OCR MCP Service

"""Data models for OCR results.""" from typing import List, Optional, Dict, Any from dataclasses import dataclass, field @dataclass class BoundingBox: """Bounding box for text detection.""" x1: float y1: float x2: float y2: float @dataclass class OCRResult: """OCR recognition result.""" text: str boxes: List[BoundingBox] confidence: float engine: str processing_time: float analysis: Optional[str] = None progress_history: List[Dict[str, Any]] = field(default_factory=list) prompt_suggestion: Optional[Dict[str, Any]] = None def to_dict(self) -> dict: """Convert to dictionary.""" result = { "text": self.text, "boxes": [ {"x1": b.x1, "y1": b.y1, "x2": b.x2, "y2": b.y2} for b in self.boxes ], "confidence": self.confidence, "engine": self.engine, "processing_time": self.processing_time, } if self.analysis: result["analysis"] = self.analysis if self.progress_history: result["progress_history"] = self.progress_history if self.prompt_suggestion: result["prompt_suggestion"] = self.prompt_suggestion return result def get_text_with_analysis(self) -> str: """Get text with analysis appended.""" parts = [self.text] if self.analysis: parts.append(f"\n\n--- 技术解析 ---\n\n{self.analysis}") return "\n".join(parts)