Amrita长期记忆插件
Project description
amrita_plugin_memory
Amrita 长期记忆插件 - 一个智能记忆管理系统,用于帮助 AI 助手记住关于用户的长期信息。
技术栈
- 后端: Python 3.x 插件架构
- 向量数据库: ChromaDB (支持本地和远程模式)
- 嵌入模型: 支持 OpenAI Embedding API 和 Ollama Embedding API
- 框架: NoneBot2 + Amrita Core + AmritaBot
- 配置管理: Pydantic + TOML
- 异步处理: asyncio + aiologic + aiohttp
功能特点
- 长期记忆存储:持久化存储关于用户的长期重要信息
- 智能标签系统:支持使用标签对记忆进行分类管理
- 重要性分级:支持设置记忆的重要程度(low/medium/high)
- 灵活检索:支持按关键词检索记忆内容
- 完整管理:支持记忆的增删改查和列表查看
工具函数
插件提供了五个主要工具函数:
1. write_memory
将重要信息存入长期记忆
参数:
- content: 记忆内容,简洁明了(必需)
- tags: 分类标签,如
"preference"或"project"(必需) - importance: 重要性等级(必需,可选值:
"low","medium","high")
2. read_memory
从记忆库检索用户相关信息
参数:
- query: 关键词字符串,用空格分割(必需)
- top_k: 返回数量,默认5条(可选)
- importance: 重要性等级过滤(可选,可选值:
"low","medium","high")
3. update_memory
更新指定ID的记忆内容
参数:
- id: 要更新的记忆ID(必需)
- content: 新的记忆内容(可选)
- tags: 新的标签(可选)
- importance: 新的重要性等级(可选,可选值:
"low","medium","high")
4. delete_memory
删除指定ID的记忆
参数:
- id: 要删除的记忆ID(必需)
5. list_memory
列出当前用户的所有记忆
参数:
- limit: 返回数量限制,默认5条(可选)
配置选项
short_term_expiry_days: 短期记忆的过期天数,默认为3天long_term_expiry_days: 长期记忆的过期天数,默认为30天permanent_expiry_days: 永久记忆的过期天数,默认为1年per_session_memory_limit: 每个会话的记忆数量限制,默认为50条
安装和使用
- 安装插件:
amrita plugin install amrita_plugin_memory - 配置插件:插件会自动生成配置文件,或者您可以在WebUI中配置。
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