"""
Lab 5.10: CI/CD Pipeline

Create a golden dataset and automated regression gate.
"""

import json
import sys
from typing import Any


# TODO 1: Import or define your agent
# from my_agent import run_agent


# TODO 2: Define the CI/CD pipeline
class AgentCIPipeline:
    """
    CI/CD pipeline for agents.
    
    Stages:
    1. CHECKOUT — latest agent config
    2. EVAL — run against golden dataset
    3. GATE — pass@k >= threshold?
    4. PROMOTE — deploy if pass
    5. ROLLBACK — revert if fail
    """
    
    def __init__(self, golden_dataset_path: str, threshold: float = 0.8):
        self.golden_dataset = json.load(open(golden_dataset_path))
        self.threshold = threshold
    
    def run_eval(self) -> dict:
        """
        Run agent against golden dataset.
        Returns pass@1, pass@3, pass@5 scores.
        """
        pass  # TODO
    
    def check_gate(self, eval_results: dict) -> bool:
        """
        Check if eval results pass the gate.
        Returns True if pass@3 >= threshold.
        """
        pass  # TODO
    
    def promote(self):
        """Promote new agent config to production."""
        # TODO: Copy new config to production path
        # TODO: Restart agent service
        # TODO: Log deployment
        pass
    
    def rollback(self, reason: str):
        """Rollback to previous agent config."""
        # TODO: Restore previous config
        # TODO: Log rollback reason
        # TODO: Alert operator
        pass
    
    def run(self):
        """Execute the full CI/CD pipeline."""
        print("=" * 50)
        print("Agent CI/CD Pipeline")
        print("=" * 50)
        
        print("\n[CHECKOUT] Loading agent config...")
        # TODO: load current config
        
        print("\n[EVAL] Running golden dataset...")
        results = self.run_eval()
        print(f"  pass@1: {results['pass@1']:.1%}")
        print(f"  pass@3: {results['pass@3']:.1%}")
        
        print(f"\n[GATE] Threshold: {self.threshold:.0%}")
        if self.check_gate(results):
            print("  ✓ Gate passed. Promoting to production...")
            self.promote()
            print("  ✓ Deployment complete")
        else:
            print("  ✗ Gate failed. Rolling back...")
            self.rollback(f"pass@3 {results['pass@3']:.1%} < threshold {self.threshold:.0%}")
            print("  ✓ Rollback complete")
            sys.exit(1)


if __name__ == "__main__":
    pipeline = AgentCIPipeline("golden_dataset.json", threshold=0.8)
    pipeline.run()