llm-scraper

LLM Scraper

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

[!IMPORTANT] LLM Scraper was updated to version 2.0.

The new version comes with Vercel AI SDK 6 support and updated examples.

Features

• Supports GPT, Sonnet, Gemini, Llama, Qwen model series
• Schemas defined with Zod or JSON Schema
• Full type-safety with TypeScript
• Based on Playwright framework
• Streaming objects
• Code-generation
• Supports 6 formatting modes:
  • html for loading pre-processed HTML
  • raw_html for loading raw HTML (no processing)
  • markdown for loading markdown
  • text for loading extracted text (using Readability.js)
  • image for loading a screenshot (multi-modal only)
  • custom for loading custom content (using a custom function)

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('gpt-4o')
   

   Anthropic

   npm i @ai-sdk/anthropic
   

   import { anthropic } from '@ai-sdk/anthropic'
   
   const llm = anthropic('claude-3-5-sonnet-20240620')
   

   Google

   npm i @ai-sdk/google
   

   import { google } from '@ai-sdk/google'
   
   const llm = google('gemini-1.5-flash')
   

   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-v2
   

   import { ollama } from 'ollama-ai-provider-v2'
   
   const llm = ollama('llama3')
   

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 { Output } from 'ai'
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('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, Output.object({ schema }), {
  format: 'html',
})

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

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

Output

[
  {
    title: "Palette lighting tricks on the Nintendo 64",
    points: 105,
    by: "ibobev",
    commentsURL: "https://news.ycombinator.com/item?id=44014587",
  },
  {
    title: "Push Ifs Up and Fors Down",
    points: 187,
    by: "goranmoomin",
    commentsURL: "https://news.ycombinator.com/item?id=44013157",
  },
  {
    title: "JavaScript's New Superpower: Explicit Resource Management",
    points: 225,
    by: "olalonde",
    commentsURL: "https://news.ycombinator.com/item?id=44012227",
  },
  {
    title: "\"We would be less confidential than Google\" Proton threatens to quit Switzerland",
    points: 65,
    by: "taubek",
    commentsURL: "https://news.ycombinator.com/item?id=44014808",
  },
  {
    title: "OBNC – Oberon-07 Compiler",
    points: 37,
    by: "AlexeyBrin",
    commentsURL: "https://news.ycombinator.com/item?id=44013671",
  }
]

More examples can be found in the examples folder.

Streaming

Replace your run function with stream to get a partial object stream.

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

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

Code-generation

Using the generate function you can generate re-usable playwright script that scrapes the contents according to a schema.

// Generate code and run it on the page
const { code } = await scraper.generate(page, Output.object({ schema }))
const result = await page.evaluate(code)
const data = schema.parse(result)

// Show the parsed result
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.