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7cb8aac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 | """Shared rule engine for the humanize-text model.
Conservative bilingual editing rules derived from the reference projects:
- spaces/humanizer-lite (phrase replacements + protected spans)
- trust-fixes/humanizer.py (multi-method pipeline philosophy)
The rules generate the supervised (ai_text -> human_text) pairs used to
fine-tune the seq2seq model, and can also run as a standalone fallback.
"""
import re
# --------------------------------------------------------------------------
# Protected spans: code, URLs, paths, numbers, quoted strings.
# --------------------------------------------------------------------------
PROTECTED_PATTERN = re.compile(
r"(`[^`]+`|https?://[^\s\u4e00-\u9fff，。！？；：、]+|(?:[A-Za-z]:)?(?:[/\\][\w.\-]+)+|"
r"\b\d+(?:\.\d+)?(?:%|[A-Za-z]+)?\b|\"[^\"]*\"|'[^']*')"
)
CJK_RE = re.compile(r"[\u4e00-\u9fff]")
def protect(text: str, lang: str = "auto"):
"""Replace protected spans with language-aware placeholders:
EN ``PROTECTED_n``, ZH ``【保护n】`` (both tokenizer-friendly)."""
protected = []
zh = (
lang == "zh"
or (lang == "auto" and len(CJK_RE.findall(text)) > 0)
)
def replace(match):
token = f"【保护{len(protected)}】" if zh else f"PROTECTED_{len(protected)}"
protected.append(match.group(0))
return token
return PROTECTED_PATTERN.sub(replace, text), protected
def restore(text: str, protected):
"""Restore placeholders (either format, tolerant of inserted spaces)."""
for index, value in enumerate(protected):
text = re.sub(rf"PROTECTED_{index}\b", lambda m: value, text)
text = re.sub(
rf"【\s*保\s*护\s*{index}\s*】", lambda m: value, text
)
return text
# --------------------------------------------------------------------------
# Formulaic (AI) phrases, English and Chinese.
# --------------------------------------------------------------------------
EN_PHRASES = {
"in today's rapidly evolving world": "today",
"in today's fast-paced world": "now",
"it is important to note that": "",
"it is worth noting that": "",
"it can be seen that": "",
"serves as a testament to": "shows",
"a testament to": "proof of",
"delve into": "look at",
"leverage": "use",
"leveraging": "using",
"seamless": "smooth",
"robust": "reliable",
"game-changer": "big improvement",
"groundbreaking": "new",
"cutting-edge": "modern",
"state-of-the-art": "modern",
"plays a crucial role in": "matters for",
"plays a crucial role": "matters",
"in the realm of": "in",
"in conclusion": "",
"moreover": "also",
"furthermore": "also",
"additionally": "also",
"it is essential to": "we need to",
"comprehensive approach": "broad approach",
"foster": "support",
"fostering": "supporting",
"undoubtedly": "",
"no longer optional but essential": "necessary",
"revolutionize": "change",
"revolutionizing": "changing",
"holistic": "full",
}
ZH_PHRASES = {
"值得注意的是": "",
"在当今快速发展的时代": "现在",
"综上所述": "",
"总而言之": "",
"由此可见": "",
"赋能": "帮助",
"助力": "帮助",
"降本增效": "省钱提效",
"闭环": "完整流程",
"无缝": "顺畅",
"发挥着重要作用": "很有用",
"发挥着至关重要的作用": "很重要",
"数字化转型": "数字化",
"必然趋势": "趋势",
"积极拥抱新技术": "用新技术",
"不断提升": "提高",
"持续优化": "改进",
"实现": "做到",
"进一步": "",
}
EN_OPENERS = ["Moreover,", "Furthermore,", "Additionally,", "In conclusion,"]
EN_EXTRA = {
"very": "",
"really": "",
"extremely": "",
"highly": "",
}
CONTRACTIONS = {
"it is": "it's",
"it will": "it'll",
"we are": "we're",
"we will": "we'll",
"you are": "you're",
"you will": "you'll",
"do not": "don't",
"does not": "doesn't",
"cannot": "can't",
"I am": "I'm",
"I will": "I'll",
"that is": "that's",
"there is": "there's",
"will not": "won't",
"it is not": "it isn't",
}
ZH_PARTICLES_END = ["了", "吧", "呢"]
ZH_PARTICLES_START = ["其实", "说实话", "我总觉得"]
# --------------------------------------------------------------------------
# Core rule application (single pass, deterministic).
# --------------------------------------------------------------------------
def humanize_rules(text: str, lang: str = "auto") -> str:
"""Apply conservative editing rules to a draft. Deterministic."""
protected_text, protected = protect(text, lang)
if lang in ("auto", "en"):
low = protected_text.lower()
for phrase, replacement in EN_PHRASES.items():
protected_text = re.sub(re.escape(phrase), replacement, protected_text, flags=re.I)
# Only apply opener removals when they start a sentence boundary.
for opener in EN_OPENERS:
protected_text = re.sub(
re.escape(opener) + r"\s*", "", protected_text, flags=re.I
)
for word, replacement in EN_EXTRA.items():
protected_text = re.sub(r"\b" + re.escape(word) + r"\s+", "", protected_text, flags=re.I)
for phrase, replacement in CONTRACTIONS.items():
protected_text = re.sub(
r"\b" + re.escape(phrase) + r"\b", replacement, protected_text, flags=re.I
)
if lang in ("auto", "zh"):
for phrase, replacement in ZH_PHRASES.items():
protected_text = protected_text.replace(phrase, replacement)
protected_text = re.sub(r"，{2,}", "，", protected_text)
protected_text = re.sub(r"[ \t]{2,}", " ", protected_text)
protected_text = re.sub(r"\s+([,.;:!?，。；：！？])", r"\1", protected_text)
protected_text = re.sub(r"[,;]\s*\.", ".", protected_text)
protected_text = re.sub(r"\.\s*[,;]", ".", protected_text)
protected_text = re.sub(r"[，,]\s*(?=[。！？.!?])", "", protected_text)
protected_text = re.sub(r"\.\s+([a-z])", lambda m: ". " + m.group(1).upper(), protected_text)
protected_text = re.sub(r"([.!?。！？])\s*\1+", r"\1", protected_text)
protected_text = re.sub(r"\n{3,}", "\n\n", protected_text).strip(" ,，")
return restore(protected_text, protected)
def zh_add_colloquial(text: str) -> str:
"""Add light colloquial markers (used for data augmentation only)."""
if re.search(r"[\u4e00-\u9fff]", text):
text = re.sub(r"[。！？]", lambda m: m.group(0) + "呢", text, count=1)
text = re.sub(r"^", "其实，", text, count=1)
text = text.replace("今天", "今天吧")
text = text.replace("我觉得", "我总觉得")
return text
def en_add_colloquial(text: str) -> str:
"""Add light colloquial markers (used for data augmentation only)."""
text = re.sub(r"(^|\. )(I|we|he|she|they)\b", r"\1Honestly, \2", text, count=1)
text = text.replace("The ", "The ", 1)
if " quite " not in text:
text = re.sub(r"(\w+)\.$", r"\1, honestly.", text, count=1)
return text
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