Overview
Flowise is an open-source tool for building LLM apps and AI agents without writing much code. You work on a visual canvas, dragging in nodes for models, prompts, memory, tools, and data sources, then wiring them together to form a flow.
It runs as a Node.js app with three parts in one repository: a server for the API logic, a React user interface, and a library of third-party node integrations. Once a flow is ready, you can use it through an API endpoint, embed it as a chat widget, or self-host it on your own infrastructure.
What it does
- Visual drag-and-drop canvas for designing LLM chains and multi-step agent flows
- Large library of built-in nodes for models, prompts, memory, tools, and data loaders
- Turns each finished flow into an API endpoint and an embeddable chat widget
- Self-host anywhere, with ready-made deployment guides for AWS, Azure, GCP, and more
- Runs locally in minutes via npm or as a Docker container
- Apache 2.0 licensed open-source codebase you can extend with custom nodes
Getting started
Flowise needs Node.js 20 or newer. The fastest way to try it is the npm package, which starts a local server you open in your browser.
Install Flowise globally
Install the Flowise CLI package using npm.
npm install -g flowiseStart the app
Launch Flowise, then open http://localhost:3000 in your browser to reach the visual builder.
npx flowise startOr run with Docker
Prefer containers? Build the image locally and run it on port 3000.
docker build --no-cache -t flowise .
docker run -d --name flowise -p 3000:3000 flowiseBuild from source for development
To work on Flowise itself, clone the repo and use PNPM to install, build, and start the monorepo.
git clone https://github.com/FlowiseAI/Flowise.git
cd Flowise
pnpm install
pnpm build
pnpm startCommands and code are distilled from the project's own documentation — always check the official repo for the latest.
When to use it
- Prototype a chatbot or RAG assistant over your own documents without writing backend code
- Build multi-step AI agents that call tools and APIs, then expose them as an endpoint for your app
- Let non-developers on a team assemble and test LLM workflows on a shared visual canvas
- Self-host an internal AI app on your own cloud to keep data and keys inside your infrastructure
How Flowise compares
Flowise alongside other open-source low-code & no-code builders tools AI/TLDR tracks, ranked by GitHub stars.
| Tool | Stars | What it does |
|---|---|---|
| Langflow | ★ 155k | Langflow is an open-source platform for building AI agents and workflows visually, then deploying each flow as an API or MCP server. |
| OpenDesign | ★ 97.3k | Local-first desktop app that turns a written brief into web, mobile and desktop prototypes, decks, images and video by delegating to the coding-agent CLIs already on your machine. |
| NocoDB | ★ 65k | An open-source tool that turns any SQL database into a no-code spreadsheet-style app, used as a self-hosted Airtable alternative. |
| Flowise | ★ 55.5k | Build LLM apps and AI agents visually with a drag-and-drop canvas |
| JeecgBoot | ★ 47.9k | Java low-code platform — online form, report and workflow designers plus a code generator — with a bundled langchain4j app layer for chat assistants, RAG knowledge bases and MCP plugins. |
| ToolJet | ★ 40.9k | An open-source low-code platform with a drag-and-drop UI builder, built-in database, and JavaScript logic for building internal tools, dashboards, and workflows. |
| Appsmith | ★ 40.9k | An open-source low-code platform for quickly building internal tools, admin panels, and dashboards from a visual editor plus custom JavaScript and data-source connections. |
| Directus | ★ 37.9k | An open-source data platform that wraps any SQL database in an instant API and a no-code admin app for managing content and building back-office tools. |
