fix: improve Chinese NLP filetype detection accuracy

[Johnson-zs]

1. Added new test case for design source files shadowing image
   substrings
2. Included "包" back to application filetype rules with negative
   lookahead to prevent false matches
3. Increased priority of design source files to shadow image matches
4. Removed outdated comment about span consumption since it's now
   standard behavior

Influence:

1. Test Chinese file search with "矢量图" to ensure design source files
   are prioritized over general image files
2. Verify "包" matches application filetype while avoiding false
   positives like "表情包"
3. Check that design source files (PSD, AI etc.) are correctly
   identified in complex queries

fix: 提升中文NLP文件类型检测准确性

1. 新增设计源文件遮蔽图片子字符串的测试用例
2. 重新包含"包"到应用文件类型规则，添加否定前瞻避免误判
3. 提高设计源文件的优先级使其遮蔽图片匹配
4. 移除关于span消费的过时注释，因这已是标准行为

Influence:

1. 测试中文文件搜索"矢量图"确保设计源文件优先于普通图片文件
2. 验证"包"能匹配应用文件类型同时避免"表情包"等误判
3. 检查在复杂查询中设计源文件(PSD, AI等)能被正确识别

Fixes: #370659

Summary by Sourcery

Improve Chinese NLP filetype detection accuracy for design source and application files.

New Features:

• Add a Chinese NLP test ensuring design source filetype matches shadow general image substring matches.

Bug Fixes:

• Restore the "包" synonym to Chinese application filetype detection while avoiding false positives such as "表情包".
• Ensure design source filetype rules take precedence over image rules in Chinese queries to prevent misclassification.

Enhancements:

• Simplify span handling in filetype extraction by removing an outdated comment about span consumption behavior.

Tests:

• Extend Chinese NLP filetype tests to cover design source precedence over image substrings and updated application synonyms.

[deepin-ci-robot]

[APPROVALNOTIFIER] This PR is NOT APPROVED

This pull-request has been approved by: Johnson-zs

The full list of commands accepted by this bot can be found here.

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[sourcery-ai]

Reviewer's Guide

This PR refines Chinese NLP filetype detection by reintroducing the “包” synonym for applications with stricter matching, adding a regression test to ensure design-source file rules override generic image matches, and cleaning up an outdated span-consumption comment in the extractor implementation, along with corresponding rule updates in the Chinese filetype rules JSON.

File-Level Changes

Change	Details	Files
Improve application filetype synonym handling to safely re-include “包”.	Extend the application filetype synonym test inputs to include the standalone term “包”. Align tests with updated application filetype rules that now match “包” while avoiding false positives like “表情包” via regex rule changes in the zh_CN filetype JSON.	autotests/dfm-search-tests/tst_chinese_nlp.cpp src/dfm-search/dfm-search-lib/semantic/rules/zh_CN/filetype_rules.json
Ensure design-source filetype rules shadow generic image matches for Chinese queries like “矢量图”.	Add a dedicated test that parses “昨天创建的矢量图” and asserts that only the design-source filetype rule is triggered and that the image filetype rule is not. Verify in the new test that the resulting file extensions match the expected design-source rule set via expectedExtsForRule. Raise the effective priority of design-source rules over image rules in the zh_CN filetype rules JSON so overlapping substrings prefer design-source matches.	autotests/dfm-search-tests/tst_chinese_nlp.cpp src/dfm-search/dfm-search-lib/semantic/rules/zh_CN/filetype_rules.json
Clean up extractor implementation comments to reflect current span consumption behavior.	Remove an outdated inline comment about always consuming matched spans, since this behavior is now standard and enforced elsewhere. Keep the MatchSpan construction and consumption logic unchanged to maintain current behavior while simplifying the code’s documentation.	src/dfm-search/dfm-search-lib/semantic/extractors/filetypeextractor.cpp

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[sourcery-ai]

Hey - I've left some high level feedback:

• In fileType_designSource_shadowsImageSubstring, consider also asserting that the resulting fileExtensions() does not include the image rule’s extensions so the shadowing behavior is verified at both span and extension levels.
• The test currently relies on hard-coded ruleId string literals like "filetype_design_source" and "filetype_image"; using shared constants or an enum for rule IDs would make the tests less brittle to future rule renames.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- In `fileType_designSource_shadowsImageSubstring`, consider also asserting that the resulting `fileExtensions()` does not include the image rule’s extensions so the shadowing behavior is verified at both span and extension levels.
- The test currently relies on hard-coded `ruleId` string literals like `"filetype_design_source"` and `"filetype_image"`; using shared constants or an enum for rule IDs would make the tests less brittle to future rule renames.

---

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[deepin-ci-robot]

deepin pr auto review

★ 总体评分：100分

■ 【总体评价】

代码通过正则优化和优先级调整有效解决了NLP语义解析的误匹配和类型冲突问题，并补充了完善的测试用例
逻辑正确且无安全漏洞，代码质量良好，修复方案精准有效

■ 【详细分析】

• 1.语法逻辑（完全正确）✓

在 filetype_rules.json 中，filetype_application 的正则表达式修改为 包(?!含)，正确使用了负向先行断言避免匹配"包含"；filetype_design_source 的优先级提升至 160，确保高于图片规则，解决了"矢量图"的冲突。测试代码 fileType_designSource_shadowsImageSubstring 逻辑严密，正确验证了修复效果。
潜在问题：无
建议：无需修改

• 2.代码质量（良好）✓

新增的测试用例覆盖了之前存在的边界条件，移除了不再适用的注释，代码可读性高。正则表达式的修改直接针对问题，且易于理解。
潜在问题：无
建议：可以考虑在 filetype_rules.json 中为 包(?!含) 添加简短注释说明为何排除"包含"，以便后续维护

• 3.代码性能（无性能问题）✓

正则表达式的负向先行断言开销极小，优先级数值的调整对匹配算法的复杂度没有负面影响。
潜在问题：无
建议：无需修改

• 4.代码安全（存在0个安全漏洞）✓

漏洞对比统计：新增漏洞 0 个，减少漏洞 0 个，持平 0 个
本次修改仅涉及正则表达式规则调整和测试代码增加，不存在外部输入注入或内存操作风险，攻击面无变化。

• 建议：无需安全修复

■ 【改进建议代码示例】

{
    "id": "filetype_application",
    "pattern": "安装包|软件|应用|脚本|程序|包(?!含)",
    "description": "Application packages",
    "enabled": true,
    "priority": 150,
    "metadata": {
        "extensions": ["deb", "rpm", "sh", "appimage", "uap"]
    }
}

[Johnson-zs]

/forcemerge

[deepin-bot]

This pr force merged! (status: blocked)