Integrations
Vercel AI SDK
Wrap Thunderbit as a TypeScript tool for streamText / generateText agents
The Vercel AI SDK's tool() helper turns any TypeScript function into something an LLM can call. Wrap /distill and the model can read live web pages mid-conversation.
Install
npm install ai @ai-sdk/openai zodDefine the tool
import { tool } from 'ai';
import { z } from 'zod';
const API = 'https://openapi.thunderbit.com/openapi/v1';
const H = { Authorization: `Bearer ${process.env.THUNDERBIT_API_KEY}` };
export const readUrl = tool({
description:
'Fetch a URL and return clean Markdown. Use for any web research task: docs, articles, product pages.',
parameters: z.object({
url: z.string().url(),
renderMode: z.enum(['basic', 'advanced']).default('basic'),
}),
execute: async ({ url, renderMode }) => {
const res = await fetch(`${API}/distill`, {
method: 'POST',
headers: { ...H, 'Content-Type': 'application/json' },
body: JSON.stringify({ url, renderMode }),
});
const json = await res.json();
return json.data.markdown;
},
});Use with streamText
import { openai } from '@ai-sdk/openai';
import { streamText } from 'ai';
const result = streamText({
model: openai('gpt-4o'),
tools: { readUrl },
maxSteps: 5,
prompt: 'Summarize the latest post on https://vercel.com/blog',
});
for await (const chunk of result.textStream) process.stdout.write(chunk);Tips
- Cap returned Markdown to ~8k tokens before returning from
execute— avoids context bloat - For multi-URL fan-out, expose a second
readUrlstool backed by/batch/distill renderMode: 'advanced'only when the page is JS-heavy —basicis 3-5× cheaper