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db4ba8d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | import pytest
from src.services.ocr_engine_svc import OCREngineService, extract_ceisa_fields_from_text, settings
def test_extract_ceisa_fields_from_text_for_cipl_fields():
text = """
Consignee / Importer: PT CIKARANG LOGISTICS INDONESIA
NPWP: 01.234.567.8-999.000
Total Packages: 42
Gross Weight: 1,250.50 KGS
Currency: USD
CIF USD 12500.75
"""
fields = extract_ceisa_fields_from_text(text)
assert fields["importer_name"] == "PT CIKARANG LOGISTICS INDONESIA"
assert fields["importer_npwp"] == "01.234.567.8-999.000"
assert fields["total_packages"] == 42
assert fields["gross_weight"] == 1250.50
assert fields["currency"] == "USD"
assert fields["cif_value"] == 12500.75
@pytest.mark.asyncio
async def test_prepare_document_runs_dual_ocr_candidates(monkeypatch):
service = OCREngineService()
async def fake_paddle(page_images):
return {
"fields": {"importer_npwp": "01.234.567.8-999.000"},
"text": "paddle text",
"confidence": 0.82,
}
async def fake_azure(file_bytes, mime_type):
return {
"fields": {"total_packages": 42},
"text": "azure text",
"confidence": 0.88,
}
monkeypatch.setattr(service, "_render_page_images", lambda file_bytes, suffix: [b"fake-image"])
monkeypatch.setattr(service, "_run_paddle", fake_paddle)
monkeypatch.setattr(service, "_run_azure", fake_azure)
monkeypatch.setattr(service, "_estimate_quality", lambda images: 0.95)
monkeypatch.setattr(settings, "ENABLE_DUAL_OCR", True)
result = await service.prepare_document(
doc_id="doc-123",
storage_path="documents/doc-123.png",
filename="doc-123.png",
file_bytes=b"fake-image-bytes",
)
assert "paddleocr" in result["ocr_candidates"]
assert "azure-di" in result["ocr_candidates"]
assert "paddle text" in result["raw_text"]
assert "azure text" in result["raw_text"]
assert result["quality_score"] == 0.95
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