"""Evaluation Harness Runner for GCP Solution Architecture Agent.

Uses google.adk.evaluation.Evaluator with PostgreSQL database metrics persistence.
"""

import json
import logging
from pathlib import Path
from typing import Any, Dict, List

from app.adk.evaluation import ADKEvaluator
from app.config import get_settings

logger = logging.getLogger(__name__)


class EvalHarness:
    """Offline Evaluation Harness for running benchmark suites against ADK agents."""

    def __init__(self, dataset_path: Path | None = None) -> None:
        settings = get_settings()
        self.dataset_path = dataset_path or settings.EVAL_DATASET_PATH
        self.evaluator = ADKEvaluator()

    def load_benchmark_cases(self) -> List[Dict[str, Any]]:
        """Load benchmark dataset JSON."""
        if not self.dataset_path.is_file():
            logger.error("Benchmark dataset not found at %s", self.dataset_path)
            return []

        with open(self.dataset_path, "r", encoding="utf-8") as f:
            return json.load(f)

    def run_eval_suite(self) -> Dict[str, Any]:
        """Execute all benchmark test cases through ADKEvaluator and compile scoring metrics."""
        cases = self.load_benchmark_cases()
        if not cases:
            return {"status": "error", "message": "No benchmark cases loaded."}

        results = []
        total_passed = 0

        for case in cases:
            logger.info("Evaluating ADK benchmark case: %s", case.get("id"))
            eval_result = self.evaluator.evaluate_benchmark_case(case)
            results.append(eval_result)

            if eval_result.get("passed"):
                total_passed += 1

        pass_rate = (total_passed / len(cases)) * 100.0 if cases else 0.0

        summary = {
            "total_cases": len(cases),
            "passed_cases": total_passed,
            "failed_cases": len(cases) - total_passed,
            "pass_rate_percentage": pass_rate,
            "results": results,
        }

        return summary


def main() -> None:
    """CLI Runner for Evaluation Harness."""
    harness = EvalHarness()
    summary = harness.run_eval_suite()
    print("=== GCP Solution Architecture Agent ADK Benchmark Summary ===")
    print(json.dumps(summary, indent=2))


if __name__ == "__main__":
    main()