Doubt about sumarization and A.I

Hello friends

I would like to ask a question about the concept of API requests.

I am using Gemini, and I decided to run the following test:

I am studying languages and using a flashcard app.

This app (AnkiApp) allows uploading content via a CSV file.

I downloaded a list of 10,000 words from GitHub.

1. I created a workflow in Knime to read the Excel file with the 10,000 rows.

2. I connected to Gemini and set up the following prompt: Translate the word from english to japanese and give me at least 1 example, or if needed, max of 5 examples with context : “word”

3. My list has 10,000 words, meaning 10,000 rows. When I send the request to Gemini, 10,000 requests will be made for each row. The return will be the translation with the examples (taking about 20 minutes)

But my real doubt arose from the following question:

What if my database were related to another topic and I needed Gemini to analyze the entire content to give me a summary of the result?

What I want to know is, if the result of the analysis depended on reading the entire document for the A.I. to then provide an output, would I have to make 10,000 requests?

Practically and performantly, how is a summarized analysis done by an A.I. on a spreadsheet with 10,000 rows?

For me doesn’t make sense do it this way.

(I understand that Knime has its own tools for data analysis, like GroupBy, Average, etc., and obviously not everything needs to be created by A.I., but my question is what to do in a situation that requires summarization of a large table of information with rows)

(I understand that if I wanted to summarize a text-related subject, I wouldn’t do it row by row, but would instead use a datatype like ‘document’)