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# Confabulation_check.py
#
# This file contains the functions that are used to check the confabulation of the user's input.
#
#
# Imports
#
# External Imports
#
# Local Imports
#
#
####################################################################################################
#
# Functions:
from App_Function_Libraries.Chat import chat_api_call
from App_Function_Libraries.Benchmarks_Evaluations.ms_g_eval import validate_inputs, detailed_api_error
def simplified_geval(transcript: str, summary: str, api_name: str, api_key: str, temp: float = 0.7) -> str:
"""
Perform a simplified version of G-Eval using a single query to evaluate the summary.
Args:
transcript (str): The original transcript
summary (str): The summary to be evaluated
api_name (str): The name of the LLM API to use
api_key (str): The API key for the chosen LLM
temp (float, optional): The temperature parameter for the API call. Defaults to 0.7.
Returns:
str: The evaluation result
"""
try:
validate_inputs(transcript, summary, api_name, api_key)
except ValueError as e:
return str(e)
prompt = f"""You are an AI assistant tasked with evaluating the quality of a summary. You will be given an original transcript and a summary of that transcript. Your task is to evaluate the summary based on the following criteria:
1. Coherence (1-5): How well-structured and organized is the summary?
2. Consistency (1-5): How factually aligned is the summary with the original transcript?
3. Fluency (1-3): How well-written is the summary in terms of grammar, spelling, and readability?
4. Relevance (1-5): How well does the summary capture the important information from the transcript?
Please provide a score for each criterion and a brief explanation for your scoring. Then, give an overall assessment of the summary's quality.
Original Transcript:
{transcript}
Summary to Evaluate:
{summary}
Please provide your evaluation in the following format:
Coherence: [score] - [brief explanation]
Consistency: [score] - [brief explanation]
Fluency: [score] - [brief explanation]
Relevance: [score] - [brief explanation]
Overall Assessment: [Your overall assessment of the summary's quality]
"""
try:
result = chat_api_call(
api_name,
api_key,
prompt,
"",
temp=temp,
system_message="You are a helpful AI assistant tasked with evaluating summaries."
)
except Exception as e:
return detailed_api_error(api_name, e)
formatted_result = f"""
Confabulation Check Results:
{result}
"""
return formatted_result |