给keywords_reaction增加正则表达式匹配

顺便做了正则表达式预编译

src/plugins/chat_module/only_process/only_message_process.py

@@ -2,7 +2,6 @@ from src.common.logger import get_module_logger
 from src.plugins.chat.message import MessageRecv
 from src.plugins.storage.storage import MessageStorage
 from src.plugins.config.config import global_config
-import re
 from datetime import datetime
 
 logger = get_module_logger("pfc_message_processor")
@@ -28,7 +27,7 @@ class MessageProcessor:
     def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
         """检查消息是否匹配过滤正则表达式"""
         for pattern in global_config.ban_msgs_regex:
-            if re.search(pattern, text):
+            if pattern.search(text):
                 logger.info(
                     f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}"
                 )

src/plugins/chat_module/reasoning_chat/reasoning_chat.py

@@ -1,6 +1,6 @@
 import time
 from random import random
-import re
+
 from typing import List
 from ...memory_system.Hippocampus import HippocampusManager
 from ...moods.moods import MoodManager
@@ -302,7 +302,7 @@ class ReasoningChat:
     def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
         """检查消息是否匹配过滤正则表达式"""
         for pattern in global_config.ban_msgs_regex:
-            if re.search(pattern, text):
+            if pattern.search(text):
                 logger.info(
                     f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}"
                 )

src/plugins/chat_module/reasoning_chat/reasoning_prompt_builder.py

@@ -115,6 +115,17 @@ class PromptBuilder:
                         f"检测到以下关键词之一：{rule.get('keywords', [])}，触发反应：{rule.get('reaction', '')}"
                     )
                     keywords_reaction_prompt += rule.get("reaction", "") + "，"
+                for pattern in rule.get("regex", []):
+                    result = pattern.search(message_txt)
+                    if result:
+                        reaction = rule.get('reaction', '')
+                        for name, content in result.groupdict().items():
+                            reaction = reaction.replace(f'[{name}]', content)
+                        logger.info(
+                            f"匹配到以下正则表达式：{pattern}，触发反应：{reaction}"
+                        )
+                        keywords_reaction_prompt += reaction + "，"
+                        break
 
         # 中文高手(新加的好玩功能)
         prompt_ger = ""

src/plugins/chat_module/think_flow_chat/think_flow_chat.py

@@ -1,6 +1,5 @@
 import time
 from random import random
-import re
 import traceback
 from typing import List
 from ...memory_system.Hippocampus import HippocampusManager
@@ -388,7 +387,7 @@ class ThinkFlowChat:
     def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
         """检查消息是否匹配过滤正则表达式"""
         for pattern in global_config.ban_msgs_regex:
-            if re.search(pattern, text):
+            if pattern.search(text):
                 logger.info(
                     f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}"
                 )

src/plugins/chat_module/think_flow_chat/think_flow_prompt_builder.py

@@ -61,6 +61,17 @@ class PromptBuilder:
                         f"检测到以下关键词之一：{rule.get('keywords', [])}，触发反应：{rule.get('reaction', '')}"
                     )
                     keywords_reaction_prompt += rule.get("reaction", "") + "，"
+                for pattern in rule.get("regex", []):
+                    result = pattern.search(message_txt)
+                    if result:
+                        reaction = rule.get('reaction', '')
+                        for name, content in result.groupdict().items():
+                            reaction = reaction.replace(f'[{name}]', content)
+                        logger.info(
+                            f"匹配到以下正则表达式：{pattern}，触发反应：{reaction}"
+                        )
+                        keywords_reaction_prompt += reaction + "，"
+                        break
 
         # 中文高手(新加的好玩功能)
         prompt_ger = ""

src/plugins/config/config.py

@@ -1,4 +1,5 @@
 import os
+import re
 from dataclasses import dataclass, field
 from typing import Dict, List, Optional
 from dateutil import tz
@@ -545,8 +546,8 @@ class BotConfig:
                 "response_interested_rate_amplifier", config.response_interested_rate_amplifier
             )
             config.down_frequency_rate = msg_config.get("down_frequency_rate", config.down_frequency_rate)
-            config.ban_msgs_regex = msg_config.get("ban_msgs_regex", config.ban_msgs_regex)
-
+            for r in msg_config.get("ban_msgs_regex", config.ban_msgs_regex):
+                config.ban_msgs_regex.add(re.compile(r))
             if config.INNER_VERSION in SpecifierSet(">=0.0.11"):
                 config.max_response_length = msg_config.get("max_response_length", config.max_response_length)
             if config.INNER_VERSION in SpecifierSet(">=1.1.4"):
@@ -587,6 +588,9 @@ class BotConfig:
             keywords_reaction_config = parent["keywords_reaction"]
             if keywords_reaction_config.get("enable", False):
                 config.keywords_reaction_rules = keywords_reaction_config.get("rules", config.keywords_reaction_rules)
+                for rule in config.keywords_reaction_rules:
+                    if rule.get("enable", False) and "regex" in rule:
+                        rule["regex"] = [re.compile(r) for r in rule.get("regex", [])]
 
         def chinese_typo(parent: dict):
             chinese_typo_config = parent["chinese_typo"]

template/bot_config_template.toml

@@ -149,6 +149,11 @@ enable = false # 仅作示例，不会触发
 keywords = ["测试关键词回复","test",""]
 reaction = "回答“测试成功”"
 
+[[keywords_reaction.rules]] # 使用正则表达式匹配句式
+enable = false # 仅作示例，不会触发
+regex = ["^(?P<n>\\S{1,20})是这样的$"] # 将匹配到的词汇命名为n，反应中对应的[n]会被替换为匹配到的内容，若不了解正则表达式请勿编写
+reaction = "请按照以下模板造句：[n]是这样的，xx只要xx就可以，可是[n]要考虑的事情就很多了，比如什么时候xx，什么时候xx，什么时候xx。（请自由发挥替换xx部分，只需保持句式结构，同时表达一种将[n]过度重视的反讽意味）"
+
 [chinese_typo]
 enable = true # 是否启用中文错别字生成器
 error_rate=0.001 # 单字替换概率