feat(chat): add protection for quoted content in response processing

In the LLM response post-processing flow, a new protection layer for quoted content has been added. This prevents the sentence splitter from incorrectly breaking up complete sentences enclosed in quotation marks, thus ensuring the integrity of the quoted text.

- Adds `protect_quoted_content` and `recover_quoted_content` functions.
- Upgrades the response processing to a three-layer protection system (kaomoji, quotes, special blocks).
- Also adjusts the default values for typing simulation time to improve user experience.

src/chat/utils/utils.py

@@ -346,15 +346,54 @@ def recover_special_blocks(sentences: list[str], placeholder_map: dict[str, str]
         recovered_sentences.append(sentence)
     return recovered_sentences
 
+
+def protect_quoted_content(text: str) -> tuple[str, dict[str, str]]:
+    """识别并保护句子中被引号包裹的内容，返回处理后的文本和映射"""
+    placeholder_map = {}
+    # 匹配中英文单双引号，使用非贪婪模式
+    quote_pattern = re.compile(r'(".*?")|(\'.*?\')|(“.*?”)|(‘.*?’)')
+    
+    matches = quote_pattern.finditer(text)
+    
+    # 为了避免替换时索引错乱，我们从后往前替换
+    # finditer 找到的是 match 对象，我们需要转换为 list 来反转
+    match_list = list(matches)
+    
+    for idx, match in enumerate(reversed(match_list)):
+        original_quoted_text = match.group(0)
+        placeholder = f"__QUOTE_{len(match_list) - 1 - idx}__"
+        
+        # 直接在原始文本上操作，替换 match 对象的 span
+        start, end = match.span()
+        text = text[:start] + placeholder + text[end:]
+        
+        placeholder_map[placeholder] = original_quoted_text
+        
+    return text, placeholder_map
+
+
+def recover_quoted_content(sentences: list[str], placeholder_map: dict[str, str]) -> list[str]:
+    """恢复被保护的引号内容"""
+    recovered_sentences = []
+    for sentence in sentences:
+        for placeholder, original_block in placeholder_map.items():
+            sentence = sentence.replace(placeholder, original_block)
+        recovered_sentences.append(sentence)
+    return recovered_sentences
+
+
 def process_llm_response(text: str, enable_splitter: bool = True, enable_chinese_typo: bool = True) -> list[str]:
     if not global_config.response_post_process.enable_response_post_process:
         return [text]
 
-    # --- 双层防护系统 ---
+    # --- 三层防护系统 ---
     # 第一层：保护颜文字
     protected_text, kaomoji_mapping = protect_kaomoji(text) if global_config.response_splitter.enable_kaomoji_protection else (text, {})
     
-    # 第二层：保护数学公式和代码块
+    # 第二层：保护引号内容
+    protected_text, quote_mapping = protect_quoted_content(protected_text)
+
+    # 第三层：保护数学公式和代码块
     protected_text, special_blocks_mapping = protect_special_blocks(protected_text)
     
     # 提取被 () 或 [] 或 （）包裹且包含中文的内容
@@ -458,6 +497,7 @@ def process_llm_response(text: str, enable_splitter: bool = True, enable_chinese
 
     # --- 恢复所有被保护的内容 ---
     sentences = recover_special_blocks(sentences, special_blocks_mapping)
+    sentences = recover_quoted_content(sentences, quote_mapping)
     if global_config.response_splitter.enable_kaomoji_protection:
         sentences = recover_kaomoji(sentences, kaomoji_mapping)
 
@@ -467,8 +507,8 @@ def process_llm_response(text: str, enable_splitter: bool = True, enable_chinese
 def calculate_typing_time(
     input_string: str,
     thinking_start_time: float,
-    chinese_time: float = 0.3,
-    english_time: float = 0.15,
+    chinese_time: float = 0.1,
+    english_time: float = 0.05,
     is_emoji: bool = False,
 ) -> float:
     """