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8c10cf2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 | #!/usr/bin/env python3
"""
Calculate success rate for each model in RecruitmentAssistant-A2A task
Success criteria: reports folder exists and contains multiple (>=2) md files
"""
import json
import os
from pathlib import Path
from collections import defaultdict
# Define base path 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 = "RecruitmentAssistant-A2A"
def check_reports_success(reports_dir: Path) -> dict:
"""
Check if reports folder meets success criteria
Success criteria:
1. reports folder exists
2. Contains multiple (>=2) md files
Returns:
{
'success': bool,
'reports_exists': bool,
'md_count': int,
'md_files': list
}
"""
result = {"success": False, "reports_exists": False, "md_count": 0, "md_files": []}
# Check if reports folder exists
if not reports_dir.exists() or not reports_dir.is_dir():
return result
result["reports_exists"] = True
# Count md files
md_files = sorted([f.name for f in reports_dir.glob("*.md")])
result["md_count"] = len(md_files)
result["md_files"] = md_files
# Determine success: at least 2 md files
result["success"] = result["md_count"] >= 2
return result
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"⚠️ Model {model} test_results directory not found: {test_results_dir}"
)
continue
model_stats = {
"success_count": 0,
"failure_count": 0,
"total_count": 0,
"sessions": [],
}
# Iterate through all session subdirectories
for session_dir in sorted(test_results_dir.iterdir()):
if not session_dir.is_dir():
continue
reports_dir = session_dir / "reports"
# Check reports folder and md files
check_result = check_reports_success(reports_dir)
model_stats["total_count"] += 1
if check_result["success"]:
model_stats["success_count"] += 1
else:
model_stats["failure_count"] += 1
model_stats["sessions"].append(
{
"session": session_dir.name,
"success": check_result["success"],
"reports_exists": check_result["reports_exists"],
"md_count": check_result["md_count"],
"md_files": check_result["md_files"],
}
)
results[model] = model_stats
return results
def print_summary(results):
"""Print statistics summary"""
print("\n" + "=" * 80)
print(f"Model Execution Results - {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} sessions")
print(
f" Success: {success} sessions (reports exists with >=2 md files, {success_rate:.1f}%)"
)
print(f" Failure: {failure} sessions ({100-success_rate:.1f}%)")
print()
else:
print(f"📊 {model}")
print(f" No data")
print()
print("=" * 80)
def print_detailed_stats(results):
"""Print detailed statistics"""
print("\n" + "=" * 80)
print("Detailed Statistics")
print("=" * 80 + "\n")
for model, stats in results.items():
if stats["total_count"] == 0:
continue
print(f"### {model}")
print()
# Count md file distribution
md_count_dist = defaultdict(int)
for session in stats["sessions"]:
md_count_dist[session["md_count"]] += 1
print(f"MD File Count Distribution:")
for count in sorted(md_count_dist.keys()):
sessions = md_count_dist[count]
percentage = (sessions / stats["total_count"]) * 100
print(f" {count} files: {sessions} sessions ({percentage:.1f}%)")
# List failed sessions
failed_sessions = [s for s in stats["sessions"] if not s["success"]]
if failed_sessions:
print(f"\nFailed sessions ({len(failed_sessions)} total):")
for session in failed_sessions[:5]: # Show only first 5
reason = (
"reports not found"
if not session["reports_exists"]
else f"only {session['md_count']} md files"
)
print(f" - {session['session']}: {reason}")
if len(failed_sessions) > 5:
print(f" ... and {len(failed_sessions) - 5} more failed sessions")
print()
print("=" * 80)
def save_detailed_results(results, output_file="success_detailed_results.json"):
"""Save detailed results to 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 summary to 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 calculation - {PROJECT_NAME}")
print(
f"Success criteria: reports folder exists and contains multiple (>=2) md files\n"
)
results = analyze_model_results()
print_summary(results)
print_detailed_stats(results)
save_detailed_results(results)
save_csv_summary(results)
print("\n✅ Calculation completed!")
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