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Dify

Dify is an LLM app development platform for building agents, RAG knowledge pipelines and visual workflows, then shipping them as web apps, APIs or MCP tools. Use the hosted Dify Cloud plans or self-host the Community Edition with Docker under its modified Apache 2.0 license.

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What is Dify?

Dify is an LLM app development platform for building agentic workflows, agents, knowledge pipelines and tool integrations on a visual canvas, then publishing the result as a web app, an API or an MCP-compatible tool. It is operated by LangGenius, Inc., a Delaware corporation, and comes in three editions that differ mainly in who runs the infrastructure.

  • Dify Cloud: hosted by Dify, so teams can build, test and launch AI apps without managing any servers.
  • Dify Enterprise: self-hosted or run inside a customer's own VPC, and pitched at organizations with procurement, security and audit requirements.
  • Community Edition: the public source repository, deployed with Docker on your own hardware. As captured on September 28, 2026, the homepage cited 157K+ stars on GitHub for this edition.

The practical choice is where Dify runs: Cloud plans meter credits, members, apps and storage per workspace, while the free self-hosted edition carries license conditions covered under Limitations.

Core features

Visual workflow canvas

As an agentic workflow builder, Dify assembles workflows from visual building blocks and AI prompts that define how an app thinks, retrieves data, makes decisions, uses tools, asks for human input and completes tasks.

  • Code node: runs custom Python or JavaScript, and both languages execute in secure sandboxes with access to common data-processing libraries.
  • Human Input node: pauses a workflow at key points to deliver a customizable request form. When the form is sent by email, anyone with the link can respond without a Dify account.
  • Triggers: a trigger starts a workflow automatically on a schedule or in response to events from external systems, instead of waiting for a user or an API call. Triggers are available for Workflow applications only.

Agents

An agent can be created by chatting with the builder or by configuring it manually. The same agent can then run as a standalone app, be embedded in a website, or be reused as an agent node inside a larger workflow.

Knowledge pipeline for RAG

Knowledge pipelines take files, websites, online documents and drives, then extract, clean, chunk and index the content and let you test retrieval before the knowledge base is connected to agents or workflows.

Models and integrations

Dify is model-agnostic. On Dify Cloud, built-in AI credits cover models from providers such as OpenAI, Anthropic, Gemini, xAI and Tongyi. One AI response is a single model call that counts once no matter how many tokens it uses. Model providers, tools, data sources and MCP integrations can be installed from the Marketplace or defined yourself. Packages can also come from any public GitHub repository by URL and version, or be uploaded locally as a .zip for private or internal integrations.

Publishing and monitoring

Publishing creates a web app and an API endpoint from the app's latest configuration. The web app can also be embedded on another site as a chat widget or inline frame. After launch, logs, user feedback, annotations, latency and usage data show how the app behaved.

Guide

Self-host the Community Edition with Docker Compose

For self-hosted Dify, the documented minimum for a Docker Compose deployment is a machine with at least 2 CPU cores and 4 GiB of RAM. Dify also requires Docker Compose 2.24.0 or later.

  1. Clone the Dify repository at the latest release tag and change into the dify/docker directory.
  2. Copy .env.example to .env; this file is where ports, storage, vector stores and feature options are customized later.
  3. Start the stack with docker compose up -d, then run docker compose ps and confirm that every container reports Up or healthy, while an exited init_permissions task is expected.
  4. Open /install on localhost or on your server's IP address to create the administrator account, then sign in at the root address.

Expose an app as an MCP server

  1. On the app's Access Point tab, switch on the MCP Server card, which is disabled by default and generates a unique server address when enabled.
  2. Add that address to the client: as an integration URL in Claude Desktop, or as an entry under mcpServers in a project's .cursor/mcp.json for Cursor.
  3. Treat the address as a secret, because the MCP Server URL contains authentication credentials, and regenerating it immediately disables the old one.

Use cases and examples

Dify's documentation and solution pages describe these patterns:

  • Scheduled reporting: a schedule trigger can, for example, generate a daily sales report every morning at 9 AM and email it to the team.
  • Event-driven processing: a webhook trigger can process new orders sent as HTTP requests from an e-commerce platform.
  • Industry workflows: solution pages cover assessment and testing, described as scaling item generation with multi-stage review, and professional services and audit, described as driving audit automation with agents and RPA.
  • Enterprise rollouts: the enterprise page reports that A.P. Møller-Maersk cut the time per AI app to 2 weeks, down from 4 months when self-built.
  • Faster workflow setup: the same page credits Kakaku.com / Tabelog with a workflow setup of 1 day that previously took a month.

Both figures are customer outcomes published by Dify, not independent measurements.

Who is it for

Dify's plans are each described for a type of team:

  • Individual developers and small teams: Professional is described as for independent developers and small teams building production AI apps.
  • Collaborating teams: Team is aimed at medium-sized teams needing collaboration and higher throughput.
  • Regulated or large organizations: Enterprise lists SSO via SAML/OIDC, fine-grained RBAC down to workflow level, SCIM provisioning and tamper-evident audit logs streamed to a SIEM.
  • Self-hosters and hobbyists: the Community Edition is described as for open-source enthusiasts, individual developers and non-commercial projects.

Inside a workspace, Dify separates builders from consumers with four roles — Owner, Admin, Editor and Normal — and only the Owner and Admin can manage roles, billing and models.

It fits poorly for reselling Dify as a multi-tenant service or shipping its frontend without the Dify logo, since both need Dify's permission.

Platforms

  • Browser: published web apps work on any device, adapt to screen size and need no app store approval or installation.
  • Your own servers: Dify runs anywhere Docker runs, including a laptop, an on-premises server or a cloud VM.
  • Marketplace images: the self-hosting docs also list Dify Premium on AWS and a setup path through BT Panel.
  • Enterprise infrastructure: Dify Enterprise offers a Helm chart for Kubernetes, Terraform modules for AWS, GCP and Azure, and air-gapped deployment for sensitive workloads.
  • AI clients: apps exposed as MCP servers can be connected to AI assistants such as Claude Desktop and development environments such as Cursor.

Pricing

Dify pricing on the Cloud edition is per workspace, and prices exclude applicable taxes, which may be added at checkout. Professional costs $59 per workspace per month and Team $159, with annual billing saving $118 and $318 a year respectively. Billed annually, Professional is $590 per workspace per year, a discount the pricing page labels as 17%. Team is $1590 per workspace per year on annual billing.

PlanMessage creditsMembersAppsKnowledge documentsKnowledge storage
Sandbox (Free)200155050MB
Professional5,000 / month3505005GB
Team10,000 / month502001,00020GB

Sandbox's 200 credits are a total allowance with no monthly reset.

Enterprise is quoted individually through sales and is the only tier that includes commercial license authorization, multiple workspaces and SSO. The self-hosted Community Edition is free.

Billing rules that change the real cost:

  • Plan changes: an upgrade takes effect immediately after paying the difference, a downgrade applies from the next billing cycle, and a cancelled workspace keeps its plan until the paid period ends before returning to Sandbox.
  • Refunds: except as the Terms expressly state or the law requires, all fees are non-refundable and payment obligations are non-cancelable.
  • Unused allowances: included credits, quotas and capacity have no cash value and, unless a plan or order says otherwise, do not roll over after the billing period.
  • Model coverage: because of model costs, some models cannot be used with message credits and need your own API key.
  • Credit cost per response: rates run from 1 credit for smaller models such as gpt-5-mini to 20 credits for Claude Opus 4.7 and 25 credits for gpt-5.5.

Dify alternatives

One community discussion about free, open-source LLM app builders listed Dify alongside Flowise, Langflow, n8n and Make, noting that n8n and Make are more general while the others are tailored to LLMs.

  • Flowise: offers modular building blocks for agentic systems, from simple compositional workflows to autonomous agents. Its homepage currently opens with the notice "We're sunsetting Flowise."
  • Langflow: presented as a tool to build and deploy AI agents and MCP servers, with support for major LLMs, vector databases and a library of AI tools.
  • n8n: a more general automation tool that lets users write JavaScript or Python anywhere in a workflow. It can be deployed with Docker, with its source code on GitHub, and a hosted version is also available.

Against these, Dify stands apart through its built-in knowledge pipeline, bundled model credits on hosted plans, and its license conditions.

Limitations

License conditions for self-hosting

Dify is licensed under a modified version of the Apache License 2.0 with additional conditions:

  • Multi-tenant use: unless Dify explicitly authorizes it in writing, the source code may not be used to operate a multi-tenant environment, where one tenant equals one workspace.
  • Branding: when Dify's frontend is used, the LOGO and copyright information in the console or applications may not be removed or modified; the restriction does not apply to uses that do not involve the frontend.
  • Contributors: contributors agree that the producer can make the license stricter or more relaxed and that contributed code may be used commercially, including in its cloud business.
  • Commercial use: outside those conditions, Dify may be used commercially, including as a backend service for other applications or as an application development platform for enterprises.

Dify's own pages describe the Community Edition in different terms, and they are listed here as published rather than reconciled. The homepage card calls it "Source-available" under an "Apache-2.0-derivative license". The site navigation labels the same edition "Open-source, self-deploy with Docker". The documentation index calls Dify "an open-source platform for building AI applications." On pricing, the Community tier is framed for non-commercial projects and commercial license authorization is listed as Enterprise-only, whereas the enterprise pricing FAQ says the Community Edition can be self-hosted for free with "no license required."

Cloud quotas that stop work

  • Knowledge storage: usage depends on the vectors a document produces rather than its file size, so a document can use several times its own file size once indexed.
  • Full storage: once a workspace reaches its limit it can no longer add knowledge content, and uploads, chunk edits and re-indexing are blocked even in Economical knowledge bases.
  • Knowledge request rate: Sandbox allows 10 knowledge requests per minute, Professional 100 and Team 1,000; exceeding the limit blocks restricted actions for the following minute.
  • Sandbox automation: the free plan allows 2 triggers per workflow. It keeps 30 days of log history and has an API rate limit of 5,000 per month. Paid plans list unlimited log history and no Dify API rate limit.
  • Extra capacity: for Professional workspaces that hit resource limits, the pricing FAQ recommends upgrading the plan rather than offering separate purchases of vector space or seats.

Security disclosures

An independent security-news report dated June 22, 2026 described four vulnerabilities, collectively named DifyTap, of which two were rated critical and three had cross-tenant impact on Dify's multi-tenant cloud service. According to that report, all of them except CVE-2026-41948 were addressed in version 1.14.2, and a fix for the remaining flaw was expected in the next Dify release.

Output reliability and acceptable use

The Terms of Service tell users not to rely on factual assertions in output without independent fact-checking, or on designs, workflows or code without reviewing them. They also prohibit using Dify to make automated decisions that may harm individual rights without appropriate human supervision.

Privacy and data use

  • Model training: LangGenius says it does not train AI models itself and will not use your AI interaction data for model training, and the model providers it manages are contractually prohibited from doing so.
  • Your own keys: when you supply your own provider key, AI interaction data goes directly to that provider, and whether it is used for training depends on your agreement with that provider.
  • Processing locations: personal information may be stored and processed wherever LangGenius or its providers have facilities, including the United States, Australia, Canada, China, the European Economic Area and the United Kingdom.
  • Aggregated statistics: Dify may compile anonymized Aggregated Statistics from Customer Data entered into the service, and it retains all rights in those statistics.

FAQ

Q1. Can I use my own model API key on Dify Cloud?

Yes. Your own key and the included AI credits can coexist, and a Usage Priority setting on each provider card decides which one Dify draws from first before falling back to the other. A key added by the owner or an admin works across the whole workspace and bills to your own account with that provider.

Q2. Is Dify free for students and teachers?

Current students, teachers and educational staff can verify their affiliation to use the Yearly Professional plan for free, with re-verification required annually. Applicants must be at least 18 and register with a school-issued email address. Education workspaces keep Professional features and quotas, but AI credits stay at 200 one-time credits with no monthly refill.

Q3. Can a company pay for Dify Cloud by invoice?

Not yet. Pay by Invoice through bank transfer is being explored but is not available; under the proposed arrangement it would apply only to annual Team subscriptions.

Q4. What happens to knowledge bases after a downgrade?

Nothing is deleted. If a downgrade or expired subscription leaves your data above the new plan's limit, apps can still retrieve from those knowledge bases, but adding content stays blocked until usage fits the limit or you upgrade again.

Q5. Where is Dify Cloud data stored?

Dify Cloud is described as running on hardened infrastructure with encryption in transit and at rest, with data stored in Dify's managed cloud region; the specific region is not named on the pricing page.

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