This looks pretty interesting! I haven't used it yet, but looked through the code a bit, it looks like it uses turndown to convert the html to markdown first, then it passes that to the LLM so assuming that's a huge reduction in tokens by preprocessing. Do you have any data on how often this can cause issues? ie tables or other information being lost?

Then langchain and structured schemas for the output along w/ a specific system prompt for the LLM. Do you know which open source models work best or do you just use gemini in production?

Also, looking at the docs, Gemini 2.5 flash is getting deprecated by June 17th https://ai.google.dev/gemini-api/docs/deprecations#gemini-2.... (I keep getting emails from Google about it), so might want to update that to Gemini 3 Flash in the examples.

HTML -> markdown -> LLM is standard practice. We strip elements like aside, embed, head , iframe etc. the criteria is conservatively set to avoid removing too many elements (especially in extractMain mode)

https://github.com/lightfeed/extractor/blob/main/src/convert...

I have used gemma 3 and had good results.

Once Gemini 3 flash drops the preview suffix, will update the examples. Thank you for the pointer.