"""
Simple CLI runner to:
1) Build a new pack from pasted scenario text.
2) Run Phase 1 (clarifications).
3) Exit with the questions so an operator/UI can answer them.
4) After answers are saved to clarifications.json, run Phase 2 to produce final output.

Usage (example):
    python -m clarityops.pipeline.main --scenario "My scenario text..." --name "oncology_pilot"
Then answer questions by editing packs/<slug>/clarifications.json and run:
    python -m clarityops.pipeline.main --pack packs/oncology_pilot --phase2
"""

import argparse
from pathlib import Path
import json

from .pack_builder import build_pack_from_scenario
from .run_two_phase import run_clarityops, call_model

def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--scenario", type=str, help="Free-form scenario text")
    parser.add_argument("--name", type=str, default="", help="Hint for pack folder name")
    parser.add_argument("--pack", type=str, help="Existing pack to run")
    parser.add_argument("--phase2", action="store_true", help="Run Phase 2 using existing clarifications.json")
    args = parser.parse_args()

    root = Path(__file__).parents[2]

    if args.scenario:
        # Build pack from scenario text
        pack_dir = build_pack_from_scenario(root, args.scenario, args.name)
        print(f"[OK] Created pack: {pack_dir}")
        print("Next step: Run Phase 1 to generate clarification questions (the pipeline will request answers).")

        # Run Phase 1 only by triggering pipeline and capturing questions
        # We let run_clarityops raise for missing clarifications.json answers to surface Phase 1 questions.
        try:
            _output, clarif_raw = run_clarityops(str(pack_dir))
        except RuntimeError as e:
            print("\n[PHASE 1 QUESTIONS]\n")
            # We don't have direct access to clarif_raw here since run_clarityops expects clarifications.json.
            # In a production stack, you'd split run_two_phase to expose a "phase1_only" call that returns questions.
            # For now, instruct the operator to open the logs or integrate your model streaming.
            print("Phase 1 questions have been generated by the model.")
            print("Open your app's model output/log to capture them, then write answers into:")
            print(f"  {pack_dir}/clarifications.json")
            print("\nTip: In production, expose a UI to show and record these answers.")
            return

    elif args.pack and args.phase2:
        output, clarif_questions = run_clarityops(args.pack)
        print("[OK] Phase 2 completed. Final JSON:")
        print(json.dumps(output, ensure_ascii=False, indent=2))
    else:
        parser.print_help()

if __name__ == "__main__":
    main()