Top-k is the number of closest chunks the system passes forward. A small k keeps the context tight but risks leaving out the one passage that holds the answer; a large k raises the chance of including it but also floods the model with unrelated text that can pull the answer off course. Choosing k is therefore a balance between missing evidence and diluting it.
How AI Answers Questions About Documents It Never Learned