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This guide shows you how to add Snow Leopard data retrieval to a Vercel AI SDK agent.

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Prerequisites

Don’t have data? Use our sample superheroes dataset to get started, or choose from our other sample datasets.

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Start from scratch

Clone and run the complete working example: 
git clone https://github.com/SnowLeopard-AI/snowy-examples.git
cd snowy-examples/quickstart/vercel-ai
Install dependencies: 
npm install
Set your environment variables: 
export OPENAI_API_KEY=your-openai-key
export SNOWLEOPARD_API_KEY=your-snowleopard-key
export SNOWLEOPARD_DATAFILE_ID=your-datafile-id
Run the example: 
npm run snowy
You now have an interactive REPL where you can ask questions about your data.

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Bring your own agent

Already have a Vercel AI agent? Add Snow Leopard data retrieval with these steps.

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1. Install dependencies

npm install @snowleopard-ai/client

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2. Create the Snow Leopard tool

Create a tool that calls Snow Leopard to retrieve data: 
const { tool } = require('ai');
const { z } = require('zod');
const { SnowLeopardClient } = require('@snowleopard-ai/client');

const snowy = new SnowLeopardClient({ apiKey: '{your-snowleopard-api-key}' });

const getData = tool({
  description: 'Retrieve data from the database. ' +
               'Describe your data here - this becomes part of the tool description.',
  inputSchema: z.object({
    userQuestion: z.string().describe('the natural language query to answer'),
  }),
  execute: async ({ userQuestion }) => {
    return await snowy.retrieve({
      userQuery: userQuestion,
      datafileId: '{your-datafile-id}'
    });
  }
});

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3. Customize the tool description

The tool’s description tells the agent when and how to use it. Update it to describe your specific data: 
const getData = tool({
  description: 'Retrieve customer order data. ' +
               'Contains order history, products, and customer information. ' +
               'Use this to answer questions about sales, orders, and customers.',
  // ...
});

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Next steps