from __future__ import annotations

import time
from typing import Any


MOCK_FAST = "mock-fast@1.0.0"
MOCK_ACCURATE = "mock-accurate@1.0.0"


def list_models() -> list[str]:
    return [MOCK_FAST, MOCK_ACCURATE]


def _image_mean_rgb(image) -> list[float]:
    rgb = image.convert("RGB")
    pixels = list(rgb.getdata())
    n = len(pixels)
    if n == 0:
        return [0.0, 0.0, 0.0]
    r = sum(p[0] for p in pixels) / n
    g = sum(p[1] for p in pixels) / n
    b = sum(p[2] for p in pixels) / n
    return [round(r, 2), round(g, 2), round(b, 2)]


def predict(model_version: str, kind: str, payload: Any) -> dict:
    if model_version not in list_models():
        raise ValueError(f"Unknown model: {model_version}")

    if kind == "image":
        output: dict[str, Any] = {"mean_rgb": _image_mean_rgb(payload)}
    elif kind == "text":
        output = {"length": len(payload)}
    else:
        raise ValueError(f"Unsupported input kind: {kind}")

    metadata: dict[str, Any] = {"model_version": model_version}

    if model_version == MOCK_ACCURATE:
        time.sleep(0.2)
        metadata["confidence"] = 0.95

    return {"output": output, "metadata": metadata}