judge-arena / prompts.py
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feat: add flow judge model
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# Default values for compatible mode
DEFAULT_EVAL_CRITERIA = """Does the model provide relevant and useful responses to the user's needs or questions?"""
DEFAULT_SCORE_1 = "The model's responses are irrelevant or unhelpful to the user's needs or queries."
DEFAULT_SCORE_2 = "The model sometimes provides helpful information, but often fails to address the user's actual needs or questions."
DEFAULT_SCORE_3 = "The model generally provides helpful responses that address the user's needs, though it may occasionally miss the mark."
DEFAULT_SCORE_4 = "The model regularly provides helpful responses that are well-aligned with the user's inquiries, with only rare inaccuracies."
DEFAULT_SCORE_5 = "The model consistently offers highly relevant and useful responses that perfectly cater to the user's needs and inquiries."
# Default Eval Prompt
DEFAULT_EVAL_PROMPT = """Does the model provide relevant and useful responses to the user's needs or questions?
Scoring Rubric:
Score 1: The model's responses are irrelevant or unhelpful to the user's needs or queries.
Score 2: The model sometimes provides helpful information, but often fails to address the user's actual needs or questions.
Score 3: The model generally provides helpful responses that address the user's needs, though it may occasionally miss the mark.
Score 4: The model regularly provides helpful responses that are well-aligned with the user's inquiries, with only rare inaccuracies.
Score 5: The model consistently offers highly relevant and useful responses that perfectly cater to the user's needs and inquiries.
[User Query]: {{input}}
[AI Response]: {{response}}"""
# Split the eval prompt into editable and fixed parts
DEFAULT_EVAL_PROMPT_EDITABLE = """Does the model provide relevant and useful responses to the user's needs or questions?
Scoring Rubric:
Score 1: The model's responses are irrelevant or unhelpful to the user's needs or queries.
Score 2: The model sometimes provides helpful information, but often fails to address the user's actual needs or questions.
Score 3: The model generally provides helpful responses that address the user's needs, though it may occasionally miss the mark.
Score 4: The model regularly provides helpful responses that are well-aligned with the user's inquiries, with only rare inaccuracies.
Score 5: The model consistently offers highly relevant and useful responses that perfectly cater to the user's needs and inquiries."""
# Fixed suffix that will always be appended
FIXED_EVAL_SUFFIX = """
[User Query]: {{input}}
[AI Response]: {{response}}"""
# Define the Prometheus prompt used by default (without reference)
PROMETHEUS_PROMPT = """###Task Description:
An instruction (might include an Input inside it) and a response to evaluate are given.
1. Write a detailed feedback that assesses the quality of the response strictly based on the given score rubric, not evaluating in general.
2. After writing the feedback, write a score that is an integer between 1 and 5.
3. The output format should look as follows: "Feedback: (write a feedback for criteria) [RESULT] (an integer number between 1 and 5)"
4. Please do not generate any other openings, closings, or explanations.
###The instruction to evaluate:
{human_input}
###Response to evaluate:
{ai_response}
###Score Rubrics:
[{eval_criteria}]
Score 1: {score1_desc}
Score 2: {score2_desc}
Score 3: {score3_desc}
Score 4: {score4_desc}
Score 5: {score5_desc}
###Feedback:
"""
# Define the Prometheus prompt with reference response
PROMETHEUS_PROMPT_WITH_REFERENCE = """###Task Description:
An instruction (might include an Input inside it), a response to evaluate, a reference answer that gets a score of 5, and a score rubric representing an evaluation criteria are given.
1. Write a detailed feedback that assesses the quality of the response strictly based on the given score rubric, not evaluating in general.
2. After writing the feedback, write a score that is an integer between 1 and 5.
3. The output format should look as follows: "Feedback: (write a feedback for criteria) [RESULT] (an integer number between 1 and 5)"
4. Please do not generate any other openings, closings, or explanations.
###The instruction to evaluate:
{human_input}
###Response to evaluate:
{ai_response}
###Reference Answer (Score 5):
{ground_truth_input}
###Score Rubrics:
[{eval_criteria}]
Score 1: {score1_desc}
Score 2: {score2_desc}
Score 3: {score3_desc}
Score 4: {score4_desc}
Score 5: {score5_desc}
###Feedback:
"""
# Define the Flow Judge prompt
FLOW_JUDGE_PROMPT = """# GOAL
Your job is to evaluate a task carried out by an AI system powered by a large \
language model.
You will be provided with the inputs and output of the task, as well as the evaluation criteria \
and scoring rubric. Your task is to evaluate the output of the AI system based on the evaluation \
criteria and scoring rubric provided.
# INPUT
Below are the inputs required for performing the task:
<inputs>
{INPUTS}
</inputs>
# OUTPUT
Below is the output of the task:
<output>
{OUTPUT}
</output>
# EVALUATION CRITERIA AND SCORING RUBRIC
Here are the evaluation criteria and the rubric that you need to use for evaluating the task:
<evaluation_criteria>
{EVALUATION_CRITERIA}
</evaluation_criteria>
<scoring_rubric>
{RUBRIC}
</scoring_rubric>
# INSTRUCTIONS FOR THE EVALUATION
1. Understand the task and criteria: Familiarize yourself with the task to be evaluated. \
Review the evaluation criteria and scoring rubric to understand the different levels of \
performance and the descriptions for each score.
2. Review the inputs and output: Look at the inputs provided for the task. Examine the output \
generated from completing the task.
3. Compare output to score descriptions: Compare the output against the criteria and score \
descriptions in the scoring rubric. For each criterion,decide which description best matches the \
output.
4. After comparing the output to the score descriptions, pay attention to the small details that \
might impact the final score that you assign. Sometimes a small difference can dictate the final \
score.
5. Write verbal feedback justifying your evaluation that includes a detailed rationale, referring \
to specific aspects of the output and comparing them to the rubric.
6. Assign a final score based on the scoring rubric.
## FORMAT FOR THE EVALUATION
- Write the verbal feedback inside <feedback> tags without any additional surrounding text.
- Write the numeric score inside <score> tags, without any additional surrounding text and always \
after the feedback.
Please accurately evaluate the task. Strictly adhere to the evaluation criteria and rubric."""
# Judge system prompt for non-Prometheus models
JUDGE_SYSTEM_PROMPT = """Please act as an impartial judge and evaluate based on the user's instruction. Your output format should strictly adhere to JSON as follows: {"feedback": "<write feedback>", "result": <numerical score>}. Ensure the output is valid JSON, without additional formatting or explanations."""