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#!/usr/bin/env python3
"""Summarize per-model success rate for LandingPageGenerator-H_A2A.
Success criterion: `file_exists` in `html_validation.json` is true.
"""
import json
import os
from pathlib import Path
from collections import defaultdict
# Base directory and model list
BASE_DIR = Path("/Users/wzr/TOSEM-2025/RESULTS")
MODELS = [
"DeepSeek-R1",
"DeepSeek-V3-1",
"GPT-4o-mini",
"GPT-5",
"Gemini-2.5-flash",
"Gemini-2.5-flash-nothinking",
"Qwen3-235b",
]
PROJECT_NAME = "LandingPageGenerator-H_A2A"
def analyze_model_results():
"""Analyze execution results for each model."""
results = {}
for model in MODELS:
test_results_dir = BASE_DIR / model / PROJECT_NAME / "test_results"
if not test_results_dir.exists():
print(
f"⚠️ test_results directory not found for model {model}: {test_results_dir}"
)
continue
model_stats = {
"success_count": 0,
"failure_count": 0,
"total_count": 0,
"sessions": [],
}
# Iterate over all session subfolders
for session_dir in sorted(test_results_dir.iterdir()):
if not session_dir.is_dir():
continue
html_validation = session_dir / "html_validation.json"
if not html_validation.exists():
continue
try:
with open(html_validation, "r", encoding="utf-8") as f:
validation_data = json.load(f)
# Success criterion: file_exists is true
success = validation_data.get("file_exists", False)
score = validation_data.get("score", 0)
grade = validation_data.get("grade", "F")
model_stats["total_count"] += 1
if success:
model_stats["success_count"] += 1
else:
model_stats["failure_count"] += 1
model_stats["sessions"].append(
{
"session": session_dir.name,
"success": success,
"file_exists": success,
"score": score,
"grade": grade,
"error": validation_data.get("error_message"),
}
)
except Exception as e:
print(f"❌ Error reading {html_validation}: {e}")
results[model] = model_stats
return results
def print_summary(results):
"""Print a summary to stdout."""
print("\n" + "=" * 80)
print(f"Model Execution Summary - {PROJECT_NAME}")
print("=" * 80 + "\n")
for model, stats in results.items():
total = stats["total_count"]
success = stats["success_count"]
failure = stats["failure_count"]
if total > 0:
success_rate = (success / total) * 100
print(f"📊 {model}")
print(f" Total: {total}")
print(f" Success: {success} (file_exists=true, {success_rate:.1f}%)")
print(f" Failure: {failure} (file_exists=false, {100-success_rate:.1f}%)")
print()
else:
print(f"📊 {model}")
print(" No data")
print()
print("=" * 80)
def save_detailed_results(results, output_file="success_detailed_results.json"):
"""Save detailed results to a JSON file."""
output_path = Path(__file__).parent / output_file
with open(output_path, "w", encoding="utf-8") as f:
json.dump(results, f, indent=2, ensure_ascii=False)
print(f"\n✅ Detailed results saved to: {output_path}")
def save_csv_summary(results, output_file="success_rate.csv"):
"""Save the summary to a CSV file."""
import csv
output_path = Path(__file__).parent / output_file
with open(output_path, "w", newline="", encoding="utf-8") as f:
writer = csv.writer(f)
writer.writerow(["Model", "Total", "Success", "Failure", "Success_Rate(%)"])
for model, stats in results.items():
total = stats["total_count"]
success = stats["success_count"]
failure = stats["failure_count"]
success_rate = (success / total * 100) if total > 0 else 0
writer.writerow([model, total, success, failure, f"{success_rate:.2f}"])
print(f"✅ CSV summary saved to: {output_path}")
if __name__ == "__main__":
print(f"Starting success rate analysis - {PROJECT_NAME}")
print("Success criterion: file_exists in html_validation.json is true\n")
results = analyze_model_results()
print_summary(results)
save_detailed_results(results)
save_csv_summary(results)
print("\n✅ Done!")