LLM Scraper is a TypeScript library that allows you to extract structured data from any webpage using LLMs.

• Supports Local (Ollama, GGUF), OpenAI, Vercel AI SDK Providers
• Schemas defined with Zod
• Full type-safety with TypeScript
• Based on Playwright framework
• Streaming objects
• NEW Code-generation
• Supports 4 formatting 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!

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

   Ollama

   npm i ollama-ai-provider
   

   import { ollama } from 'ollama-ai-provider'
   
   const llm = ollama('llama3')

   GGUF

   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)

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, {
  format: 'html',
})

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

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

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

// Run the scraper in streaming mode
const { stream } = await scraper.stream(page, schema)

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