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@kaibanjs/tools

v0.1.2

Published

A set of tools to work with LLMs and KaibanJS

Downloads

272

Readme

Kaiban Tools for AI Agents

This package provides a collection of specialized tools designed for use with AI agents, enhancing their capabilities for various tasks.

Purpose

The Kaiban Tools package offers a set of tools that can be integrated into AI agent systems, allowing agents to perform a wide range of tasks more effectively. These tools are designed to extend the capabilities of AI agents, enabling them to interact with external services, process data, and perform complex operations.

Features

  • A collection of tools specifically designed for AI agents
  • Easy integration with existing agent frameworks and architectures
  • Tools for various purposes, including web scraping, data transformation, and more
  • Configurable options for each tool to suit different agent requirements

Installation

npm install @kaibanjs/tools

Available Tools

1. Firecrawl

Firecrawl is a tool that allows agents to interact with the Firecrawl web scraping service, enabling them to extract clean, structured data from websites.

Learn more: https://www.firecrawl.dev/

2. Tavily Search

Tavily Search is a tool that provides AI-optimized search capabilities, delivering comprehensive and accurate results. It's particularly useful for retrieving current information and answering questions about recent events.

Learn more: https://tavily.com/

Development

Local Setup

  1. Clone the repository:
git clone https://github.com/kaiban-ai/KaibanJS.git
  1. Navigate to the tools package:
cd packages/tools
  1. Install dependencies:
npm install
  1. Environment Variables:

Create a .env file in the root directory with your API keys:

VITE_FIRECRAWL_API_KEY=your_firecrawl_api_key
VITE_TAVILY_API_KEY=your_tavily_api_key
  1. Run Storybook to view and test components:
npm run storybook
  1. Build the package:
npm run build
  1. Run tests:
npm run test

Contributing

To contribute a new tool:

  1. Follow the Development steps above to set up your local environment
  2. Use an existing tool as reference (check src/firecrawl or src/tavily for examples)
  3. Remember to create:
    • Your tool implementation
    • A Storybook story
    • Tests

For questions or discussions, join our Discord.

License

MIT License