"""Artifact save/load and model metadata for Brettapps/trifecta-bro-v1."""

from __future__ import annotations

import json
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Any

from .predictor import Race, Runner, TrifectaPredictor


MODEL_ID = "Brettapps/trifecta-bro/v1"
MODEL_CARD_VERSION = "1.0.0"


@dataclass
class ModelArtifact:
    model_id: str
    version: str
    method: str
    feature_weights: dict[str, float]
    notes: str


# The "learned" configuration of the rule-based model. Documented explicitly so
# the published artifact is interpretable and reproducible.
ARTIFACT = ModelArtifact(
    model_id=MODEL_ID,
    version=MODEL_CARD_VERSION,
    method="multi-factor rule-based scoring (0-100)",
    feature_weights={
        "recent_form": 25.0,
        "overall_win_pct": 20.0,
        "overall_place_pct": 10.0,
        "track_strike": 10.0,
        "distance_strike": 8.0,
        "condition_strike": 8.0,
        "barrier_draw": 5.0,
        "career_prize": 5.0,
    },
    notes=(
        "Open-source multi-factor trifecta scorer. No supervised training "
        "(no historical race results available in data/results/). Scores are "
        "deterministic given runner form/stat inputs. Future v2 will train a "
        "gradient-boosted model on observed outcomes."
    ),
)


def save_artifact(out_dir: str | Path) -> Path:
    out_dir = Path(out_dir)
    out_dir.mkdir(parents=True, exist_ok=True)
    path = out_dir / "model_artifact.json"
    path.write_text(json.dumps(asdict(ARTIFACT), indent=2))
    return path


def load_artifact(path: str | Path) -> ModelArtifact:
    data = json.loads(Path(path).read_text())
    return ModelArtifact(**data)


def predict_race(race: Race) -> dict[str, Any]:
    """Convenience: run the packaged predictor on a Race."""
    return TrifectaPredictor().predict(race)


def race_from_payload(payload: dict[str, Any]) -> Race:
    """Build a Race from the Trifecta-Bro predictions JSON shape."""
    form = payload.get("form", {})
    runners = [
        Runner(
            number=r.get("number", 0),
            name=r.get("name", ""),
            jockey=r.get("jockey", ""),
            trainer=r.get("trainer", ""),
            weight=r.get("weight"),
            barrier=r.get("barrier"),
            form=r.get("form", ""),
            last20Starts=r.get("last20Starts", ""),
            careerPrizeMoney=r.get("careerPrizeMoney", "$0"),
            scratched=bool(r.get("scratched", False)),
            stats=r.get("stats", {}),
        )
        for r in form.get("runners", [])
    ]
    return Race(
        date=payload.get("date", ""),
        track=payload.get("track", ""),
        track_slug=payload.get("track_slug", ""),
        race_number=str(payload.get("race_number", "")),
        race_name=payload.get("race_name", ""),
        distance=payload.get("distance", ""),
        condition=payload.get("condition", ""),
        weather=payload.get("weather", ""),
        race_class=payload.get("race_class", ""),
        start_time=payload.get("start_time", ""),
        prize_money=payload.get("prize_money", ""),
        number_of_runners=int(payload.get("number_of_runners", 0) or 0),
        runners=runners,
    )