Llama 2: Representation Model

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In the documentation, it mentioned that:

_By default, four of the most representative documents will be passed to [DOCUMENTS]. These documents are selected by calculating their similarity (through c-TF-IDF representations) with the main c-TF-IDF representation of the topics. The four best matching documents per topic are selected.
To increase the number of documents passed to [DOCUMENTS], we can use the nr_docs parameter which is accessible in all LLMs on this page._

I am using Llama 2 to represent a label for each cluster. but I don't want to pass only the four of the most representative documents; I want to pass the top 10 or 20 or maybe all the documents.

I try to use the **nr_docs** parameter, but when I check the number of the representative documents, it displays 3.

llama2 = TextGeneration(generator, nr_docs= 20, prompt=prompt)

How can we ensure that Llama 2 provides an accurate and appropriate name if we don't have all of the cluster's documents?

Start by reproducing the Llama 2 TextGeneration example with nr_docs=20 and inspect how the representative-document count is determined. Confirm whether the parameter is honored, then update the behavior or documentation so the resulting document count and supported limits are clear.

Written by the indexing model from the issue text.