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feat(server): 新增文档智能识别服务，扩展OCR接口支持 Azure Document Intelligence

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caoxiaozhu
2026-05-14 09:32:15 +00:00
parent 8adeefe4a9
commit 8b39f48dec
7 changed files with 1128 additions and 61 deletions
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66
server/tests/test_document_intelligence.py Normal file
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@@ -0,0 +1,66 @@
from __future__ import annotations
import json
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.pool import StaticPool
from app.services.document_intelligence import DocumentIntelligenceService, build_document_insight
from app.services.runtime_chat import RuntimeChatService
def test_build_document_insight_prefers_transport_for_didi_text_with_hotel_noise() -> None:
insight = build_document_insight(
filename="didi-trip.png",
summary="滴滴出行行程单",
text="滴滴出行电子发票 订单号 12345678 上车点 深圳湾 下车点 后海 全季酒店 里程 12.4 公里 金额 48 元",
)
assert insight.document_type == "taxi_receipt"
assert insight.document_type_label == "出租车/网约车票据"
assert insight.scene_code == "transport"
assert any(field.label == "金额" and field.value == "48元" for field in insight.fields)
def test_document_intelligence_service_uses_vlm_result_when_preview_available(monkeypatch) -> None:
calls: list[tuple[str, ...]] = []
def fake_complete(self, messages, *, slot_priority=("main", "backup"), max_tokens=500, temperature=0.2):
calls.append(slot_priority)
if slot_priority == ("vlm",):
assert isinstance(messages[1]["content"], list)
return json.dumps(
{
"document_type": "taxi_receipt",
"scene_code": "transport",
"scene_label": "交通票据",
"expense_type": "transport",
"confidence": 0.91,
"evidence": ["图片主体为滴滴行程单，OCR 中出现订单号、上车、下车等字段"],
},
ensure_ascii=False,
)
return None
monkeypatch.setattr(RuntimeChatService, "complete", fake_complete)
engine = create_engine(
"sqlite+pysqlite:///:memory:",
connect_args={"check_same_thread": False},
poolclass=StaticPool,
)
session = sessionmaker(bind=engine, autoflush=False, autocommit=False)()
try:
insight = DocumentIntelligenceService(session).build_document_insight(
filename="mixed-noise.png",
summary="OCR 混入酒店名称",
text="全季酒店 滴滴出行 订单号 12345678 上车 下车 金额 52 元",
preview_data_url="data:image/png;base64,ZmFrZQ==",
)
finally:
session.close()
assert insight.document_type == "taxi_receipt"
assert insight.classification_source == "llm_vision"
assert calls[0] == ("vlm",)

22
server/tests/test_ocr_endpoints.py
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@@ -10,7 +10,7 @@ from sqlalchemy.pool import StaticPool
from app.api.deps import get_db
from app.db.base import Base
from app.main import create_app
from app.schemas.ocr import OcrRecognizeBatchRead, OcrRecognizeDocumentRead, OcrRecognizeLineRead
from app.schemas.ocr import OcrRecognizeBatchRead, OcrRecognizeDocumentRead, OcrRecognizeFieldRead, OcrRecognizeLineRead
from app.services.ocr import OcrService
@@ -50,14 +50,23 @@ def test_ocr_recognize_endpoint_returns_structured_payload(monkeypatch) -> None:
OcrRecognizeDocumentRead(
filename="invoice.png",
media_type="image/png",
text="发票金额 100 元",
summary="发票金额 100 元",
text="增值税电子发票 发票号码12345678 金额 100 元 2026-05-13",
summary="增值税电子发票，金额 100 元。",
avg_score=0.98,
line_count=1,
page_count=1,
document_type="vat_invoice",
document_type_label="增值税发票",
scene_code="other",
scene_label="通用发票",
document_fields=[
OcrRecognizeFieldRead(key="amount", label="金额", value="100元"),
OcrRecognizeFieldRead(key="date", label="日期", value="2026-05-13"),
OcrRecognizeFieldRead(key="invoice_number", label="票据号码", value="12345678"),
],
lines=[
OcrRecognizeLineRead(
text="发票金额 100 元",
text="增值税电子发票 发票号码12345678 金额 100 元 2026-05-13",
score=0.98,
box=[[1, 2], [10, 2], [10, 8], [1, 8]],
page_index=0,
@@ -81,4 +90,7 @@ def test_ocr_recognize_endpoint_returns_structured_payload(monkeypatch) -> None:
assert payload["engine"] == "paddleocr_mobile"
assert payload["success_count"] == 1
assert payload["documents"][0]["filename"] == "invoice.png"
assert payload["documents"][0]["summary"] == "发票金额 100 元"
assert payload["documents"][0]["summary"] == "增值税电子发票，金额 100 元。"
assert payload["documents"][0]["document_type"] == "vat_invoice"
assert payload["documents"][0]["document_type_label"] == "增值税发票"
assert payload["documents"][0]["document_fields"][0]["label"] == "金额"

106
server/tests/test_ocr_service.py
View File

@@ -26,15 +26,15 @@ for index, arg in enumerate(sys.argv):
"input_path": input_path,
"engine": "paddleocr_mobile",
"model": "PP-OCRv5_mobile",
"text": "发票金额 100 元",
"summary": "发票金额 100 元",
"text": "增值税电子发票 发票号码12345678 金额 100 元 2026-05-13",
"summary": "增值税电子发票，金额 100 元。",
"avg_score": 0.98,
"line_count": 1,
"page_count": 1,
"warnings": [],
"lines": [
{
"text": "发票金额 100 元",
"text": "增值税电子发票 发票号码12345678 金额 100 元 2026-05-13",
"score": 0.98,
"box": [[1, 2], [10, 2], [10, 8], [1, 8]],
"page_index": 0,
@@ -74,10 +74,106 @@ print("__OCR_JSON__=" + json.dumps(payload, ensure_ascii=False))
assert len(result.documents) == 2
recognized = next(item for item in result.documents if item.filename == "invoice.png")
assert recognized.summary == "发票金额 100 元"
assert recognized.summary == "增值税电子发票，金额 100 元。"
assert recognized.line_count == 1
assert recognized.lines[0].text == "发票金额 100 元"
assert recognized.document_type == "vat_invoice"
assert recognized.document_type_label == "增值税发票"
assert any(field.label == "金额" and field.value == "100元" for field in recognized.document_fields)
assert any(field.label == "票据号码" and field.value == "12345678" for field in recognized.document_fields)
assert any(field.label == "日期" and field.value == "2026-05-13" for field in recognized.document_fields)
assert recognized.lines[0].text == "增值税电子发票 发票号码12345678 金额 100 元 2026-05-13"
skipped = next(item for item in result.documents if item.filename == "notes.txt")
assert skipped.line_count == 0
assert skipped.warnings == ["当前仅支持图片和 PDF 文件进行 OCR。"]
def test_ocr_service_converts_pdf_to_images_and_returns_image_preview(
monkeypatch,
tmp_path: Path,
) -> None:
def fake_convert_pdf_to_images(self, *, pdf_path: Path, output_dir: Path) -> list[Path]:
first = output_dir / "page-1.png"
second = output_dir / "page-2.png"
first.write_bytes(b"fake-page-1")
second.write_bytes(b"fake-page-2")
return [first, second]
def fake_invoke_worker(
self,
*,
python_bin: str,
worker_path: str,
input_paths: list[Path],
) -> dict:
assert [path.name for path in input_paths] == ["page-1.png", "page-2.png"]
return {
"engine": "paddleocr_mobile",
"model": "PP-OCRv5_mobile",
"documents": [
{
"input_path": str(input_paths[0]),
"engine": "paddleocr_mobile",
"model": "PP-OCRv5_mobile",
"text": "高铁票 深圳北-广州南 车次 G1234 2026-05-13 金额 188 元",
"summary": "高铁票第一页",
"avg_score": 0.97,
"line_count": 1,
"page_count": 1,
"warnings": [],
"lines": [
{
"text": "高铁票 深圳北-广州南 车次 G1234 2026-05-13 金额 188 元",
"score": 0.97,
"box": [[1, 2], [10, 2], [10, 8], [1, 8]],
}
],
},
{
"input_path": str(input_paths[1]),
"engine": "paddleocr_mobile",
"model": "PP-OCRv5_mobile",
"text": "乘车人 张三",
"summary": "高铁票第二页",
"avg_score": 0.94,
"line_count": 1,
"page_count": 1,
"warnings": [],
"lines": [
{
"text": "乘车人 张三",
"score": 0.94,
"box": [[1, 2], [10, 2], [10, 8], [1, 8]],
}
],
},
],
}
monkeypatch.setenv("STORAGE_ROOT_DIR", str(tmp_path / "storage"))
monkeypatch.setattr(OcrService, "_resolve_python_bin", lambda self: "python")
monkeypatch.setattr(OcrService, "_resolve_worker_path", lambda self: "worker.py")
monkeypatch.setattr(OcrService, "_convert_pdf_to_images", fake_convert_pdf_to_images)
monkeypatch.setattr(OcrService, "_invoke_worker", fake_invoke_worker)
get_settings.cache_clear()
try:
result = OcrService().recognize_files(
[
("train-ticket.pdf", b"%PDF-1.4 fake", "application/pdf"),
]
)
finally:
get_settings.cache_clear()
assert result.success_count == 1
assert len(result.documents) == 1
recognized = result.documents[0]
assert recognized.filename == "train-ticket.pdf"
assert recognized.page_count == 2
assert recognized.preview_kind == "image"
assert recognized.preview_data_url.startswith("data:image/png;base64,")
assert recognized.document_type == "train_ticket"
assert any(field.label == "金额" and field.value == "188元" for field in recognized.document_fields)
assert any(field.label == "车次/航班" and field.value == "G1234" for field in recognized.document_fields)
assert recognized.lines[0].page_index == 0
assert recognized.lines[1].page_index == 1