Dify vs Langflow

Dify Cloud · Self-hosting · Documentation · Dify edition overview

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Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features:

Quick start

Before installing Dify, make sure your machine meets the following minimum system requirements:

• CPU >= 2 Core
• RAM >= 4 GiB

The easiest way to start the Dify server is through Docker Compose. Install Docker with a running daemon, Docker Compose v2.35.0 or later, and OpenSSL.

For a new deployment, run the following commands from the repository root. For an existing deployment, preserve your .env and follow the upgrade guidance.

cd docker
cp .env.example .env
openssl rand -hex 32

Open .env and set DIFY_AGENT_LOCAL_SANDBOX_AUTH_TOKEN to the generated value. Keep the default COMPOSE_PROFILES value for the bundled services. Service defaults load automatically; no additional configuration files are required.

From the same docker directory, start the services:

docker compose up -d
docker compose ps --all

Once the services are running, open http://localhost/install to complete the initial setup. The one-time init_permissions service is expected to exit with code 0.

For optional settings and service overrides, see the Docker deployment guide.

Seeking help

Please refer to our FAQ if you encounter problems setting up Dify. Reach out to the community and us if you are still having issues.

If you'd like to contribute to Dify or do additional development, refer to our guide to deploying from source code

Key features

1. Workflow:
Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.

2. Comprehensive model support:
Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama3, and any OpenAI API-compatible models. A full list of supported model providers can be found here.

3. Prompt IDE:
Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app.

4. RAG Pipeline:
Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats.

5. Agent: Autonomous agents with a sandbox of their own: they run commands, install software, and handle files to get open-ended tasks done. Describe the agent you want and it builds itself. Give it skills, connect tools from Dify Marketplace, MCP servers, or your own APIs, and put it to work as a chat app or as a step in any workflow.

6. LLMOps:
Monitor and analyze application logs and performance over time. You could continuously improve prompts, datasets, and models based on production data and annotations.

7. Backend-as-a-Service:
All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.

Using Dify

• Cloud
  
  We host Dify Cloud so you can try Dify without managing a server. See the pricing page for current plans and usage allowances. If you run into issues, contact our Cloud support team.

• Self-hosting Dify Community Edition
  
  Quickly get Dify running in your environment with this starter guide.
  Use our documentation for further references and more in-depth instructions.

• Dify Enterprise
  
  For organizations requiring self-hosting, SSO, RBAC Security and Enterprise Support SLAs, please fill out this form to speak to a solution representative.
  

Staying ahead

Star Dify on GitHub and be instantly notified of new releases.

Advanced Setup

For custom configuration, observability, and deployment options, see Advanced Setup.

Contributing

Dify welcomes contributions of all kinds:

• Code: Read the Contribution Guide, then browse good first issues.
• Ideas and feedback: Start or join a GitHub Discussion.
• Translations: Follow the internationalization guide to add or update a locale.
• Community: Share the apps you build, help other users, and spread the word about Dify.

Contributors

Community & contact

Choose the channel that best fits your question:

• GitHub Discussions: Get help, share feedback, and propose ideas.
• GitHub Issues: Report reproducible bugs and track engineering work. Read the Contribution Guide before opening one.
• Discord: Chat in real time, share your apps, and connect with other Dify users.
• X: Follow Dify for release news and project updates.

Star History

Security disclosure

Report vulnerabilities privately through GitHub Security Advisories, following our security policy. Do not disclose them in public issues, discussions, or pull requests.

License

This repository is licensed under the Dify Open Source License, based on Apache 2.0 with additional conditions.

Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.

✨ Highlight features

• Visual builder interface to quickly get started and iterate.
• Source code access lets you customize any component using Python.
• Interactive playground to immediately test and refine your flows with step-by-step control.
• Multi-agent orchestration with conversation management and retrieval.
• Deploy as an API or export as JSON for Python apps.
• Deploy as an MCP server and turn your flows into tools for MCP clients.
• Observability with LangSmith, LangFuse and other integrations.
• Enterprise-ready security and scalability.

🖥️ Langflow Desktop

Langflow Desktop is the easiest way to get started with Langflow. All dependencies are included, so you don't need to manage Python environments or install packages manually.
Available for Windows and macOS.

📥 Download Langflow Desktop

⚡️ Quickstart

Install locally (recommended)

Requires Python 3.10–3.14 and uv (recommended package manager).

Install

From a fresh directory, run:

uv pip install langflow -U

The latest Langflow package is installed.
For more information, see Install and run the Langflow OSS Python package.

Run

Official release packages and tagged source archives disable automatic login by default. Set LANGFLOW_SUPERUSER_PASSWORD before starting Langflow, then sign in with the username langflow (or your configured LANGFLOW_SUPERUSER). Development branches retain automatic login by default. See authentication configuration.

To start Langflow, run:

uv run langflow run

Langflow starts at http://127.0.0.1:7860.

That's it! You're ready to build with Langflow! 🎉

📦 Other install options

Run from source

If you've cloned this repository and want to contribute, run this command from the repository root:

make run_cli

For more information, see DEVELOPMENT.md.

Docker

Set and export a strong password before starting the container (Bash):

read -rsp "Langflow administrator password: " LANGFLOW_SUPERUSER_PASSWORD; echo
export LANGFLOW_SUPERUSER_PASSWORD
docker run -p 7860:7860 -e LANGFLOW_SUPERUSER_PASSWORD langflowai/langflow:latest

Langflow is available at http://localhost:7860/. Sign in as langflow with the password you entered. Official Docker images require authentication by default.
If you already have an auto-login installation, follow the upgrade instructions before switching defaults.
For configuration options, see the Docker deployment guide.

🛡️ Security

For security information, see our Security Policy.

🚀 Deployment

Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to deploy Langflow, see our Langflow deployment guides.

⭐ Stay up-to-date

Star Langflow on GitHub to be instantly notified of new releases.

👋 Contribute

We welcome contributions from developers of all levels. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.

❤️ Contributors