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from typing import List, Dict, Optional |
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from pydantic import BaseModel, Field |
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class SourceDocument(BaseModel): |
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"""Represents a source document used in splicing.""" |
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doc_type: str = Field(..., description="Document category/type") |
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doc_name: str = Field(..., description="Source document identifier") |
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pages: List[int] = Field(..., description="Page numbers used from this document") |
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class GroundTruthPage(BaseModel): |
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"""Ground truth for a single page in spliced document.""" |
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page_num: int = Field(..., ge=1, description="Page number in spliced document") |
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doc_type: str = Field(..., description="Document category/type") |
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source_doc: str = Field(..., description="Source document identifier") |
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source_page: int = Field(..., ge=1, description="Page number in source document") |
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class SplicedDocument(BaseModel): |
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"""Represents a spliced benchmark document.""" |
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spliced_doc_id: str = Field(..., description="Unique identifier for spliced document") |
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source_documents: List[SourceDocument] = Field(..., description="Source documents used") |
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ground_truth: List[GroundTruthPage] = Field(..., description="Ground truth page mappings") |
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total_pages: int = Field(..., gt=0, description="Total pages in spliced document") |
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class BenchmarkSet(BaseModel): |
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"""Collection of spliced documents for a benchmark.""" |
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benchmark_name: str = Field(..., description="Benchmark identifier") |
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strategy: str = Field(..., description="Shuffling strategy used") |
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split: str = Field(..., description="Dataset split: train, test, or validation") |
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created_at: str = Field(..., description="Creation timestamp") |
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documents: List[SplicedDocument] = Field(..., description="Spliced documents") |
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statistics: Dict[str, int] = Field(default_factory=dict, description="Benchmark statistics") |
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class DocumentAsset(BaseModel): |
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"""Represents a loaded document asset.""" |
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doc_type: str = Field(..., description="Document category/type") |
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doc_name: str = Field(..., description="Document identifier") |
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filename: str = Field(..., description="PDF filename") |
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page_count: int = Field(..., gt=0, description="Number of pages") |
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pages: List['PageAsset'] = Field(default_factory=list, description="Page assets") |
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class PageAsset(BaseModel): |
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"""Represents a single page asset.""" |
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page_num: int = Field(..., ge=1, description="Page number") |
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image_path: str = Field(..., description="Path to page image") |
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text_path: str = Field(..., description="Path to OCR text") |
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text_content: Optional[str] = Field(None, description="Loaded text content") |
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