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)
Updated about 1 month ago