I guess, it involves splitting a file into smaller document snippets, getting page numbers and such, and calculating embeddings for each snippet—that’s the usual approach. Specific signals vary by use case.
Hopefully, @jerednel can add more details.
Hopefully, @jerednel can add more details.
My retriever functions will typically use metadata in combination with the similarity search to do impart some sort of influence or for reranking.