Ask HN: Way to extract relevant parts from a PDF based on a question?

This is a key usecase for text embeddings. Essentially it is a process of converting sentences or paragraphs to vectors, where the closeness of vectors then represents a semantic similarity.

So you can convert all the paragraphs in your document into vectors, convert your question into a vector, and then find the e.g. 10 closest vectors, or all that fall under a certain maximum distance, etc.

You can store the embeddings in a vector database, to search across multiple documents.

LlamaIndex is my tool of choice right now

https://docs.llamaindex.ai/en/stable/

https://docs.llamaindex.ai/en/stable/examples/citation/pdf_p...

I'm using it with Qdrant and can get the text sections & locations that are tied to the answer & citation as well

Try: https://notebooklm.google/