#!/usr/bin/env python3
"""
Compute success rates for LandingPageGenerator-A2A across models.

Success criterion: the `file_exists` field in html_validation.json is true.
"""

import json
import os
from pathlib import Path
from collections import defaultdict

# 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 = "LandingPageGenerator-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 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."""
    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 a 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 field 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!")