Let ChatGPT read the HTML so you don't have to

What it does

The repository is essentially a usage guide and sample-code showcase for ScrapingBee’s commercial ChatGPT scraping API. You send a natural-language prompt—optionally spiced with live web search results, geotargeted queries, or raw HTML from a specific page—and get back structured JSON. It is pitched as an alternative to maintaining fragile CSS selectors and parsing logic.

The interesting bit

The core idea is delegating extraction logic to an LLM rather than writing bespoke parsers. That shifts the maintenance burden from “update selectors because the frontend team moved a div” to “tweak a prompt and hope the model notices the price in the HTML you injected.”

Key highlights

• Uses natural language prompts to define extraction goals instead of fixed selectors
• Can perform live web search before answering, with geotargeting via country_code
• Supports injecting raw target-page HTML into the model context via add_html
• Returns structured JSON responses rather than free-form text
• Provides JavaScript SDK examples and bare requests Python snippets

Caveats

• The repository itself contains no scraper logic; it is documentation and sample calls for a paid third-party API
• The README is heavy on SEO repetition and light on technical depth (no pricing, rate-limit specifics, or latency numbers)
• You must possess a ScrapingBee API key, meaning this is not a self-hosted or offline-capable tool

Verdict

Worth a skim if you are evaluating commercial scraping APIs and prefer prompt-based extraction over traditional parser maintenance. Skip it if you are looking for open-source scraping infrastructure you can run locally.