"""Arena orchestrator — wire a team + challenge through the loop and persist.

This is the M1 entry the launcher calls: build the room substrate, the VM, and a
manifest-stamped transcript; run the phase machine; freeze the transcript; score
it deterministically. The run/score split mirrors ``bench/score.py`` — results
persist so ``score``/``replay`` never re-run a model.
"""

from __future__ import annotations

import time
from pathlib import Path

from . import comms, scoring, transcript as T
from .challenge import Challenge
from .loop import Budget, run_event
from .team import Team
from .vm import VM


def run_one(team: Team, challenge: Challenge, *, room_kind: str = "local",
            runtime: str = "auto", budget: Budget | None = None,
            profile: str = "balanced", seed: int = 0,
            host: str = "http://127.0.0.1:11434",
            out_dir: str = "/tmp/hh-olympics/runs",
            room_kwargs: dict | None = None, progress=None) -> dict:
    budget = budget or Budget()
    member_names = [m.name for m in team.members]
    room = comms.make_room(room_kind, member_names, **(room_kwargs or {}))

    manifest = {
        "models": team.models, "seed": seed, "topology": team.topology,
        "framing": team.framing, "room_substrate": room.substrate,
        "runtime": runtime, "host": host,
        "budget": {"deliberate_rounds": budget.deliberate_rounds,
                   "implement_attempts": budget.implement_attempts,
                   "max_tokens": budget.max_tokens,
                   "wall_clock_s": budget.wall_clock_s},
        "challenge_meta": challenge.meta, "profile": profile,
        "created": time.strftime("%Y-%m-%dT%H:%M:%S"),
    }
    tx = T.Transcript(team.id, challenge.id, manifest)
    vm = VM(challenge.lang, runtime_kind=runtime)

    room.connect()
    try:
        outcome = run_event(team, challenge, room, vm, tx, budget,
                            host=host, seed=seed, progress=progress)
    finally:
        room.close()

    run_dir = Path(out_dir) / f"{team.id}__{challenge.id}"
    tx_path = run_dir / "transcript.json"
    tx.save(tx_path)

    score = scoring.score_event(outcome, profile=profile,
                                budget={"max_rounds": budget.max_rounds})
    score["transcript"] = str(tx_path)
    score["room_substrate"] = room.substrate
    import json
    (run_dir / "score.json").write_text(json.dumps(score, indent=2))
    return score