init: WordFileParse docx→HTML 解析服务（含 Word EQ 域公式修复）
服务：Spring Boot 3.2 + docx4j 8.3.9，POST /api/v3/server_office_file/file/parse
接受 .docx，返回 HTML（公式 → LaTeX，图片 → RustFS 外链）
公式支持三类来源：
- OMML（Word 2007+ 公式） → Python omml_mathml2latex
- MathType OLE 对象 → Ruby mathtype2mathml → MathML → LaTeX
- Word EQ 域（老教辅主力） → EqToLatexUtil（本次新增）
本次改动：
1. 新增 java-svc/.../core/EqToLatexUtil.java：
移植自 jby backend-services office-core，EQ 语法 → LaTeX
（\f→\dfrac、\r→\sqrt、\i→\int/\sum/\prod、\s→^{}/_{}、\b→\left\right、
\a→array、\x→\boxed/\overline、\o\al 堆叠、圈码、化学符号、极限、连等式）
品牌标记 JBYU* → WPU*，与采集端一致
2. CtoMathFinder：接上 EQ 分支（原为 not-ported 桩），域代码经
EqToLatexUtil.convert 转 LaTeX 写入 eqLatexMap（WPEQNUM 占位符）
3. WordParseUtil.dealPlaceholder：EQ 的 LaTeX 同样加 \( \) 包裹
（原先因 WPEQNUM 例外不加包裹，前端/MathJax 不渲染）
修前症状：教辅 Word 里分式/方程组/上下标整段丢失（如 {−1/3, 1} 变成 {－，1}）
修后实测：46 份教辅 2908 处 EQ 域全部还原，公式总数 2954 处、零未包裹残留
安全：application.yml（含 RustFS 密钥）不入库，提供 application.yml.example；
OssService 的 @Value 默认密钥已清空
This commit is contained in:
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scripts/omml_mathml2latex/utils/chemistry.py
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296
scripts/omml_mathml2latex/utils/chemistry.py
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"""
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Chemistry detection utilities for identifying chemical equations and contexts.
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This module provides functions to detect chemical reactions, conditions, and
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other chemistry-specific patterns in mathematical equations.
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"""
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from typing import Optional, Dict
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from lxml import etree as ET
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# OMML namespace constant
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OMML_NS = "http://schemas.openxmlformats.org/officeDocument/2006/math"
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def contains_chinese_characters(text: str) -> bool:
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"""Check if text contains Chinese characters.
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Args:
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text: Text to check
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Returns:
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True if text contains at least one Chinese character
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Example:
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>>> contains_chinese_characters('加热')
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True
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>>> contains_chinese_characters('heat')
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False
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"""
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if not text:
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return False
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for char in text:
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if '\u4e00' <= char <= '\u9fff': # Chinese character range
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return True
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return False
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def is_typical_reaction_condition_text(text: str) -> bool:
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"""Check if text looks like a typical chemical reaction condition.
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Args:
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text: Text to check
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Returns:
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True if text contains typical chemical reaction condition terms
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Example:
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>>> is_typical_reaction_condition_text('加热')
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True
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>>> is_typical_reaction_condition_text('heat')
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True
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>>> is_typical_reaction_condition_text('abc')
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False
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"""
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if not text:
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return False
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# Common chemical reaction conditions
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typical_conditions = {
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# Chinese conditions
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"电解", "加热", "催化剂", "高温", "高压", "光照", "加压", "蒸馏", "熔融", "溶解", "酸化", "碱化",
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"氧化", "还原", "分解", "合成", "中和", "干燥", "过滤", "沉淀", "结晶", "升华", "煅烧",
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# English conditions
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"heat", "catalyst", "pressure", "light", "oxidation", "reduction", "electrolysis",
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"distillation", "crystallization", "precipitation", "filtration", "drying",
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# Symbols and abbreviations
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"Δ", "hv", "H+", "OH-", "cat", "pt", "ni", "pd"
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}
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text_lower = text.lower().strip()
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return any(condition.lower() in text_lower for condition in typical_conditions)
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def is_chemical_reaction_arrow(eqArr_node: ET._Element) -> Optional[Dict[str, str]]:
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"""Detect if an eqArr represents a chemical reaction arrow with conditions.
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Args:
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eqArr_node: OMML eqArr element
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Returns:
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Dictionary with chemical reaction info if detected, None otherwise.
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Structure: {
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'above': str, # Text above the arrow (e.g., '电解')
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'below': str, # Text below the arrow (e.g., '加热', can be empty)
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'type': str # 'chemical_reaction'
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}
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Example:
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>>> # Assuming eqArr_node is an OMML element with reaction conditions
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>>> result = is_chemical_reaction_arrow(eqArr_node)
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>>> result['above']
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'电解'
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"""
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# Find all equation array elements
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e_elements = eqArr_node.findall(f"{{{OMML_NS}}}e")
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# Must have exactly 2 elements for chemical reaction conditions
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if len(e_elements) != 2:
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return None
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# Extract text from first element (above the arrow)
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above_text = ""
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first_elem = e_elements[0]
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# Extract text from all t elements in the first element, avoiding duplication
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# Use a set to track unique text content
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text_parts = set()
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for t_elem in first_elem.findall(f".//{{{OMML_NS}}}t"):
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if t_elem.text and t_elem.text.strip():
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text_parts.add(t_elem.text.strip())
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# Join unique text parts
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above_text = "".join(sorted(text_parts))
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# Extract text from second element (below the arrow)
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below_text = ""
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second_elem = e_elements[1]
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# Extract text from all t elements in the second element, avoiding duplication
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text_parts_below = set()
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for t_elem in second_elem.findall(f".//{{{OMML_NS}}}t"):
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if t_elem.text and t_elem.text.strip():
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text_parts_below.add(t_elem.text.strip())
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# Join unique text parts
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below_text = "".join(sorted(text_parts_below))
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# Validate that this looks like a chemical reaction pattern
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if above_text.strip():
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# Check if contains chemical condition patterns (Chinese text or typical reaction words)
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if (contains_chinese_characters(above_text) or
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is_typical_reaction_condition_text(above_text) or
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contains_chinese_characters(below_text) or
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is_typical_reaction_condition_text(below_text)):
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return {
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'above': above_text.strip(),
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'below': below_text.strip(),
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'type': 'chemical_reaction'
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}
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return None
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def detect_chemistry_context(equation_text: str) -> bool:
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"""Detect if equation suggests chemistry context - Conservative approach.
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Args:
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equation_text: The full equation text to analyze
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Returns:
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True if chemistry context is detected
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Example:
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>>> detect_chemistry_context('H2O + pH = 7')
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True
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>>> detect_chemistry_context('sin x + cos x')
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False
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"""
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if not equation_text:
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return False
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# Check if we're in a set theory context - if so, don't treat letters as chemical elements
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if has_set_theory_symbols(equation_text):
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return False
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# Check if we're in a mathematical context (trigonometry, calculus, etc.)
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if has_mathematical_functions(equation_text):
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return False
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# Conservative chemistry detection: require multiple indicators, not just chemical elements
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chemistry_indicators = ['pH', 'pOH', 'mol', 'atm', 'bar', 'Torr', 'eq', 'aq', 'sol',
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'↑', '↓', '→', '⇋', '⇌', 'xlongequal', 'rightarrow']
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# Only return True if we have actual chemistry indicators in the equation text
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return any(indicator in equation_text for indicator in chemistry_indicators)
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def has_mathematical_functions(equation_text: str) -> bool:
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"""Check if the equation contains mathematical functions.
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Args:
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equation_text: The equation text to analyze
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Returns:
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True if mathematical functions are detected
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Example:
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>>> has_mathematical_functions('sin x + cos x')
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True
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>>> has_mathematical_functions('H2O')
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False
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"""
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if not equation_text:
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return False
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# Common mathematical functions that indicate math context, not chemistry
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math_functions = ['sin', 'cos', 'tan', 'log', 'ln', 'exp', 'sqrt', 'lim', 'max', 'min',
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'arcsin', 'arccos', 'arctan', 'sinh', 'cosh', 'tanh']
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return any(func in equation_text for func in math_functions)
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def has_set_theory_symbols(equation_text: str) -> bool:
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"""Check if the equation contains set theory symbols.
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Args:
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equation_text: The equation text to analyze
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Returns:
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True if set theory symbols are detected
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Example:
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>>> has_set_theory_symbols('A ∩ B ⊂ C')
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True
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>>> has_set_theory_symbols('H2O')
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False
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"""
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if not equation_text:
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return False
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set_symbols = ['⊂', '⊃', '⊆', '⊇', '⊄', '⊅', '⊈', '⊉', '⊊', '⊋',
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'∈', '∉', '∋', '∌', '∪', '∩', '∖', '∁']
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return any(symbol in equation_text for symbol in set_symbols)
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def detect_physics_context(equation_text: str) -> bool:
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"""Detect if equation suggests physics context.
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Args:
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equation_text: The equation text to analyze
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Returns:
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True if physics context is detected
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Example:
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>>> detect_physics_context('F = ma, where m is in kg')
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True
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>>> detect_physics_context('x + y = z')
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False
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"""
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if not equation_text:
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return False
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# Check if we're in a mathematical context (trigonometry, calculus, etc.)
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if has_mathematical_functions(equation_text):
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return False
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# Common physics constants and units - look for these in the equation context
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physics_indicators = [
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'kg', 'm', 's', 'A', 'K', 'mol', 'cd', # SI base units
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'Hz', 'N', 'Pa', 'J', 'W', 'C', 'V', 'F', 'Ω', 'S', 'Wb', 'T', 'H', # Derived units
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'eV', 'cal', 'Bar', 'L', # Common non-SI
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# Note: removed single-letter constants like 'c', 'h', 'k', 'G', 'R', 'NA'
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# These are too common in math contexts and cause false positives
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]
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# Only return True if we have actual physics indicators in the equation text
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return any(indicator in equation_text for indicator in physics_indicators)
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def is_physics_constant(content: str) -> bool:
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"""Check if content is a known physics constant.
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Args:
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content: String to check
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Returns:
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True if content represents a known physics constant
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Example:
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>>> is_physics_constant('c')
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True
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>>> is_physics_constant('x')
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False
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"""
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constants = {
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'c', # speed of light
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'h', # Planck constant
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'hbar', # reduced Planck constant
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'k', # Boltzmann constant
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'kB', # Boltzmann constant
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'G', # gravitational constant
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'R', # gas constant
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'NA', # Avogadro number
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'e', # elementary charge
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'me', # electron mass
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'mp', # proton mass
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'mn', # neutron mass
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'mu', # atomic mass unit
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'epsilon0', # vacuum permittivity
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'mu0', # vacuum permeability
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'alpha', # fine structure constant
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'sigma', # Stefan-Boltzmann constant
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}
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return content in constants
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