You want to assign urgency and sentiment categories to a large number of customer emails. You want to get a valid json string output for creating custom applications. You decide to develop a prompt for the same using generative Al hub.

What is the main purpose of the following code in this context?

prompt_test = """Your task is to extract and categorize messages. Here are some examples:

{{?technique_examples}}

Use the examples when extract and categorize the following message:

{{?input}}

Extract and return a json with the following keys and values:

- "urgency" as one of {{?urgency}}

- "sentiment" as one of {{?sentiment}}

"categories" list of the best matching support category tags from: {{?categories}}

Your complete message should be a valid json string that can be read directly and only contains the keys mentioned in t

import random random.seed(42) k = 3

examples random. sample (dev_set, k) example_template = """ {example_input} examples

'\n---\n'.join([example_template.format(example_input=example ["message"], example_output=json.dumps (example[

f_test = partial (send_request, prompt=prompt_test, technique_examples examples, **option_lists) response = f_test(input=mail["message"])