from __future__ import annotations

import numpy as np
import pytest

from core.models import Bounds
from perception.ocr import OCRBox, PaddleOCREngine, parse_paddle_result, run_ocr


def test_paddle_ocr_engine_disables_doc_preprocessing_by_default() -> None:
    # Screenshots are flat, upright digital captures, not photographed paper
    # documents: PaddleOCR's document-unwarping preprocessing has nothing real
    # to correct and instead warps the image, so detected box coordinates no
    # longer line up with the original screenshot.
    engine = PaddleOCREngine(lang="ch")

    assert engine.kwargs["use_doc_orientation_classify"] is False
    assert engine.kwargs["use_doc_unwarping"] is False


def test_paddle_ocr_engine_lets_callers_override_doc_preprocessing() -> None:
    engine = PaddleOCREngine(use_doc_unwarping=True)

    assert engine.kwargs["use_doc_unwarping"] is True


def test_parse_paddle_result_accepts_ndarray_fields() -> None:
    boxes = parse_paddle_result(
        {
            "rec_texts": np.array(["Search"]),
            "rec_scores": np.array([0.95]),
            "rec_boxes": np.array([[1, 2, 10, 12]]),
        }
    )

    assert boxes == [
        OCRBox(
            text="Search",
            bounds=Bounds(x=1.0, y=2.0, width=9.0, height=10.0),
            confidence=0.95,
        )
    ]


class CallableJsonResult:
    def json(self) -> dict[str, object]:
        return {
            "res": {
                "rec_texts": ["Search"],
                "rec_scores": [0.95],
                "rec_boxes": [[1, 2, 10, 12]],
            }
        }


def test_parse_paddle_result_accepts_callable_json_result() -> None:
    assert parse_paddle_result(CallableJsonResult()) == [
        OCRBox(
            text="Search",
            bounds=Bounds(x=1.0, y=2.0, width=9.0, height=10.0),
            confidence=0.95,
        )
    ]


class FailingOCREngine:
    def extract(self, image: bytes | str) -> list[OCRBox]:
        raise ValueError(
            "The truth value of an array with more than one element is ambiguous"
        )


def test_run_ocr_degrades_when_ocr_engine_raises() -> None:
    assert run_ocr(b"image", engine=FailingOCREngine()) == []  # type: ignore[arg-type]


def test_run_ocr_strict_mode_preserves_engine_error() -> None:
    with pytest.raises(ValueError, match="truth value"):
        run_ocr(b"image", engine=FailingOCREngine(), strict=True)  # type: ignore[arg-type]