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An open-source drag-and-drop visual AI agent building platform based on LangChain technology, allowing users to quickly create custom LLM applications without programming.

NOASSERTIONTypeScript 40.5kFlowiseAIFlowise Last Updated: 2025-06-22

Flowise Project Detailed Introduction

Project Overview

Flowise is an open-source, drag-and-drop visual platform specifically designed for building AI agents and LLM (Large Language Model) applications. Built on LangChain.js, the project provides a low-code/no-code development environment, allowing users to quickly create complex AI-driven applications through an intuitive drag-and-drop interface.

Core Features

1. Visual Development Interface

  • Drag-and-Drop Operation: Assemble AI workflows through simple drag-and-drop operations.
  • Node-Based Design: Each functional module is presented as a node, making it easy to understand and use.
  • Real-Time Preview: Supports real-time viewing and testing of built AI applications.

2. Powerful AI Capabilities

  • Intelligent Agent Building: Can create chat assistants that can follow instructions, use tools when necessary, and retrieve knowledge from uploaded files (RAG).
  • Memory Function: Supports creating conversational agents with dialogue memory capabilities.
  • Tool Integration: Built-in integration with various AI tools and third-party services.

3. Technical Architecture

Flowise is built on LangChain.js, providing advanced features from LLM orchestration and agent creation to seamless integration via APIs, SDKs, and embedded chat.

The project adopts a monorepo architecture, comprising three main modules:

  • server: Node.js backend, providing API logic services.
  • ui: React frontend interface.
  • components: Third-party node integration components.
  • api-documentation: Swagger UI API documentation automatically generated from Express.

Main Application Scenarios

1. Chatbot Development

  • Customer service robots
  • Knowledge Q&A systems
  • Intelligent assistants

2. RAG (Retrieval-Augmented Generation) Applications

  • Document Q&A systems
  • Knowledge base queries
  • Intelligent search assistants

3. Workflow Automation

  • Business process automation
  • Data processing pipelines
  • Content generation processes

Installation and Deployment

Quick Installation

# Install Flowise
npm install -g flowise

# Start the application
npx flowise start

Docker Deployment

# Build the image
docker build --no-cache -t flowise .

# Run the container
docker run -d --name flowise -p 3000:3000 flowise

Development Environment Setup

# Clone the repository
git clone https://github.com/FlowiseAI/Flowise.git

# Enter the project directory
cd Flowise

# Install dependencies
pnpm install

# Build the project
pnpm build

# Start the application
pnpm start

Technical Requirements

  • Node.js: Version >= 18.15.0
  • Package Manager: Supports npm, pnpm
  • Containerization: Supports Docker deployment

Project Advantages

1. Ease of Use

  • No programming background required
  • Intuitive visual interface
  • Rich pre-set templates

2. Flexibility

  • Supports custom node development
  • Flexible configuration options
  • Extensible architectural design

3. Community Support

  • Active open-source community
  • Detailed documentation support
  • Discord community communication platform

Deployment Options

Flowise supports multiple deployment methods:

  • Self-Hosted Deployment: Deploy on existing infrastructure.
  • Cloud Deployment: Supports various cloud platforms.
  • Flowise Cloud: Official managed service.

Open Source License

The project uses the Apache License Version 2.0 open-source license, allowing free commercial and personal use.

Summary

Flowise is a powerful and easy-to-use AI development platform that lowers the barrier to AI application development, enabling more users to quickly build and deploy intelligent applications. Whether you are a beginner or a professional developer, you can benefit from this platform to quickly realize the conception and implementation of AI projects.

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