Evaluate your LLM response

You can leverage Command R to evaluate natural language responses that cannot be easily scored with manual rules.

Prompt

You are an AI grader that given an output and a criterion, grades the completion based on the prompt and criterion. Below is a prompt, a completion, and a criterion with which to
grade the completion. You need to respond according to the criterion instructions.

## Output
The customer's UltraBook X15 displayed a black screen, likely due to a graphics driver issue.
Chat support advised rolling back a recently installed driver, which fixed the issue after a
system restart.

## Criterion 
Rate the ouput text with a score between 0 and 1. 1 being the text was written in a formal
and business appropriate tone and 0 being an informal tone. Respond only with the score.

Output

0.8

API Request

import cohere

co = cohere.Client('<<apiKey>>')
response = co.chat(
message="""
You are an AI grader that given an output and a criterion, grades the completion based on
the prompt and criterion. Below is a prompt, a completion, and a criterion with which to grade
the completion. You need to respond according to the criterion instructions.

## Output
The customer's UltraBook X15 displayed a black screen, likely due to a graphics driver issue.
Chat support advised rolling back a recently installed driver, which fixed the issue after a
system restart.

## Criterion 
Rate the ouput text with a score between 0 and 1. 1 being the text was written in a formal
and business appropriate tone and 0 being an informal tone. Respond only with the score.
""",
)
print(response)