mirror of https://github.com/Mai-with-u/MaiBot.git
fix：优化agent模式提取逻辑，修复配置文件版本问题
SengokuCola
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060ce5d55b
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@ -44,14 +44,16 @@
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## 🔥 更新和安装
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**最新版本: v0.11.0** ([更新日志](changelogs/changelog.md))
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**最新版本: v0.11.3** ([更新日志](changelogs/changelog.md))
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可前往 [Release](https://github.com/MaiM-with-u/MaiBot/releases/) 页面下载最新版本
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可前往 [启动器发布页面](https://github.com/MaiM-with-u/mailauncher/releases/)下载最新启动器
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**GitHub 分支说明：**
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- `main`: 稳定发布版本(推荐)
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- `dev`: 开发测试版本(不稳定)
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- `classical`: 旧版本(停止维护)
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- `classical`: 经典版本(停止维护)
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### 最新版本部署教程
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- [🚀 最新版本部署教程](https://docs.mai-mai.org/manual/deployment/mmc_deploy_windows.html) - 基于 MaiCore 的新版本部署方式(与旧版本不兼容)
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@ -1,6 +1,11 @@
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# Changelog
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## [0.11.2] - 2025-11-15
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## [0.11.3] - 2025-11-17
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### 功能更改和修复
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- 优化记忆提取策略
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- 修改readme
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## [0.11.2] - 2025-11-16
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### 🌟 主要功能更改
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- "海马体Agent"记忆系统上线，最新最好的记忆系统，默认已接入lpmm
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- 添加黑话jargon学习系统
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@ -56,7 +56,7 @@ TEMPLATE_DIR = os.path.join(PROJECT_ROOT, "template")
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# 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
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# 对该字段的更新，请严格参照语义化版本规范：https://semver.org/lang/zh-CN/
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MMC_VERSION = "0.11.2"
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MMC_VERSION = "0.11.3"
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def get_key_comment(toml_table, key):
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@ -15,6 +15,35 @@ from src.llm_models.payload_content.message import MessageBuilder, RoleType, Mes
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logger = get_logger("memory_retrieval")
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THINKING_BACK_NOT_FOUND_RETENTION_SECONDS = 3600 # 未找到答案记录保留时长
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THINKING_BACK_CLEANUP_INTERVAL_SECONDS = 300 # 清理频率
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_last_not_found_cleanup_ts: float = 0.0
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def _cleanup_stale_not_found_thinking_back() -> None:
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"""定期清理过期的未找到答案记录"""
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global _last_not_found_cleanup_ts
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now = time.time()
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if now - _last_not_found_cleanup_ts < THINKING_BACK_CLEANUP_INTERVAL_SECONDS:
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return
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threshold_time = now - THINKING_BACK_NOT_FOUND_RETENTION_SECONDS
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try:
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deleted_rows = (
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ThinkingBack.delete()
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.where(
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(ThinkingBack.found_answer == 0) &
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(ThinkingBack.update_time < threshold_time)
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)
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.execute()
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)
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if deleted_rows:
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logger.info(f"清理过期的未找到答案thinking_back记录 {deleted_rows} 条")
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_last_not_found_cleanup_ts = now
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except Exception as e:
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logger.error(f"清理未找到答案的thinking_back记录失败: {e}")
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def init_memory_retrieval_prompt():
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"""初始化记忆检索相关的 prompt 模板和工具"""
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# 首先注册所有工具
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@ -312,8 +341,7 @@ async def _retrieve_concepts_with_jargon(
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results.append("；".join(output_parts) if len(output_parts) > 1 else output_parts[0])
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logger.info(f"在jargon库中找到匹配（精确匹配）: {concept}，找到{len(jargon_results)}条结果")
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else:
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# 未找到
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results.append(f"未在jargon库中找到'{concept}'的解释")
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# 未找到，不返回占位信息，只记录日志
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logger.info(f"在jargon库中未找到匹配: {concept}")
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if results:
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@ -351,11 +379,10 @@ async def _retrieve_persons_info(
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results.append(f"【{person}】\n{person_info}")
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logger.info(f"查询到人物信息: {person}")
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else:
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results.append(f"未找到人物'{person}'的信息")
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# 未找到时不插入占位信息
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logger.info(f"未找到人物信息: {person}")
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except Exception as e:
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logger.error(f"查询人物信息失败: {person}, 错误: {e}")
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results.append(f"查询人物'{person}'信息时发生错误: {str(e)}")
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if results:
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return "【人物信息检索结果】\n" + "\n\n".join(results) + "\n"
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@ -997,6 +1024,8 @@ async def _process_single_question(
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Optional[str]: 如果找到答案，返回格式化的结果字符串，否则返回None
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"""
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logger.info(f"开始处理问题: {question}")
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_cleanup_stale_not_found_thinking_back()
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# 先检查thinking_back数据库中是否有现成答案
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cached_result = _query_thinking_back(chat_id, question)
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@ -1005,26 +1034,22 @@ async def _process_single_question(
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if cached_result:
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cached_found_answer, cached_answer = cached_result
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# 根据found_answer的值决定是否重新查询
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if cached_found_answer: # found_answer == 1 (True)
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# found_answer == 1：20%概率重新查询
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if random.random() < 0.2:
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if random.random() < 0.5:
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should_requery = True
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logger.info(f"found_answer=1，触发20%概率重新查询，问题: {question[:50]}...")
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else: # found_answer == 0 (False)
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# found_answer == 0：40%概率重新查询
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if random.random() < 0.4:
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should_requery = True
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logger.info(f"found_answer=0，触发40%概率重新查询，问题: {question[:50]}...")
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# 如果不需要重新查询，使用缓存答案
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if not should_requery:
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if cached_answer:
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if not should_requery and cached_answer:
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logger.info(f"从thinking_back缓存中获取答案，问题: {question[:50]}...")
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return f"问题：{question}\n答案：{cached_answer}"
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else:
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# 缓存中没有答案，需要查询
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elif not cached_answer:
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should_requery = True
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logger.info(f"found_answer=1 但缓存答案为空，重新查询，问题: {question[:50]}...")
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else:
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# found_answer == 0：不使用缓存，直接重新查询
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should_requery = True
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logger.info(f"thinking_back存在但未找到答案，忽略缓存重新查询，问题: {question[:50]}...")
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# 如果没有缓存答案或需要重新查询，使用ReAct Agent查询
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if not cached_result or should_requery:
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@ -1,5 +1,5 @@
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[inner]
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version = "6.21.4"
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version = "6.21.5"
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#----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
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#如果你想要修改配置文件，请递增version的值
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@ -1,5 +1,5 @@
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[inner]
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version = "1.7.7"
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version = "1.7.8"
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# 配置文件版本号迭代规则同bot_config.toml
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