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Build AI Agents, Visually

Flowise is an open-source visual tool for building customized AI agents and workflows. Create powerful LLM applications with an intuitive drag-and-drop interface.

What is Flowise?

Flowise is an open-source low-code platform that enables you to build customized LLM orchestration flows and AI agents. With its visual drag-and-drop interface, you can create complex AI workflows without writing extensive code. Flowise Agent Flow

Key Features

Visual Workflow Builder

Drag and drop nodes to create complex AI workflows. Connect LLMs, chains, agents, and tools without writing code.

Multi-Agent Systems

Orchestrate multiple AI agents to work together on complex tasks with autonomous decision-making capabilities.

Extensive LLM Support

Connect to OpenAI, Anthropic, Google, Azure OpenAI, Hugging Face, and many more LLM providers.

Vector Store Integrations

Integrate with Pinecone, Qdrant, Weaviate, Chroma, PostgreSQL, and other vector databases for semantic search.

Document Processing

Upload, process, and query documents with built-in RAG (Retrieval-Augmented Generation) support.

Custom Nodes & Tools

Extend Flowise with your own custom integrations, tools, and logic using TypeScript/JavaScript.

API & Embeddings

RESTful APIs for integrating workflows into your applications, plus built-in embedding capabilities.

Self-Hosted & Cloud

Deploy on your own infrastructure or use Flowise Cloud for managed hosting.

Architecture

Flowise is built as a monorepo with three main modules:
  • server - Node.js backend that serves API logic and handles workflow execution
  • ui - React frontend providing the visual canvas and user interface
  • components - Third-party node integrations (LLMs, vector stores, tools, etc.)
  • api-documentation - Auto-generated Swagger UI API documentation

Use Cases

Build intelligent chatbots with memory, context awareness, and personality. Integrate with various LLMs and customize conversation flows.
Create RAG-based systems that can answer questions from your documents. Upload PDFs, text files, or connect to document stores.
Design agents that can use tools, make decisions, and complete complex tasks autonomously with minimal human intervention.
Build workflows that analyze data, generate insights, and create reports using AI-powered analysis.
Create automated content generation pipelines for blogs, marketing copy, code, and more.
Connect multiple APIs and services in intelligent workflows that make decisions based on LLM reasoning.

Why Flowise?

Open Source

Apache 2.0 licensed. Full transparency and community-driven development.

No Vendor Lock-in

Self-host on your infrastructure. Full control over your data and workflows.

Production Ready

Battle-tested with thousands of deployments. Enterprise-grade security and reliability.

Active Community

Join thousands of developers building with Flowise. Get help on Discord.

Regular Updates

Frequent releases with new features, integrations, and improvements.

Easy to Extend

Create custom nodes and integrations with simple TypeScript/JavaScript.

Requirements

  • Node.js >= 18.15.0 (version 18.15.0 to < 19.0.0 or version 20+)
  • npm or pnpm for package management
  • Optional: Docker for containerized deployment
  • Optional: PostgreSQL or MySQL for production database (SQLite used by default)
Flowise uses SQLite by default for development. For production deployments, it’s recommended to use PostgreSQL or MySQL.

Community & Support

GitHub Repository

Star the project, report issues, and contribute to development.

Discord Community

Join our Discord server for support, discussions, and community help.

Twitter/X

Follow us for updates, tips, and announcements.

Flowise Cloud

Managed hosting solution with automatic updates and scaling.

Next Steps

1

Install Flowise

Follow the Installation guide to set up Flowise locally or via Docker.
2

Quick Start

Build your first chatflow with the Quickstart tutorial.
3

Explore Examples

Browse example workflows to learn common patterns and best practices.

Build docs developers (and LLMs) love