From 6900a8b26959ee33cabf80558ed4b5a2dd7fd66b Mon Sep 17 00:00:00 2001 From: SengokuCola <1026294844@qq.com> Date: Fri, 25 Jul 2025 16:51:13 +0800 Subject: [PATCH] =?UTF-8?q?feat=EF=BC=9A=E4=BC=98=E5=8C=96=E5=85=B3?= =?UTF-8?q?=E9=94=AE=E8=AF=8D=E6=8F=90=E5=8F=96=EF=BC=8C=E4=BC=98=E5=8C=96?= =?UTF-8?q?at=E5=92=8C=E5=9B=9E=E5=A4=8D=E7=9A=84=E8=A7=A3=E6=9E=90?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../heart_flow/heartflow_message_processor.py | 9 + src/chat/memory_system/Hippocampus.py | 81 +++---- src/chat/replyer/default_generator.py | 10 +- src/chat/utils/chat_message_builder.py | 216 +++++++++++++----- src/plugin_system/apis/send_api.py | 31 +-- 5 files changed, 218 insertions(+), 129 deletions(-) diff --git a/src/chat/heart_flow/heartflow_message_processor.py b/src/chat/heart_flow/heartflow_message_processor.py index 6956dbda7..95b059892 100644 --- a/src/chat/heart_flow/heartflow_message_processor.py +++ b/src/chat/heart_flow/heartflow_message_processor.py @@ -12,6 +12,7 @@ from src.chat.message_receive.storage import MessageStorage from src.chat.heart_flow.heartflow import heartflow from src.chat.utils.utils import is_mentioned_bot_in_message from src.chat.utils.timer_calculator import Timer +from src.chat.utils.chat_message_builder import replace_user_references_in_content from src.common.logger import get_logger from src.person_info.relationship_manager import get_relationship_manager from src.mood.mood_manager import mood_manager @@ -148,6 +149,14 @@ class HeartFCMessageReceiver: # 如果消息中包含图片标识，则将 [picid:...] 替换为 [图片] picid_pattern = r"\[picid:([^\]]+)\]" processed_plain_text = re.sub(picid_pattern, "[图片]", message.processed_plain_text) + + # 应用用户引用格式替换，将回复和@格式转换为可读格式 + processed_plain_text = replace_user_references_in_content( + processed_plain_text, + message.message_info.platform, + is_async=False, + replace_bot_name=True + ) logger.info(f"[{mes_name}]{userinfo.user_nickname}:{processed_plain_text}[兴趣度：{interested_rate:.2f}]") # type: ignore diff --git a/src/chat/memory_system/Hippocampus.py b/src/chat/memory_system/Hippocampus.py index c2dfc2180..13cf53f22 100644 --- a/src/chat/memory_system/Hippocampus.py +++ b/src/chat/memory_system/Hippocampus.py @@ -305,7 +305,7 @@ class Hippocampus: memories.sort(key=lambda x: x[2], reverse=True) return memories - async def get_keywords_from_text(self, text: str, fast_retrieval: bool = False) -> list: + async def get_keywords_from_text(self, text: str) -> list: """从文本中提取关键词。 Args: @@ -317,50 +317,45 @@ class Hippocampus: if not text: return [] - if fast_retrieval: - # 使用jieba分词提取关键词 + # 使用LLM提取关键词 - 根据详细文本长度分布优化topic_num计算 + text_length = len(text) + topic_num:str|list[int] = None + if text_length <= 5: words = jieba.cut(text) - # 过滤掉停用词和单字词 keywords = [word for word in words if len(word) > 1] - # 去重 - keywords = list(set(keywords)) - # 限制关键词数量 - logger.debug(f"提取关键词: {keywords}") - + keywords = list(set(keywords))[:3] # 限制最多3个关键词 + logger.info(f"提取关键词: {keywords}") + return keywords + elif text_length <= 10: + topic_num = [1,3] # 6-10字符: 1个关键词 (27.18%的文本) + elif text_length <= 20: + topic_num = [2,4] # 11-20字符: 2个关键词 (22.76%的文本) + elif text_length <= 30: + topic_num = [3,5] # 21-30字符: 3个关键词 (10.33%的文本) + elif text_length <= 50: + topic_num = [4,5] # 31-50字符: 4个关键词 (9.79%的文本) else: - # 使用LLM提取关键词 - 根据详细文本长度分布优化topic_num计算 - text_length = len(text) - topic_num:str|list[int] = None - if text_length <= 5: - topic_num = [1,2] # 1-5字符: 1个关键词 (26.57%的文本) - elif text_length <= 10: - topic_num = 2 # 6-10字符: 1个关键词 (27.18%的文本) - elif text_length <= 20: - topic_num = [2,3] # 11-20字符: 2个关键词 (22.76%的文本) - elif text_length <= 30: - topic_num = 3 # 21-30字符: 3个关键词 (10.33%的文本) - elif text_length <= 50: - topic_num = 4 # 31-50字符: 4个关键词 (9.79%的文本) - else: - topic_num = 5 # 51+字符: 5个关键词 (其余长文本) - - # logger.info(f"提取关键词数量: {topic_num}") - topics_response, (reasoning_content, model_name) = await self.model_summary.generate_response_async( - self.find_topic_llm(text, topic_num) - ) + topic_num = 5 # 51+字符: 5个关键词 (其余长文本) + + + topics_response, (reasoning_content, model_name) = await self.model_summary.generate_response_async( + self.find_topic_llm(text, topic_num) + ) - # 提取关键词 - keywords = re.findall(r"<([^>]+)>", topics_response) - if not keywords: - keywords = [] - else: - keywords = [ - keyword.strip() - for keyword in ",".join(keywords).replace("，", ",").replace("、", ",").replace(" ", ",").split(",") - if keyword.strip() - ] - - return keywords + # 提取关键词 + keywords = re.findall(r"<([^>]+)>", topics_response) + if not keywords: + keywords = [] + else: + keywords = [ + keyword.strip() + for keyword in ",".join(keywords).replace("，", ",").replace("、", ",").replace(" ", ",").split(",") + if keyword.strip() + ] + + logger.info(f"提取关键词: {keywords}") + + return keywords async def get_memory_from_text( @@ -388,7 +383,7 @@ class Hippocampus: - memory_items: list, 该主题下的记忆项列表 - similarity: float, 与文本的相似度 """ - keywords = await self.get_keywords_from_text(text, fast_retrieval) + keywords = await self.get_keywords_from_text(text) # 过滤掉不存在于记忆图中的关键词 valid_keywords = [keyword for keyword in keywords if keyword in self.memory_graph.G] @@ -710,7 +705,7 @@ class Hippocampus: Returns: float: 激活节点数与总节点数的比值 """ - keywords = await self.get_keywords_from_text(text, fast_retrieval) + keywords = await self.get_keywords_from_text(text) # 过滤掉不存在于记忆图中的关键词 valid_keywords = [keyword for keyword in keywords if keyword in self.memory_graph.G] diff --git a/src/chat/replyer/default_generator.py b/src/chat/replyer/default_generator.py index 9d75671c6..efefa0934 100644 --- a/src/chat/replyer/default_generator.py +++ b/src/chat/replyer/default_generator.py @@ -17,7 +17,7 @@ from src.chat.message_receive.uni_message_sender import HeartFCSender from src.chat.utils.timer_calculator import Timer # <--- Import Timer from src.chat.utils.utils import get_chat_type_and_target_info from src.chat.utils.prompt_builder import Prompt, global_prompt_manager -from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat +from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat, replace_user_references_in_content from src.chat.express.expression_selector import expression_selector from src.chat.knowledge.knowledge_lib import qa_manager from src.chat.memory_system.memory_activator import MemoryActivator @@ -629,6 +629,14 @@ class DefaultReplyer: mood_prompt = "" sender, target = self._parse_reply_target(reply_to) + + target = replace_user_references_in_content( + target, + chat_stream.platform, + is_async=False, + replace_bot_name=True + ) + # 构建action描述 (如果启用planner) action_descriptions = "" diff --git a/src/chat/utils/chat_message_builder.py b/src/chat/utils/chat_message_builder.py index 3a08ca72b..22f56d1df 100644 --- a/src/chat/utils/chat_message_builder.py +++ b/src/chat/utils/chat_message_builder.py @@ -2,7 +2,7 @@ import time # 导入 time 模块以获取当前时间 import random import re -from typing import List, Dict, Any, Tuple, Optional +from typing import List, Dict, Any, Tuple, Optional, Union, Callable from rich.traceback import install from src.config.config import global_config @@ -15,6 +15,155 @@ from src.chat.utils.utils import translate_timestamp_to_human_readable,assign_me install(extra_lines=3) +def replace_user_references_in_content( + content: str, + platform: str, + name_resolver: Union[Callable[[str, str], str], Callable[[str, str], Any]] = None, + is_async: bool = False, + replace_bot_name: bool = True +) -> Union[str, Any]: + """ + 替换内容中的用户引用格式，包括回复和@格式 + + Args: + content: 要处理的内容字符串 + platform: 平台标识 + name_resolver: 名称解析函数，接收(platform, user_id)参数，返回用户名称 + 如果为None，则使用默认的person_info_manager + is_async: 是否为异步模式 + replace_bot_name: 是否将机器人的user_id替换为"机器人昵称(你)" + + Returns: + 处理后的内容字符串（同步模式）或awaitable对象（异步模式） + """ + if is_async: + return _replace_user_references_async(content, platform, name_resolver, replace_bot_name) + else: + return _replace_user_references_sync(content, platform, name_resolver, replace_bot_name) + + +def _replace_user_references_sync( + content: str, + platform: str, + name_resolver: Optional[Callable[[str, str], str]] = None, + replace_bot_name: bool = True +) -> str: + """同步版本的用户引用替换""" + if name_resolver is None: + person_info_manager = get_person_info_manager() + def default_resolver(platform: str, user_id: str) -> str: + # 检查是否是机器人自己 + if replace_bot_name and user_id == global_config.bot.qq_account: + return f"{global_config.bot.nickname}(你)" + person_id = PersonInfoManager.get_person_id(platform, user_id) + return person_info_manager.get_value_sync(person_id, "person_name") or user_id + name_resolver = default_resolver + + # 处理回复格式 + reply_pattern = r"回复<([^:<>]+):([^:<>]+)>" + match = re.search(reply_pattern, content) + if match: + aaa = match.group(1) + bbb = match.group(2) + try: + # 检查是否是机器人自己 + if replace_bot_name and bbb == global_config.bot.qq_account: + reply_person_name = f"{global_config.bot.nickname}(你)" + else: + reply_person_name = name_resolver(platform, bbb) or aaa + content = re.sub(reply_pattern, f"回复 {reply_person_name}", content, count=1) + except Exception: + # 如果解析失败，使用原始昵称 + content = re.sub(reply_pattern, f"回复 {aaa}", content, count=1) + + # 处理@格式 + at_pattern = r"@<([^:<>]+):([^:<>]+)>" + at_matches = list(re.finditer(at_pattern, content)) + if at_matches: + new_content = "" + last_end = 0 + for m in at_matches: + new_content += content[last_end:m.start()] + aaa = m.group(1) + bbb = m.group(2) + try: + # 检查是否是机器人自己 + if replace_bot_name and bbb == global_config.bot.qq_account: + at_person_name = f"{global_config.bot.nickname}(你)" + else: + at_person_name = name_resolver(platform, bbb) or aaa + new_content += f"@{at_person_name}" + except Exception: + # 如果解析失败，使用原始昵称 + new_content += f"@{aaa}" + last_end = m.end() + new_content += content[last_end:] + content = new_content + + return content + + +async def _replace_user_references_async( + content: str, + platform: str, + name_resolver: Optional[Callable[[str, str], Any]] = None, + replace_bot_name: bool = True +) -> str: + """异步版本的用户引用替换""" + if name_resolver is None: + person_info_manager = get_person_info_manager() + async def default_resolver(platform: str, user_id: str) -> str: + # 检查是否是机器人自己 + if replace_bot_name and user_id == global_config.bot.qq_account: + return f"{global_config.bot.nickname}(你)" + person_id = PersonInfoManager.get_person_id(platform, user_id) + return await person_info_manager.get_value(person_id, "person_name") or user_id + name_resolver = default_resolver + + # 处理回复格式 + reply_pattern = r"回复<([^:<>]+):([^:<>]+)>" + match = re.search(reply_pattern, content) + if match: + aaa = match.group(1) + bbb = match.group(2) + try: + # 检查是否是机器人自己 + if replace_bot_name and bbb == global_config.bot.qq_account: + reply_person_name = f"{global_config.bot.nickname}(你)" + else: + reply_person_name = await name_resolver(platform, bbb) or aaa + content = re.sub(reply_pattern, f"回复 {reply_person_name}", content, count=1) + except Exception: + # 如果解析失败，使用原始昵称 + content = re.sub(reply_pattern, f"回复 {aaa}", content, count=1) + + # 处理@格式 + at_pattern = r"@<([^:<>]+):([^:<>]+)>" + at_matches = list(re.finditer(at_pattern, content)) + if at_matches: + new_content = "" + last_end = 0 + for m in at_matches: + new_content += content[last_end:m.start()] + aaa = m.group(1) + bbb = m.group(2) + try: + # 检查是否是机器人自己 + if replace_bot_name and bbb == global_config.bot.qq_account: + at_person_name = f"{global_config.bot.nickname}(你)" + else: + at_person_name = await name_resolver(platform, bbb) or aaa + new_content += f"@{at_person_name}" + except Exception: + # 如果解析失败，使用原始昵称 + new_content += f"@{aaa}" + last_end = m.end() + new_content += content[last_end:] + content = new_content + + return content + + def get_raw_msg_by_timestamp( timestamp_start: float, timestamp_end: float, limit: int = 0, limit_mode: str = "latest" ) -> List[Dict[str, Any]]: @@ -374,33 +523,8 @@ def _build_readable_messages_internal( else: person_name = "某人" - # 检查是否有 回复 字段 - reply_pattern = r"回复<([^:<>]+):([^:<>]+)>" - match = re.search(reply_pattern, content) - if match: - aaa: str = match[1] - bbb: str = match[2] - reply_person_id = PersonInfoManager.get_person_id(platform, bbb) - reply_person_name = person_info_manager.get_value_sync(reply_person_id, "person_name") or aaa - # 在内容前加上回复信息 - content = re.sub(reply_pattern, lambda m, name=reply_person_name: f"回复 {name}", content, count=1) - - # 检查是否有 @ 字段 @<{member_info.get('nickname')}:{member_info.get('user_id')}> - at_pattern = r"@<([^:<>]+):([^:<>]+)>" - at_matches = list(re.finditer(at_pattern, content)) - if at_matches: - new_content = "" - last_end = 0 - for m in at_matches: - new_content += content[last_end : m.start()] - aaa = m.group(1) - bbb = m.group(2) - at_person_id = PersonInfoManager.get_person_id(platform, bbb) - at_person_name = person_info_manager.get_value_sync(at_person_id, "person_name") or aaa - new_content += f"@{at_person_name}" - last_end = m.end() - new_content += content[last_end:] - content = new_content + # 使用独立函数处理用户引用格式 + content = replace_user_references_in_content(content, platform, is_async=False, replace_bot_name=replace_bot_name) target_str = "这是QQ的一个功能，用于提及某人，但没那么明显" if target_str in content and random.random() < 0.6: @@ -916,38 +1040,14 @@ async def build_anonymous_messages(messages: List[Dict[str, Any]]) -> str: anon_name = get_anon_name(platform, user_id) # print(f"anon_name:{anon_name}") - # 处理 回复 - reply_pattern = r"回复<([^:<>]+):([^:<>]+)>" - match = re.search(reply_pattern, content) - if match: - # print(f"发现回复match:{match}") - bbb = match.group(2) + # 使用独立函数处理用户引用格式，传入自定义的匿名名称解析器 + def anon_name_resolver(platform: str, user_id: str) -> str: try: - anon_reply = get_anon_name(platform, bbb) - # print(f"anon_reply:{anon_reply}") + return get_anon_name(platform, user_id) except Exception: - anon_reply = "?" - content = re.sub(reply_pattern, f"回复 {anon_reply}", content, count=1) - - # 处理 @，无嵌套def - at_pattern = r"@<([^:<>]+):([^:<>]+)>" - at_matches = list(re.finditer(at_pattern, content)) - if at_matches: - # print(f"发现@match:{at_matches}") - new_content = "" - last_end = 0 - for m in at_matches: - new_content += content[last_end : m.start()] - bbb = m.group(2) - try: - anon_at = get_anon_name(platform, bbb) - # print(f"anon_at:{anon_at}") - except Exception: - anon_at = "?" - new_content += f"@{anon_at}" - last_end = m.end() - new_content += content[last_end:] - content = new_content + return "?" + + content = replace_user_references_in_content(content, platform, anon_name_resolver, is_async=False, replace_bot_name=False) header = f"{anon_name}说 " output_lines.append(header) diff --git a/src/plugin_system/apis/send_api.py b/src/plugin_system/apis/send_api.py index 352ccdb45..f7b3092ef 100644 --- a/src/plugin_system/apis/send_api.py +++ b/src/plugin_system/apis/send_api.py @@ -19,6 +19,7 @@ await send_api.custom_message("video", video_data, "123456", True) """ +import asyncio import traceback import time import difflib @@ -30,7 +31,7 @@ from src.common.logger import get_logger from src.chat.message_receive.chat_stream import get_chat_manager from src.chat.message_receive.uni_message_sender import HeartFCSender from src.chat.message_receive.message import MessageSending, MessageRecv -from src.chat.utils.chat_message_builder import get_raw_msg_before_timestamp_with_chat +from src.chat.utils.chat_message_builder import get_raw_msg_before_timestamp_with_chat, replace_user_references_in_content from src.person_info.person_info import get_person_info_manager from maim_message import Seg, UserInfo from src.config.config import global_config @@ -183,32 +184,8 @@ async def _find_reply_message(target_stream, reply_to: str) -> Optional[MessageR if person_name == sender: translate_text = message["processed_plain_text"] - # 检查是否有 回复 字段 - reply_pattern = r"回复<([^:<>]+):([^:<>]+)>" - if match := re.search(reply_pattern, translate_text): - aaa = match.group(1) - bbb = match.group(2) - reply_person_id = get_person_info_manager().get_person_id(platform, bbb) - reply_person_name = await get_person_info_manager().get_value(reply_person_id, "person_name") or aaa - # 在内容前加上回复信息 - translate_text = re.sub(reply_pattern, f"回复 {reply_person_name}", translate_text, count=1) - - # 检查是否有 @ 字段 - at_pattern = r"@<([^:<>]+):([^:<>]+)>" - at_matches = list(re.finditer(at_pattern, translate_text)) - if at_matches: - new_content = "" - last_end = 0 - for m in at_matches: - new_content += translate_text[last_end : m.start()] - aaa = m.group(1) - bbb = m.group(2) - at_person_id = get_person_info_manager().get_person_id(platform, bbb) - at_person_name = await get_person_info_manager().get_value(at_person_id, "person_name") or aaa - new_content += f"@{at_person_name}" - last_end = m.end() - new_content += translate_text[last_end:] - translate_text = new_content + # 使用独立函数处理用户引用格式 + translate_text = await replace_user_references_in_content(translate_text, platform, is_async=True) similarity = difflib.SequenceMatcher(None, text, translate_text).ratio() if similarity >= 0.9: