Drag & drop UI to build your customized LLM flow using LangchainJS https://github.com/FlowiseAI/Flowise

天问 4851641958 Update 'README.md' 10 months ago
README.md 4851641958 Update 'README.md' 10 months ago

README.md

Flowise - LangchainJS UI

Drag & drop UI to build your customized LLM flow using LangchainJS

⚡Quick Start

  1. Install Flowise

    npm install -g flowise
    
  2. Start Flowise

    npx flowise start
    

    With username & password

    npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234
    
  3. Open http://localhost:3000

🐳 Docker

Docker Compose

  1. Go to docker folder at the root of the project
  2. Create .env file and specify the PORT (refer to .env.example)
  3. docker-compose up -d
  4. Open http://localhost:3000
  5. You can bring the containers down by docker-compose stop

Docker Image

  1. Build the image locally:

    docker build --no-cache -t flowise .
    
  2. Run image:

    docker run -d --name flowise -p 3000:3000 flowise
    
  3. Stop image:

    docker stop flowise
    

👨‍💻 Developers

Flowise has 3 different modules in a single mono repository.

  • server: Node backend to serve API logics
  • ui: React frontend
  • components: Langchain components

Prerequisite

  • Install Yarn

    npm i -g yarn
    

Setup

  1. Clone the repository

    git clone https://github.com/FlowiseAI/Flowise.git
    
  2. Go into repository folder

    cd Flowise
    
  3. Install all dependencies of all modules:

    yarn install
    
  4. Build all the code:

    yarn build
    
  5. Start the app:

    yarn start
    

    You can now access the app on http://localhost:3000

  6. For development build:

    yarn dev
    

    Any code changes will reload the app automatically on http://localhost:8080

🔒 Authentication

To enable app level authentication, add FLOWISE_USERNAME and FLOWISE_PASSWORD to the .env file in packages/server:

FLOWISE_USERNAME=user
FLOWISE_PASSWORD=1234