"""Tests for the document classifier."""

from __future__ import annotations

from pathlib import Path
from unittest.mock import patch

import pytest
from PIL import Image

from odoo_ocr.pipeline.classifier import classify_document
from odoo_ocr.schemas.document import DocumentClass


@pytest.fixture
def blank_image() -> Image.Image:
    return Image.new("RGB", (100, 100), color="white")


@pytest.mark.asyncio
async def test_heuristic_digital_pdf(tmp_path: Path) -> None:
    pdf_path = tmp_path / "invoice.pdf"
    # Minimal valid PDF with text via pymupdf
    import fitz

    doc = fitz.open()
    page = doc.new_page()
    page.insert_text((50, 50), "Invoice number 12345\nVendor: Acme")
    doc.save(str(pdf_path))
    doc.close()

    from odoo_ocr.config import Settings
    from tests.conftest import FakeVLMClient

    client = FakeVLMClient()
    result = await classify_document(pdf_path, [], client, Settings())
    assert result.category == DocumentClass.digital_pdf
    assert result.confidence >= 0.90


@pytest.mark.asyncio
async def test_heuristic_scanned_print(blank_image: Image.Image) -> None:
    # Blank image has low handwriting score
    from odoo_ocr.config import Settings
    from tests.conftest import FakeVLMClient

    client = FakeVLMClient()
    result = await classify_document(Path("scan.jpg"), [blank_image], client, Settings())
    assert result.category == DocumentClass.scanned_print


@pytest.mark.asyncio
async def test_vlm_classifier_fallback(blank_image: Image.Image) -> None:

    from odoo_ocr.config import Settings
    from tests.conftest import FakeVLMClient

    client = FakeVLMClient(
        responses={
            "document classifier": {
                "category": "handwritten",
                "confidence": 0.91,
                "reasoning": "handwritten text visible",
            }
        }
    )
    with patch(
        "odoo_ocr.pipeline.classifier._heuristic_classify", return_value=None
    ):
        result = await classify_document(Path("unknown.png"), [blank_image], client, Settings())
    assert result.category == DocumentClass.handwritten
    assert result.confidence == 0.91


@pytest.mark.asyncio
async def test_empty_pages_raises() -> None:
    """The VLM fallback must fail cleanly for documents with no renderable pages."""
    from odoo_ocr.config import Settings
    from tests.conftest import FakeVLMClient

    client = FakeVLMClient()
    with (
        patch("odoo_ocr.pipeline.classifier._heuristic_classify", return_value=None),
        pytest.raises(ValueError, match="no renderable pages"),
    ):
        await classify_document(Path("empty.pdf"), [], client, Settings())