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Ask HN: A translation pipeline that doesn't chew up long HTML pages

1•lym11248•1h ago
My site has 1000+ HTML pages. Most of the content is AI-drafted and poured into templates, so pages tend to be long and full of repeated structural markup instead of hand-written one-offs.

Feed a long HTML page straight to an LLM for translation and it doesn't just mistranslate. It silently drops content. Whole sections vanish, paragraphs get summarized instead of translated, and the longer the page, the worse it gets. You get back something that looks like a translation but is missing half the page, with no warning that anything was lost.

Naively splitting the page into smaller chunks, by line or by character count, doesn't fix this. It just cuts through the middle of tags and sentences, breaking the structure and handing the model fragments that don't mean anything on their own.

What actually works is parsing the page into its real structure with tree-sitter, then chunking along structural boundaries so each chunk is a complete, meaningful unit and nothing gets silently cut or dropped. Anything non-translatable, like template logic or layout attributes, stays out of the model's hands entirely. A structural check after translation catches anything that still slips through, mostly as a safety net at this point.

Ran it for real on 1000+ pages, six languages, output checked by hand.

Not pitching anything. Just want to know if this content-loss problem bites other people translating long pages with LLMs, or if it's specific to how my site is built.

Hyperlight 0.17.0

https://hyperlight.org/blog/hyperlight-0170/
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https://setsumeiapp.kulman.sk/
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Ask HN: What's the Best AI Setup?

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