在句子分割里拉石

pull/937/head
Bakadax 2025-05-15 19:00:29 +08:00
parent a6c4bcd6cf
commit abb2ba3ce1
1 changed files with 80 additions and 50 deletions

View File

@ -50,6 +50,13 @@ def is_han_character(char_str: str) -> bool:
return _HAN_CHAR_REGEX.fullmatch(char_str) is not None return _HAN_CHAR_REGEX.fullmatch(char_str) is not None
def is_digit(char_str: str) -> bool:
"""检查字符是否为Unicode数字"""
if not isinstance(char_str, str) or len(char_str) != 1:
return False
return _Nd_REGEX.fullmatch(char_str) is not None
def is_relevant_word_char(char_str: str) -> bool: # 新增辅助函数 def is_relevant_word_char(char_str: str) -> bool: # 新增辅助函数
""" """
检查字符是否为相关词语字符非汉字字母 数字 检查字符是否为相关词语字符非汉字字母 数字
@ -229,16 +236,16 @@ def get_recent_group_speaker(chat_stream_id: int, sender, limit: int = 12) -> li
def split_into_sentences_w_remove_punctuation(text: str) -> list[str]: def split_into_sentences_w_remove_punctuation(text: str) -> list[str]:
"""将文本分割成句子,并根据概率合并 """将文本分割成句子,并根据概率合并
Args: Args:
text: 要分割的文本字符串 (假定颜文字已被保护) text: 要分割的文本字符串
Returns: Returns:
List[str]: 分割和合并后的句子列表 List[str]: 分割和合并后的句子列表
""" """
# print(f"DEBUG: 输入文本 (repr): {repr(text)}") # print(f"DEBUG: 输入文本 (repr): {repr(text)}")
# 预处理 # 预处理
text = regex.sub(r"\n\s*\n+", "\n", text) text = regex.sub(r"\n\s*\n+", "\n", text)
text = regex.sub(r"\n\s*([—。.,;\s\xa0])", r"\1", text) text = regex.sub(r"\n\s*([—。.,;\s\xa0])", r"\1", text)
text = regex.sub(r"([—。.,;\s\xa0])\s*\n", r"\1", text) text = regex.sub(r"([—。.,;\s\xa0])\s*\n", r"\1", text)
def replace_han_newline(match): def replace_han_newline(match):
char1 = match.group(1) char1 = match.group(1)
char2 = match.group(2) char2 = match.group(2)
@ -250,13 +257,13 @@ def split_into_sentences_w_remove_punctuation(text: str) -> list[str]:
len_text = len(text) len_text = len(text)
if len_text < 3: if len_text < 3:
if random.random() < 0.01: stripped_text = text.strip()
return list(text) if not stripped_text: return []
else: if len(stripped_text) == 1 and stripped_text in {"", "", ",", ".", ";", "", ""}:
return [text] return []
return [stripped_text]
separators = {"", "", ",", " ", ";", "\xa0", "\n", ".", "", "", ""} # 保持原有分隔符集合 separators = {"", "", ",", " ", ";", "\xa0", "\n", ".", "", "", ""}
# logger.debug(f"DEBUG: 使用的分隔符集合: {separators}")
segments = [] segments = []
current_segment = "" current_segment = ""
@ -264,16 +271,29 @@ def split_into_sentences_w_remove_punctuation(text: str) -> list[str]:
while i < len(text): while i < len(text):
char = text[i] char = text[i]
if char in separators: if char in separators:
can_split = True can_split = True # 默认情况下,分隔符会导致分割
if char == ' ' or char == '\xa0': # 仅当分隔符是空格或NBSP时检查两侧字符
if char == '.':
# 检查 '.' 是否处于需要特殊处理的上下文中 (例如,小数点或缩写词)
# 只有当 '.' 同时拥有前一个和后一个字符时,这些上下文检查才有意义
if 0 < i < len(text) - 1:
prev_char_val = text[i-1]
next_char_val = text[i+1]
# 规则1: 小数点 (数字.数字) -> 不分割
if is_digit(prev_char_val) and is_digit(next_char_val):
can_split = False
# 规则2: 西文缩写/域名 (西文字母.西文字母) -> 不分割
# 例如 U.S.A., example.com
elif is_letter_not_han(prev_char_val) and is_letter_not_han(next_char_val):
can_split = False
# 如果不满足上述不分割的条件 (例如句末的'.', 或'. '后的空格)can_split 保持 True执行分割
elif char == ' ' or char == '\xa0': # 处理空格/NBSP
if 0 < i < len(text) - 1: if 0 < i < len(text) - 1:
prev_char = text[i - 1] prev_char = text[i - 1]
next_char = text[i + 1] next_char = text[i + 1]
# 检查前后字符是否都是“相关词语字符”(非汉字字母或数字)
# 如果是,则不应在此处分割,因为这可能是一个单词内部的空格(例如 "word1 word2"
if is_relevant_word_char(prev_char) and is_relevant_word_char(next_char): if is_relevant_word_char(prev_char) and is_relevant_word_char(next_char):
can_split = False can_split = False # 非中文单词内部的空格不分割
if can_split: if can_split:
if current_segment: if current_segment:
segments.append((current_segment, char)) segments.append((current_segment, char))
@ -281,81 +301,91 @@ def split_into_sentences_w_remove_punctuation(text: str) -> list[str]:
segments.append(("", char)) segments.append(("", char))
current_segment = "" current_segment = ""
else: else:
# 如果不能分割 (can_split is False),则将当前字符(空格/NBSP加入到当前段落 current_segment += char # 不分割,将当前分隔符加入到当前段落
current_segment += char
else: else:
current_segment += char current_segment += char
i += 1 i += 1
if current_segment: if current_segment:
segments.append((current_segment, "")) segments.append((current_segment, ""))
filtered_segments = [] filtered_segments = []
for content, sep in segments: for content, sep in segments:
if content.strip(): stripped_content = content.strip()
filtered_segments.append((content, sep)) if stripped_content:
elif sep and sep not in [' ', '\xa0']: filtered_segments.append((stripped_content, sep))
elif sep and (sep not in [' ', '\xa0'] or sep == '\n'):
filtered_segments.append(("", sep)) filtered_segments.append(("", sep))
segments = filtered_segments segments = filtered_segments
if not segments: if not segments:
return [text] if text.strip() else [] return [text.strip()] if text.strip() else []
preliminary_final_sentences = [] preliminary_final_sentences = []
current_sentence_build = "" current_sentence_build = ""
for content, sep in segments: for k, (content, sep) in enumerate(segments):
current_sentence_build += content current_sentence_build += content
if sep and sep not in [' ', '\xa0']: is_strong_separator = sep in {"", ".", "", "", "\n", ""}
current_sentence_build += sep
if current_sentence_build.strip(): if content:
if sep and sep not in [' ', '\xa0']:
current_sentence_build += sep
if current_sentence_build.strip():
preliminary_final_sentences.append(current_sentence_build.strip())
current_sentence_build = ""
elif sep:
if current_sentence_build.strip() and not content.endswith(sep):
preliminary_final_sentences.append(current_sentence_build.strip())
current_sentence_build = ""
elif sep:
if current_sentence_build.strip() and is_strong_separator:
current_sentence_build += sep
preliminary_final_sentences.append(current_sentence_build.strip()) preliminary_final_sentences.append(current_sentence_build.strip())
current_sentence_build = "" current_sentence_build = ""
elif sep: elif not current_sentence_build.strip() and sep not in [' ', '\xa0']:
if current_sentence_build.strip(): preliminary_final_sentences.append(sep)
preliminary_final_sentences.append(current_sentence_build.strip())
current_sentence_build = ""
if current_sentence_build.strip(): if current_sentence_build.strip():
preliminary_final_sentences.append(current_sentence_build.strip()) preliminary_final_sentences.append(current_sentence_build.strip())
logger.debug(f"初步分割未合并已strip后的句子: {preliminary_final_sentences}") preliminary_final_sentences = [s for s in preliminary_final_sentences if s.strip()]
# print(f"DEBUG: 初步分割未合并已strip后的句子: {preliminary_final_sentences}")
if not preliminary_final_sentences: if not preliminary_final_sentences:
return [] return []
if len_text < 12: if len_text < 12: split_strength = 0.2
split_strength = 0.5 elif len_text < 32: split_strength = 0.5
elif len_text < 32: else: split_strength = 0.7
split_strength = 0.7
else:
split_strength = 0.9
merge_probability = 1.0 - split_strength merge_probability = 1.0 - split_strength
if merge_probability == 1.0 and len(preliminary_final_sentences) > 1 : # 只有多个句子才合并 if merge_probability == 1.0 and len(preliminary_final_sentences) > 1:
merged_text = "".join(preliminary_final_sentences).strip() merged_text = "".join(preliminary_final_sentences).strip()
# 移除末尾的逗号(中英文)
if merged_text.endswith(',') or merged_text.endswith(''): if merged_text.endswith(',') or merged_text.endswith(''):
merged_text = merged_text[:-1].strip() merged_text = merged_text[:-1].strip()
return [merged_text] if merged_text else [] return [merged_text] if merged_text else []
elif len(preliminary_final_sentences) == 1: # 如果只有一个初步句子,直接返回 elif len(preliminary_final_sentences) == 1:
s = preliminary_final_sentences[0].strip() s = preliminary_final_sentences[0].strip()
if s.endswith(',') or s.endswith(''): if s.endswith(',') or s.endswith(''):
s = s[:-1].strip() s = s[:-1].strip()
return [s] if s else [] return [s] if s else []
final_sentences_merged = [] final_sentences_merged = []
temp_sentence = "" temp_sentence = ""
if preliminary_final_sentences: if preliminary_final_sentences:
temp_sentence = preliminary_final_sentences[0] temp_sentence = preliminary_final_sentences[0]
for i in range(1, len(preliminary_final_sentences)): for i_merge in range(1, len(preliminary_final_sentences)):
if random.random() < merge_probability and temp_sentence: should_merge_based_on_punctuation = True
temp_sentence += " " + preliminary_final_sentences[i] if temp_sentence and temp_sentence[-1] in {"", ".", "", ""}:
should_merge_based_on_punctuation = False
if random.random() < merge_probability and temp_sentence and should_merge_based_on_punctuation:
temp_sentence += " " + preliminary_final_sentences[i_merge]
else: else:
if temp_sentence: if temp_sentence:
final_sentences_merged.append(temp_sentence) final_sentences_merged.append(temp_sentence)
temp_sentence = preliminary_final_sentences[i] temp_sentence = preliminary_final_sentences[i_merge]
if temp_sentence: if temp_sentence:
final_sentences_merged.append(temp_sentence) final_sentences_merged.append(temp_sentence)