A set of tools to work with LLMs and KaibanJS
npm install @kaibanjs/toolsThis package provides a collection of specialized tools designed for use with AI agents, enhancing their capabilities for various tasks.
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.
- 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
``bash`
npm install @kaibanjs/tools
Here's a list of all available tools. Click on the tool names to view their detailed documentation.
| Tool | Description | Documentation |
| ------------------- | ------------------------------------------------------------------------------- | -------------------------------------------- |
| Exa | AI-focused search engine using embeddings to organize web data | README |
| Firecrawl | Web scraping service for extracting structured data | README |
| GitHub Issues | GitHub API integration for fetching and analyzing repository issues | README |
| Jina URL to MD | Convert web content into clean, LLM-ready markdown using Jina.ai | README |
| PDF Search | Extract and search content from PDF documents | README |
| Serper | Google Search API integration with support for multiple search types | README |
| Simple RAG | Basic Retrieval-Augmented Generation implementation for Q&A | README |
| Tavily Search | AI-optimized search engine for comprehensive and accurate results | README |
| Text File Search | Search and analyze content within text files | README |
| Website Search | Semantic search within website content using RAG models | README |
| WolframAlpha | Computational intelligence engine for complex queries and calculations | README |
| Zapier Webhook | Integration with Zapier for workflow automation | README |
| Make Webhook | Integration with Make (formerly Integromat) for workflow automation | README |
| Simple RAG Retrieve | Basic Retrieval-Augmented Generation implementation for Q&A with preloaded data | README |
1. Clone the repository:
`bash`
git clone https://github.com/kaiban-ai/KaibanJS.git
2. Install KaibanJS dependencies:
`bash`
npm install
3. Build the package:
`bash`
npm run build
3. Navigate to the tools package:
`bash`
cd packages/tools
3. Install dependencies:
`bash`
npm install
4. Environment Variables:
Create a .env file in the root directory with your API keys:
`env`
VITE_FIRECRAWL_API_KEY=your_firecrawl_api_key
VITE_TAVILY_API_KEY=your_tavily_api_key
VITE_SERPER_API_KEY=your_serper_api_key
VITE_EXA_API_KEY=your_exa_api_key
VITE_WOLFRAM_APP_ID=your_wolfram_app_id
5. Run Storybook to view and test components:
`bash`
npm run storybook
6. Build the package:
`bash`
npm run build
7. Run tests:
`bash`
npm run test
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.
MIT License