feat(server): add OCR invoice processing functionality
New endpoints: - server/src/app/api/v1/endpoints/ocr.py: OCR API endpoints for invoice scanning New schemas: - server/src/app/schemas/ocr.py: OCR request/response data schemas New services: - server/src/app/services/ocr.py: OCR processing business logic - server/src/app/services/expense_claims.py: expense claims management service Scripts: - server/scripts/bootstrap_paddleocr_mobile.sh: PaddleOCR mobile setup script - server/scripts/paddle_ocr_worker.py: PaddleOCR worker process
This commit is contained in:
caoxiaozhu
221
server/src/app/services/ocr.py
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221
server/src/app/services/ocr.py
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from __future__ import annotations
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import json
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import shutil
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import subprocess
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from pathlib import Path
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from uuid import uuid4
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from app.core.config import SERVER_DIR, get_settings
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from app.schemas.ocr import OcrRecognizeBatchRead, OcrRecognizeDocumentRead, OcrRecognizeLineRead
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WORKER_JSON_PREFIX = "__OCR_JSON__="
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SUPPORTED_SUFFIXES = {".png", ".jpg", ".jpeg", ".webp", ".bmp", ".pdf"}
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class OcrService:
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def __init__(self) -> None:
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self.settings = get_settings()
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def recognize_files(
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self,
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files: list[tuple[str, bytes, str | None]],
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) -> OcrRecognizeBatchRead:
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if not files:
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raise ValueError("至少需要上传一个文件。")
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temp_root = self.settings.resolved_ocr_temp_dir
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temp_root.mkdir(parents=True, exist_ok=True)
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documents: list[OcrRecognizeDocumentRead] = []
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input_paths: list[Path] = []
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meta_by_path: dict[str, tuple[str, str]] = {}
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python_bin = self._resolve_python_bin()
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worker_path = self._resolve_worker_path()
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try:
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for filename, content, media_type in files:
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normalized_name = Path(str(filename or "").strip()).name or "upload.bin"
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suffix = Path(normalized_name).suffix.lower()
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resolved_media_type = str(media_type or "application/octet-stream")
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if not content:
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documents.append(
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OcrRecognizeDocumentRead(
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filename=normalized_name,
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media_type=resolved_media_type,
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warnings=["文件内容为空，未执行 OCR。"],
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)
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)
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continue
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if suffix not in SUPPORTED_SUFFIXES:
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documents.append(
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OcrRecognizeDocumentRead(
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filename=normalized_name,
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media_type=resolved_media_type,
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warnings=["当前仅支持图片和 PDF 文件进行 OCR。"],
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)
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)
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continue
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if len(content) > self.settings.ocr_max_file_size_mb * 1024 * 1024:
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documents.append(
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OcrRecognizeDocumentRead(
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filename=normalized_name,
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media_type=resolved_media_type,
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warnings=[
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f"文件超过 {self.settings.ocr_max_file_size_mb} MB，未执行 OCR。"
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],
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)
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)
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continue
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temp_path = temp_root / f"{uuid4().hex}{suffix}"
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temp_path.write_bytes(content)
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input_paths.append(temp_path)
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meta_by_path[str(temp_path)] = (normalized_name, resolved_media_type)
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if input_paths:
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worker_payload = self._invoke_worker(
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python_bin=python_bin,
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worker_path=worker_path,
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input_paths=input_paths,
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)
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for item in worker_payload.get("documents", []):
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documents.append(self._build_document(item, meta_by_path))
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success_count = sum(
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1
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for item in documents
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if item.line_count > 0 or not item.warnings
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)
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engine = (
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str(worker_payload.get("engine", "paddleocr_mobile"))
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if input_paths
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else "paddleocr_mobile"
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)
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model = (
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str(worker_payload.get("model", "PP-OCRv5_mobile"))
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if input_paths
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else "PP-OCRv5_mobile"
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)
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return OcrRecognizeBatchRead(
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engine=engine,
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model=model,
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total_file_count=len(files),
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success_count=success_count,
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documents=documents,
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)
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finally:
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for path in input_paths:
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path.unlink(missing_ok=True)
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def _resolve_python_bin(self) -> str:
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candidates = []
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configured = str(self.settings.ocr_python_bin or "").strip()
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if configured:
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candidates.append(configured)
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candidates.append(str(SERVER_DIR / ".venv-ocr312" / "bin" / "python"))
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candidates.append("/usr/local/bin/python3.12")
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resolved = shutil.which("python3.12")
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if resolved:
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candidates.append(resolved)
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for candidate in candidates:
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if candidate and Path(candidate).exists():
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return candidate
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raise RuntimeError(
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"未找到可用的 OCR Python 运行时。请先执行 scripts/bootstrap_paddleocr_mobile.sh "
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"或通过 OCR_PYTHON_BIN 指向已安装 PaddleOCR 的 Python 3.12。"
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)
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@staticmethod
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def _resolve_worker_path() -> str:
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worker_path = SERVER_DIR / "scripts" / "paddle_ocr_worker.py"
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if not worker_path.exists():
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raise RuntimeError(f"OCR worker 不存在：{worker_path}")
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return str(worker_path)
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def _invoke_worker(
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self,
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*,
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python_bin: str,
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worker_path: str,
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input_paths: list[Path],
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) -> dict:
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command = [
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python_bin,
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worker_path,
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"--lang",
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self.settings.ocr_language,
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"--text-detection-model",
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self.settings.ocr_text_detection_model,
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"--text-recognition-model",
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self.settings.ocr_text_recognition_model,
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]
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for path in input_paths:
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command.extend(["--input", str(path)])
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completed = subprocess.run(
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command,
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capture_output=True,
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text=True,
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timeout=self.settings.ocr_timeout_seconds,
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check=False,
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)
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if completed.returncode != 0:
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detail = (completed.stderr or completed.stdout or "").strip()
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raise RuntimeError(f"OCR 执行失败：{detail or 'worker 返回非 0 状态码。'}")
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payload = self._parse_worker_stdout(completed.stdout)
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if payload is None:
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raise RuntimeError("OCR worker 未返回可解析的 JSON 结果。")
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return payload
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@staticmethod
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def _parse_worker_stdout(stdout: str) -> dict | None:
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for line in reversed(stdout.splitlines()):
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normalized = line.strip()
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if normalized.startswith(WORKER_JSON_PREFIX):
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return json.loads(normalized[len(WORKER_JSON_PREFIX) :])
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return None
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@staticmethod
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def _build_document(
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payload: dict,
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meta_by_path: dict[str, tuple[str, str]],
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) -> OcrRecognizeDocumentRead:
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input_path = str(payload.get("input_path") or "")
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filename, media_type = meta_by_path.get(
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input_path,
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(Path(input_path).name or "upload.bin", "application/octet-stream"),
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)
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lines = [
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OcrRecognizeLineRead(
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text=str(item.get("text", "")),
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score=float(item.get("score", 0.0) or 0.0),
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box=[
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[int(point[0]), int(point[1])]
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for point in item.get("box", [])
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if isinstance(point, list) and len(point) == 2
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],
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page_index=int(item["page_index"]) if item.get("page_index") is not None else None,
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)
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for item in payload.get("lines", [])
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if isinstance(item, dict)
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]
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return OcrRecognizeDocumentRead(
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filename=filename,
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media_type=media_type,
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engine=str(payload.get("engine", "paddleocr_mobile")),
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model=str(payload.get("model", "PP-OCRv5_mobile")),
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text=str(payload.get("text", "")),
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summary=str(payload.get("summary", "")),
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avg_score=float(payload.get("avg_score", 0.0) or 0.0),
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line_count=int(payload.get("line_count", len(lines)) or 0),
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page_count=int(payload.get("page_count", 1) or 1),
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warnings=[str(item) for item in payload.get("warnings", [])],
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lines=lines,
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)
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