Step-by-Step Guides

How to contribute?

How to

How to contribute?

👋 Hello there! We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.

As an open-source project in a rapidly developing field, we are extremely open to contributions, whether in the form of a new feature, improved infra, or better documentation.

To contribute to this project, please follow a "fork and pull request" workflow.

Please do not try to push directly to this repo unless you are a maintainer.

Local development

You can develop Langflow using docker compose, or locally.

We provide a .vscode/launch.json file for debugging the backend in VSCode, which is a lot faster than using docker compose.

Setting up hooks:

make init

This will install the pre-commit hooks, which will run make format on every commit.

It is advised to run make lint before pushing to the repository.

Run locally

Langflow can run locally by cloning the repository and installing the dependencies. We recommend using a virtual environment to isolate the dependencies from your system.

Before you start, make sure you have the following installed:

  • Poetry (>=1.4)

  • Node.js

Then, in the root folder, install the dependencies and start the development server for the backend:

make backend

And the frontend:

make frontend

Docker compose

The following snippet will run the backend and frontend in separate containers. The frontend will be available at localhost:3000 and the backend at localhost:7860.

docker compose up --build
# or


The documentation is built using Docusaurus. To run the documentation locally, run the following commands:

cd docs
npm install
npm run start

The documentation will be available at localhost:3000 and all the files are located in the docs/docs folder. Once you are done with your changes, you can create a Pull Request to the main branch.

Getting Started

👋 Welcome to Langflow
📦 How to install?
🤗 HuggingFace Spaces
🎨 Creating Flows


Sign up and Sign in
API Keys
Assynchronous Processing
Prompt Customization
Chat Interface
Chat Widget
Custom Components

Step-by-Step Guides

Async API
Integrating documents with prompt variables
Building chatbots with System Message
Integrating Langfuse with Langflow


FlowRunner Component
Conversation Chain
Buffer Memory
MidJourney Prompt Chain
CSV Loader
Serp API Tool
Multiple Vector Stores
Python Function
📚 How to Upload Examples?


Deploy on Google Cloud Platform


How to contribute?
GitHub Issues

Search Docs…

Search Docs…