- docling 转换器通过 PdfPipelineOptions 显式设置 do_ocr=False, 混合 PDF 的图片页不再产出 OCR 文字;不提供重新开启 OCR 的参数。 - 无文本层 PDF 的错误文案改为"扫描版或图片型 PDF 不支持", 上传阶段整批拒绝,保留混合 PDF 的可处理判定。 - 新增 test_layout_converter_disables_ocr 守护开关状态, 同步设计文档与 disable-ocr 实施计划/设计说明。
132 lines
4.6 KiB
Python
132 lines
4.6 KiB
Python
from __future__ import annotations
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import sys
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from types import ModuleType, SimpleNamespace
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from llama_index.core.embeddings import MockEmbedding
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from app.modules.data_process.document_chunking import (
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DocumentChunk,
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_compact_with_offsets,
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_document_converter,
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_project_layout_span,
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chunk_fixed_text,
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chunk_semantic_text,
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merge_short_chunks,
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)
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def test_fixed_splitter_preserves_offsets_and_token_limit() -> None:
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text = "第一段说明苹果。第二段说明香蕉。\n第三段说明数据库。第四段说明索引。"
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chunks = chunk_fixed_text(text, chunk_size=20, chunk_overlap=0)
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assert len(chunks) > 1
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assert all(chunk.source_start is not None for chunk in chunks)
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assert all(chunk.source_end is not None for chunk in chunks)
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assert all(
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chunk.original_content == text[chunk.source_start : chunk.source_end]
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for chunk in chunks
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if chunk.source_start is not None and chunk.source_end is not None
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)
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assert all(chunk.token_count <= 20 for chunk in chunks)
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def test_semantic_splitter_uses_llamaindex_and_reapplies_maximum_size() -> None:
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text = "第一段讨论水果。第二段继续讨论香蕉。第三段讨论数据库。第四段讨论索引。"
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chunks = chunk_semantic_text(
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text,
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chunk_size=30,
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chunk_overlap=0,
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breakpoint_percentile_threshold=95,
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embed_model=MockEmbedding(embed_dim=8),
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)
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assert len(chunks) >= 2
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assert all(chunk.token_count <= 30 for chunk in chunks)
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assert "".join(chunk.original_content for chunk in chunks) == text
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def test_layout_converter_disables_ocr(monkeypatch) -> None:
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class FakePipelineOptions:
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def __init__(self) -> None:
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self.do_ocr = True
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class FakePdfFormatOption:
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def __init__(self, *, pipeline_options) -> None:
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self.pipeline_options = pipeline_options
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class FakeDocumentConverter:
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def __init__(self, *, format_options) -> None:
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self.format_options = format_options
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docling_module = ModuleType("docling")
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docling_module.__path__ = []
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document_converter_module = ModuleType("docling.document_converter")
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document_converter_module.DocumentConverter = FakeDocumentConverter
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document_converter_module.PdfFormatOption = FakePdfFormatOption
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datamodel_module = ModuleType("docling.datamodel")
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datamodel_module.__path__ = []
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base_models_module = ModuleType("docling.datamodel.base_models")
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base_models_module.InputFormat = SimpleNamespace(PDF="pdf")
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pipeline_options_module = ModuleType("docling.datamodel.pipeline_options")
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pipeline_options_module.PdfPipelineOptions = FakePipelineOptions
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for name, module in {
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"docling": docling_module,
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"docling.document_converter": document_converter_module,
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"docling.datamodel": datamodel_module,
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"docling.datamodel.base_models": base_models_module,
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"docling.datamodel.pipeline_options": pipeline_options_module,
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}.items():
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monkeypatch.setitem(sys.modules, name, module)
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_document_converter.cache_clear()
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try:
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converter = _document_converter()
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options = converter.format_options["pdf"].pipeline_options
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assert options.do_ocr is False
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finally:
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_document_converter.cache_clear()
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def test_layout_projection_ignores_layout_whitespace_but_keeps_source_lines() -> None:
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source = "标题\n第一条 这是正文。\n第二条 后续正文。"
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compact_source, offsets = _compact_with_offsets(source)
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start, end, cursor = _project_layout_span(
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source,
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"第一条\n这是正文。",
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compact_source=compact_source,
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source_offsets=offsets,
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compact_start=0,
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)
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assert source[start:end] == "第一条 这是正文。"
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assert cursor > 0
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def test_short_layout_chunk_merges_with_neighbor_and_keeps_page_provenance() -> None:
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source = "短标题\n这是一段足够长的正文内容,用于测试相邻切片合并。"
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chunks = [
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DocumentChunk("短标题", "短标题", 0, 3, 1, 1, 2, source_pages=(1,)),
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DocumentChunk(
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"这是一段足够长的正文内容,用于测试相邻切片合并。",
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"这是一段足够长的正文内容,用于测试相邻切片合并。",
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4,
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len(source),
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2,
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2,
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20,
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source_pages=(1, 2),
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),
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]
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merged = merge_short_chunks(
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chunks,
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source_text=source,
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min_token_count=10,
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max_token_count=100,
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)
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assert len(merged) == 1
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assert merged[0].original_content == source
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assert merged[0].source_pages == (1, 2)
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