171 lines
5.8 KiB
Python
171 lines
5.8 KiB
Python
import os
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import re
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import sys
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import importlib
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from config.logger import setup_logging
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from core.utils.textUtils import check_emoji
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logger = setup_logging()
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punctuation_set = {
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"，",
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",", # 中文逗号 + 英文逗号
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"。",
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".", # 中文句号 + 英文句号
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"！",
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"!", # 中文感叹号 + 英文感叹号
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"“",
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"”",
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'"', # 中文双引号 + 英文引号
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"：",
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":", # 中文冒号 + 英文冒号
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"-",
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"－", # 英文连字符 + 中文全角横线
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"、", # 中文顿号
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"[",
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"]", # 方括号
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"【",
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"】", # 中文方括号
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"~", # 波浪号
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}
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def create_instance(class_name, *args, **kwargs):
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# 创建TTS实例
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if os.path.exists(os.path.join('core', 'providers', 'tts', f'{class_name}.py')):
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lib_name = f'core.providers.tts.{class_name}'
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if lib_name not in sys.modules:
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sys.modules[lib_name] = importlib.import_module(f'{lib_name}')
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return sys.modules[lib_name].TTSProvider(*args, **kwargs)
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raise ValueError(f"不支持的TTS类型: {class_name}，请检查该配置的type是否设置正确")
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class MarkdownCleaner:
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"""
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封装 Markdown 清理逻辑：直接用 MarkdownCleaner.clean_markdown(text) 即可
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"""
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# 公式字符
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NORMAL_FORMULA_CHARS = re.compile(r'[a-zA-Z\\^_{}\+\-\(\)\[\]=]')
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@staticmethod
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def _replace_inline_dollar(m: re.Match) -> str:
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"""
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只要捕获到完整的 "$...$":
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- 如果内部有典型公式字符 => 去掉两侧 $
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- 否则 (纯数字/货币等) => 保留 "$...$"
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"""
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content = m.group(1)
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if MarkdownCleaner.NORMAL_FORMULA_CHARS.search(content):
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return content
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else:
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return m.group(0)
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@staticmethod
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def _replace_table_block(match: re.Match) -> str:
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"""
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当匹配到一个整段表格块时，回调该函数。
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"""
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block_text = match.group('table_block')
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lines = block_text.strip('\n').split('\n')
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parsed_table = []
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for line in lines:
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line_stripped = line.strip()
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if re.match(r'^\|\s*[-:]+\s*(\|\s*[-:]+\s*)+\|?$', line_stripped):
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continue
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columns = [col.strip() for col in line_stripped.split('|') if col.strip() != '']
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if columns:
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parsed_table.append(columns)
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if not parsed_table:
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return ""
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headers = parsed_table[0]
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data_rows = parsed_table[1:] if len(parsed_table) > 1 else []
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lines_for_tts = []
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if len(parsed_table) == 1:
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# 只有一行
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only_line_str = ", ".join(parsed_table[0])
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lines_for_tts.append(f"单行表格：{only_line_str}")
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else:
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lines_for_tts.append(f"表头是：{', '.join(headers)}")
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for i, row in enumerate(data_rows, start=1):
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row_str_list = []
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for col_index, cell_val in enumerate(row):
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if col_index < len(headers):
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row_str_list.append(f"{headers[col_index]} = {cell_val}")
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else:
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row_str_list.append(cell_val)
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lines_for_tts.append(f"第 {i} 行：{', '.join(row_str_list)}")
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return "\n".join(lines_for_tts) + "\n"
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# 预编译所有正则表达式（按执行频率排序）
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# 这里要把 replace_xxx 的静态方法放在最前定义，以便在列表里能正确引用它们。
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REGEXES = [
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(re.compile(r'```.*?```', re.DOTALL), ''), # 代码块
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(re.compile(r'^#+\s*', re.MULTILINE), ''), # 标题
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(re.compile(r'(\*\*|__)(.*?)\1'), r'\2'), # 粗体
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(re.compile(r'(\*|_)(?=\S)(.*?)(?<=\S)\1'), r'\2'), # 斜体
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(re.compile(r'!\[.*?\]\(.*?\)'), ''), # 图片
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(re.compile(r'\[(.*?)\]\(.*?\)'), r'\1'), # 链接
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(re.compile(r'^\s*>+\s*', re.MULTILINE), ''), # 引用
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(
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re.compile(r'(?P<table_block>(?:^[^\n]*\|[^\n]*\n)+)', re.MULTILINE),
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_replace_table_block
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),
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(re.compile(r'^\s*[*+-]\s*', re.MULTILINE), '- '), # 列表
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(re.compile(r'\$\$.*?\$\$', re.DOTALL), ''), # 块级公式
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(
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re.compile(r'(?<![A-Za-z0-9])\$([^\n$]+)\$(?![A-Za-z0-9])'),
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_replace_inline_dollar
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),
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(re.compile(r'\n{2,}'), '\n'), # 多余空行
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]
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@staticmethod
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def clean_markdown(text: str) -> str:
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"""
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主入口方法：依序执行所有正则，移除或替换 Markdown 元素
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"""
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# 检查文本是否全为英文和基本标点符号
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if text and all((c.isascii() or c.isspace() or c in punctuation_set) for c in text):
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# 保留原始空格，直接返回
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return text
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for regex, replacement in MarkdownCleaner.REGEXES:
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text = regex.sub(replacement, text)
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# 去除emoji表情
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text = check_emoji(text)
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return text.strip()
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def convert_percentage_to_range(percentage, min_val, max_val, base_val=None):
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"""
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将百分比(-100~100)转换为指定范围的值
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Args:
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percentage: 百分比值 (-100 到 100)
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min_val: 目标范围最小值
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max_val: 目标范围最大值
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base_val: 基准值（可选，默认为范围中点）
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Returns:
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转换后的值
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"""
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percentage, min_val, max_val = float(percentage), float(min_val), float(max_val)
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base_val = float(base_val) if base_val is not None else (min_val + max_val) / 2
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if percentage < 0:
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# 负百分比：从 base_val 向 min_val 线性插值
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result = base_val + (base_val - min_val) * (percentage / 100)
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else:
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# 正百分比：从 base_val 向 max_val 线性插值
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result = base_val + (max_val - base_val) * (percentage / 100)
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# 确保结果在有效范围内
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return max(min_val, min(max_val, result))
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