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the AI record the time spent with you as a first-person narrative memory.","contributors":[{"name":"ProcyonNAN","email":"3189960265@qq.com"}],"maintainers":[{"name":"procyon-nan","email":"3189960265@qq.com"}],"readme":"# koishi-plugin-chatluna-livingmemory\n\n> 适用于 ChatLuna 的长期记忆插件。\n\n让 Bot 以第一人称的叙事记忆，记录下与你共度的时光。\n\n## 功能\n\n- 以预设（preset）为核心，全自动、异步地进行长期记忆的生成与召回\n- 标准 ChatLuna 会话会在系统提示词后注入用户画像，并在历史上下文之后、当前用户输入之前注入记忆快照；Character（伪装）插件通过预设中的 `{living_memory}` 变量注入记忆快照和相关用户画像\n- 提供 `embedding-rerank` 与 `agentic-recall（实验性）` 两种记忆召回策略\n- 提供 `living_memory_search` 与 `living_memory_get_messages` 记忆工具，供模型查询记忆并按记忆 id 查看来源消息；开启 `enableMemoryCreationTool` 后另提供 `living_memory_create_memory`，允许模型在对话中主动创建长期记忆\n- 通过手动全量 Dream 与自动增量 Dream 执行记忆库的合并、更新与归档\n- 根据记忆内容形成用户画像，并在对话中实时注入\n- 提供 Koishi Console WebUI，方便手动查看、创建、编辑、删除记忆和快照等数据\n\n## 安装方式\n\n### 在线安装\n\n在 Koishi 的插件市场中搜索 `chatluna-livingmemory`，并选择添加。\n\n### 本地开发\n\n1. 在本地 Koishi 项目的根目录中克隆仓库：\n\n```bash\nyarn clone https://github.com/Procyon-Nan/koishi-plugin-chatluna-livingmemory.git\n```\n\n2. 在本地 Koishi 项目的根目录中构建：\n\n```bash\nyarn workspace koishi-plugin-chatluna-livingmemory build\n```\n\n## 使用\n\n1. 在 Koishi 中启用 `koishi-plugin-chatluna-livingmemory`。\n\n2. 配置模型：\n\n| 配置项           | 模型用途                                                           | 是否必需                                    |\n| ---------------- | ------------------------------------------------------------------ | ------------------------------------------- |\n| `mainModel`      | 提取长期记忆，并在 Dream 中整理记忆和生成用户画像                  | 启用自动提取或 Dream 时必需                 |\n| `subModel`       | 改写 `embedding-rerank` 查询，或执行 `agentic-recall`              | 查询改写或 `agentic-recall` 启用时必需      |\n| `embeddingModel` | 为记忆检索、模型工具、手动 Dream 聚类和自动增量 Dream 检索生成向量 | 两种召回策略和 Dream 均必需                 |\n| `rerankModel`    | 对 `embedding-rerank` 的候选记忆重排序                             | 可选；未配置或调用失败时使用 embedding 排序 |\n\n如果你不知道应该如何配置 Embedding 嵌入模型和 Reranker 重排序模型，请参考[此文档](https://github.com/Procyon-Nan/koishi-plugin-chatluna-livingmemory/blob/main/docs/embedding-reranker-guide.md)进行配置。\n\n参考测试组合：\n\n- LLM 模型：`gemma4:31b`\n- Embedding 模型：`bce-embedding-base_v1`\n- Reranker 模型：`bce-reranker-base_v1`\n\n3. 在插件配置中选择记忆召回策略：\n\n    - `embedding-rerank`：可选使用 `subModel` 改写查询，使用 embedding 检索候选记忆，并在 reranker 可用时重排序，最后将 top-K 记忆引用写入快照。\n\n    - `agentic-recall（实验性）`：由 `subModel` 结合近期对话和当前消息，调用 `living_memory_search` 查询记忆，再将最终记忆文本和搜索轨迹写入快照。\n\n    `enableConversationIsolation` 默认关闭，同一预设内共享记忆。开启后，两种自动召回策略和对话中的 `living_memory_search` 只检索当前会话及来源会话为 `null` 的全局记忆。用户画像继续以用户为核心，Dream 和管理操作保留预设范围；Dream 跨来源合并仍可产生全局记忆。旧快照不清理，后续召回成功产生结果时替换；`living_memory_get_messages` 保留预设归属校验。\n\n    首次升级会在本地向量索引中增加来源会话字段，并通过启动对账补齐；已有向量保留，对账完成后恢复检索。后续切换隔离开关无需重建索引。管理页面的来源标签用于说明记忆来源，实际隔离依据是来源会话 ID。\n\n4. 对于 ChatLuna 主插件，在插件配置中开启 `开启记忆快照注入`。开启后，会在历史上下文之后、当前用户输入之前自动注入最近一次成功召回的记忆快照；同一次主插件请求内如果发生工具调用，后续模型调用会继续使用同一份记忆快照注入。开启用户画像注入后，相关用户画像会以 system 语义插入在系统提示词之后，并同样在同一次主插件请求内保持可用。\n\n5. 对于 Character（伪装）插件，需要在 Character 的预设文件 input 中写入变量以注入记忆快照和已启用的用户画像，例如：\n\n```text\ninput: |\n    # 你的记忆\n    {living_memory}\n```\n\n6. 在 Koishi Console 侧边栏进入 livingmemory WebUI，进行记忆的查看和管理。\n\n## Dream 整理流程\n\n- 在 WebUI 中手动执行 Dream 流程会对指定预设的活跃记忆执行分区聚类和整理，完成后按配置更新用户画像。\n- 自动 Dream 以尚未完成 consolidation 的记忆数量作为触发依据。阈值同时是单次任务的批次大小；每次只处理最早的一批，不会连续清空全部积压。\n- 自动 Dream 先整理本批新增记忆，再将仍需处理的记忆逐条与已固化的活跃旧记忆进行 content 向量检索，每条最多读取 30 条候选。该流程不执行 HDBSCAN，也不生成用户画像。\n- 自动 Dream 同时依赖 `mainModel` 和 `embeddingModel`。模型调用、Embedding 或持久化失败会保留未完成记忆，供后续任务继续处理。\n- 预设导入不会触发自动 Dream。跨预设导入的记忆会作为未整理数据写入，WebUI 会在导入完成后提示手动执行一次全量 Dream。\n\n## 记忆隔离机制\n\n记忆条目仅依照预设隔离，群聊和私聊之间不进行长期记忆隔离。\n\n预设召回使用的记忆快照依照会话隔离：\n\n| 接入方式          | 长期记忆分区          | 快照隔离方式                                                |\n| ----------------- | --------------------- | ----------------------------------------------------------- |\n| ChatLuna 主插件   | 原始 preset 名        | `conversationId`                                            |\n| Character（伪装） | `预设名（Character）` | `private:{userId}` 或 `group:{guildId}` 形式的 `sessionKey` |\n\n这意味着同一预设在不同会话中会共享长期记忆，但每个会话会使用各自的记忆快照，避免召回结果直接串到其他会话。\n\n## 自动提取白名单\n\n默认情况下，只要预设启用了自动记忆提取，所有使用该预设的群聊和私聊都会产生记忆。开启 `开启自动记忆总结（提取）白名单` 后，只有白名单内的会话才会自动提取记忆。\n\n白名单列表填写用户可直接获取的平台 id：群聊填群号，私聊填对方的用户 QQ 号。两种接入方式（ChatLuna 主插件与 Character）都使用同一份列表，判定所用的 id 与平台原始 id 一致，不需要填写 `conversationId` 或带前缀的频道 id。\n\n关闭白名单时，白名单列表本身不生效。开启白名单但列表为空，等同于全局关闭自动记忆提取。\n\n白名单只约束自动记忆提取。非白名单会话仍然照常召回记忆、注入记忆快照和用户画像，`living_memory_create_memory` 主动创建工具也不受白名单限制，只是不再由对话内容产生新的自动提取记忆。\n\n## 记忆查询工具\n\n`living_memory_search` 是提供给模型调用的记忆查询工具。它会在当前预设的 active 记忆中进行检索，并按匹配相关度排序返回结果。\n\n模型可填写的工具参数包括：\n\n| 字段             | 说明                                                                                                |\n| ---------------- | --------------------------------------------------------------------------------------------------- |\n| `searchTexts`    | 必填，1 到 3 个语义查询短语，每个 2 到 100 个字符，须为第一人称的完整句子描述                       |\n| `searchKeywords` | 选填，最多 3 个精确关键词，每个 2 到 10 个字符，用于关键词匹配                                      |\n| `memoryTypes`    | 必填，记忆类别，可选 `identity`、`preference`、`fact`、`plan`、`context`、`other`，或单独使用 `all` |\n\n工具返回结果包含记忆 `id`、记忆类别、记忆内容、摘要、关键词、重要度、创建时间、更新时间。返回结果不会包含 `status` 或来源消息。\n\n`living_memory_get_messages` 用于在当前预设内按记忆 `id` 批量查看来源消息。它只接受 `living_memory_search` 返回的记忆 `id`，每次最多查询 10 条记忆。返回结果包含目标记忆的基本信息、按 `originIndex` 编号的 `sourceOrigins`，以及未找到或不属于当前预设的 `notFoundMemoryIds`。\n\n`living_memory_create_memory` 是默认关闭的主动记忆创建工具，需在插件配置中开启 `enableMemoryCreationTool` 后才会注册。开启后，模型可以在对话中主动将当前内容写入长期记忆：既用于即时响应用户“记住这个”类的显式请求，也用于模型自主决定记录显著重要、不宜等待自动提取的信息。它与自动记忆提取使用同一套字段规范，产出完全同构的记忆；两者同时开启时同一事件可能被记录两次，由 Dream 整理收敛。单次调用允许提交的记忆条数由 `memoryCreateToolMaxMemories` 控制（默认 10）。\n\n工具参数为 `memories`，必填 JSON 数组，每条记忆包含与自动提取完全一致的六个字段：`type`（记忆类别）、`content`（第一人称记忆正文）、`summary`（检索摘要）、`keywords`（关键词）、`sentiment`（情绪色彩）、`importance`（0 到 1 的长期价值）。\n\n返回结果包含 `createdMemories`（已写入记忆的 `id` 与类别）与 `warnings`（如向量索引同步延迟等说明）。经此工具创建的记忆没有来源对话消息，`living_memory_get_messages` 会显示其无来源记录。\n\n默认日志会记录 Recall 快照更新后的完整最终注入文本、Recall 无结果时的快照保留事件、Dream 的启动/完成/失败，以及低频运维和索引事件。\n\n启用 `debug` 后，还会记录 Recall、Extraction、Dream（含用户画像）的每一次真实模型调用，包括完整 Prompt、完整原始响应、解析状态和关联标识。此类日志包含对话、预设提示词和记忆正文，仅应在访问受控的环境启用。API Key、Authorization、访问令牌、密码等基础设施凭证字段会统一掩码。\n","readmeFilename":"README.md"}