Robust LLM extractor for websites in TypeScript
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
In plain words
Robust LLM extractor for websites is a TypeScript tool that uses large language models to extract structured data from websites. It addresses common pain points in web scraping by cleaning noisy HTML, validating JSON responses, and handling URL normalization automatically. The tool reduces token costs and prevents pipeline failures caused by malformed data or website layout changes, making it suitable for developers building data extraction pipelines.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with nested arrays and complex schemas. One bad bracket and your pipeline crashes. - Relative URLs, markdown-escaped links, tracking parameters — the "small" URL issues compound fast when you're processing thousands of pages. - You end up writing the same boilerplate: HTML cleanup → markdown conversion → LLM call → JSON parsing → error recovery → schema validation. Over and over. We got tired of rebuilding this stack for every project, so we extracted it into a library. Lightfeed Extractor is a TypeScript library that handles the full pipeline from raw HTML to validated, structured data: - Converts HTML to LLM-ready markdown with main content extraction (strips nav, headers, footers), optional image inclusion, and URL cleaning - Works with any LangChain-compatible LLM (OpenAI, Gemini, Claude, Ollama, etc.) - Uses Zod schemas for type-safe extraction with real validation - Recovers partial data from malformed LLM output instead of failing entirely — if 19 out of 20 products parsed correctly, you get those 19 - Built-in browser automation via Playwright (local, serverless, or remote) with anti-bot patches - Pairs with our browser agent (@lightfeed/browser-agent) for AI-driven page navigation before extraction We use this ourselves in production at Lightfeed, and it's been solid enough that we decided to open-source it. GitHub: https://github.com/lightfeed/extractor npm: npm install @lightfeed/extractor Apache 2.0 licensed. Happy to answer questions or hear feedback.
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