LLM Scraper

LLM Scraper is a TypeScript library that allows you to convert any webpages into structured data using LLMs.

[!TIP] Under the hood, it uses function calling to convert pages to structured data. You can find more about this approach here

Features

• Supports Local (GGUF), OpenAI, Groq chat models
• Schemas defined with Zod
• Full type-safety with TypeScript
• Based on Playwright framework
• Streaming objects
• Supports 4 input modes:
  • html for loading raw HTML
  • markdown for loading markdown
  • text for loading extracted text (using Readability.js)
  • image for loading a screenshot (multi-modal only)

Make sure to give it a star!

Getting started

1. Install the required dependencies from npm:

   npm i zod playwright llm-scraper

2. Initialize your LLM:

   OpenAI

   npm i @ai-sdk/openai

   import { openai } from '@ai-sdk/openai'
   const llm = openai.chat('gpt-4o')

   Groq

   npm i @ai-sdk/openai

   import { createOpenAI } from '@ai-sdk/openai'
   const groq = new OpenAI({
    baseURL: 'https://api.groq.com/openai/v1',
    apiKey: process.env.GROQ_API_KEY,
   })
   
   const llm = groq('llama3-8b-8192')

   Local

   import { LlamaModel } from 'node-llama-cpp'
   const llm = new LlamaModel({ modelPath: 'model.gguf' })

3. Create a new scraper instance provided with the llm:

   import LLMScraper from 'llm-scraper'
   const scraper = new LLMScraper(llm)

Example

In this example, we're extracting top stories from HackerNews:

import { chromium } from 'playwright'
import { z } from 'zod'
import { openai } from '@ai-sdk/openai'
import LLMScraper from 'llm-scraper'

// Launch a browser instance
const browser = await chromium.launch()

// Initialize LLM provider
const llm = openai.chat('gpt-4o')

// Create a new LLMScraper
const scraper = new LLMScraper(llm)

// Open new page
const page = await browser.newPage()
await page.goto('https://news.ycombinator.com')

// Define schema to extract contents into
const schema = z.object({
  top: z
    .array(
      z.object({
        title: z.string(),
        points: z.number(),
        by: z.string(),
        commentsURL: z.string(),
      })
    )
    .length(5)
    .describe('Top 5 stories on Hacker News'),
})

// Run the scraper
const { data } = await scraper.run(page, {
  schema,
  mode: 'html',
})

// Show the result from LLM
console.log(data?.top)

await page.close()
await browser.close()

Streaming

Replace your run function with stream to get a partial object stream (Vercel AI SDK only).

// Run the scraper
const { stream } = await scraper.stream(page, {
  schema,
  mode: 'html',
})

// Stream the result from LLM
for await (const data of stream) {
  console.log(data.top)
}

Contributing

As an open-source project, we welcome contributions from the community. If you are experiencing any bugs or want to add some improvements, please feel free to open an issue or pull request.