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Running
on
Zero
File size: 4,453 Bytes
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import os
import csv
import json
from datetime import datetime
import pandas as pd
def save_vote_details(example, model_a, model_b, winner, feedback, summary_a, summary_b):
"""
Save detailed vote information to CSV file for future analysis.
Parameters:
- example: The question and context information
- model_a, model_b: Names of models being compared
- winner: 'left', 'right', 'tie', or 'neither' indicating the vote result
- feedback: List of feedback options selected by the user
- summary_a, summary_b: The model outputs (summaries)
"""
# Prepare the vote details record
vote_record = {
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
"model_a": model_a,
"model_b": model_b,
"winner": winner,
"feedback": json.dumps(feedback),
"question_id": example.get("id", "unknown"),
"question": example.get("question", ""),
"insufficient_context": example.get("insufficient", False),
"summary_a": summary_a,
"summary_b": summary_b
}
# Define the path to the CSV file
csv_path = os.path.join('utils', 'vote_details.csv')
file_exists = os.path.exists(csv_path)
try:
# Open the file in append mode
with open(csv_path, 'a', newline='', encoding='utf-8') as f:
writer = csv.DictWriter(f, fieldnames=vote_record.keys())
# Write header if file doesn't exist
if not file_exists:
writer.writeheader()
# Write the vote record
writer.writerow(vote_record)
print(f"Vote details saved to {csv_path}")
except Exception as e:
print(f"Error saving vote details: {e}")
# Create a backup copy every 10 votes
try:
if os.path.exists(csv_path):
with open(csv_path, 'r', encoding='utf-8') as f:
num_votes = sum(1 for _ in f) - 1 # Subtract 1 for header
if num_votes % 10 == 0:
backup_path = os.path.join('utils', f'vote_details_backup_{datetime.now().strftime("%Y%m%d_%H%M%S")}.csv')
with open(csv_path, 'r', encoding='utf-8') as src, open(backup_path, 'w', encoding='utf-8') as dst:
dst.write(src.read())
print(f"Created backup at {backup_path}")
except Exception as e:
print(f"Error creating backup: {e}")
def get_vote_statistics():
"""
Analyze vote details and provide statistics.
Returns:
- Dictionary of statistics about votes
"""
csv_path = os.path.join('utils', 'vote_details.csv')
if not os.path.exists(csv_path):
return {"error": "No vote data available"}
try:
# Read the CSV into a DataFrame
df = pd.read_csv(csv_path)
# Basic statistics
stats = {
"total_votes": len(df),
"winner_distribution": {
"left": len(df[df['winner'] == 'left']),
"right": len(df[df['winner'] == 'right']),
"tie": len(df[df['winner'] == 'tie']),
"neither": len(df[df['winner'] == 'neither'])
},
"model_appearances": {},
"model_wins": {},
"feedback_frequency": {}
}
# Count model appearances and wins
for model in set(list(df['model_a']) + list(df['model_b'])):
a_appearances = len(df[df['model_a'] == model])
b_appearances = len(df[df['model_b'] == model])
stats["model_appearances"][model] = a_appearances + b_appearances
a_wins = len(df[(df['model_a'] == model) & (df['winner'] == 'left')])
b_wins = len(df[(df['model_b'] == model) & (df['winner'] == 'right')])
stats["model_wins"][model] = a_wins + b_wins
# Process feedback
all_feedback = []
for feedback_json in df['feedback']:
try:
feedback_list = json.loads(feedback_json)
all_feedback.extend(feedback_list)
except:
pass
for feedback in all_feedback:
stats["feedback_frequency"][feedback] = stats["feedback_frequency"].get(feedback, 0) + 1
return stats
except Exception as e:
return {"error": f"Error analyzing vote data: {e}"}
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