation deletion APIs