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## What problem does this PR solve?
DOCX parsing could crash when a paragraph used a `Heading`-prefixed
style without a trailing numeric level, such as `Heading`, `Heading1`,
or `Heading Title`.
`docx_question_level()` assumed every heading style looked like `Heading
N` and called `int(p.style.name.split(" ")[-1])`. For non-numbered
heading styles, that raises `ValueError` and breaks Manual, Q&A, and
Laws chunking.
This PR parses heading levels safely and falls back to level 1 for
Heading-prefixed styles without an explicit numeric suffix.
Closes #16163.
## Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Test Case (non-breaking change which adds test coverage)
91 lines
3.0 KiB
Python
91 lines
3.0 KiB
Python
#
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# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import importlib
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import sys
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import types
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import pytest
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def _stub(monkeypatch, name, **attrs):
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mod = types.ModuleType(name)
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for key, value in attrs.items():
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setattr(mod, key, value)
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monkeypatch.setitem(sys.modules, name, mod)
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return mod
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@pytest.fixture()
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def docx_question_level(monkeypatch):
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_stub(monkeypatch, "common.token_utils", num_tokens_from_string=lambda *a, **k: 0)
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_stub(monkeypatch, "roman_numbers")
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_stub(monkeypatch, "word2number", w2n=types.SimpleNamespace())
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_stub(monkeypatch, "cn2an", cn2an=lambda *a, **k: 0)
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pil = _stub(monkeypatch, "PIL")
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pil.Image = _stub(monkeypatch, "PIL.Image")
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_stub(monkeypatch, "chardet")
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monkeypatch.delitem(sys.modules, "rag.nlp", raising=False)
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return importlib.import_module("rag.nlp").docx_question_level
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class _Style:
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def __init__(self, name):
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self.name = name
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class _Paragraph:
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def __init__(self, style_name, text="Some title"):
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self.style = _Style(style_name)
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self.text = text
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@pytest.mark.p2
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@pytest.mark.parametrize(
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"style_name, expected_level",
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[
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("Heading 1", 1),
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("Heading 2", 2),
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("Heading 9", 9),
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("Heading 10", 10),
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("Heading1", 1), # no space
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("Heading", 1), # base style, no number -> top level
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("HeadingTitle", 1), # custom prefix, no number -> top level
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("Heading Title", 1), # custom prefix with space, no number -> top level
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],
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)
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def test_docx_question_level_heading_styles(docx_question_level, style_name, expected_level):
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level, text = docx_question_level(_Paragraph(style_name))
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assert level == expected_level
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assert text == "Some title"
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@pytest.mark.p2
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def test_docx_question_level_no_number_does_not_raise(docx_question_level):
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# Regression for #16163: a "Heading"-prefixed style without a parseable
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# number used to raise ValueError: invalid literal for int().
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for name in ("Heading", "HeadingTitle", "Heading Title"):
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level, _ = docx_question_level(_Paragraph(name))
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assert level == 1
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@pytest.mark.p2
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def test_docx_question_level_non_heading_default_bull(docx_question_level):
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# Non-heading paragraph with the default bull=-1 returns level 0 (body text).
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level, text = docx_question_level(_Paragraph("Normal", text="just a body line"))
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assert level == 0
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assert text == "just a body line"
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