sebastian
Sebastian is a LLM assistant with the ability to have permanent memory.
Stars: 908
Sebastian is a large model assistant with permanent memory. It not only provides basic answers from large models but also remembers anything you mention, recalling it at any time. It functions like a real Jarvis, with private deployment, no identity recognition, and data security. It breaks the context limits of large models, has automatic memory discovery, iterative memory updates, and memory associations. Based on Qwen2-Max model, using RAG and embedding, each conversation is a token. Users can interact with Sebastian to remember and recall information seamlessly over time.
README:
简体中文 | English
一个拥有永久记忆的大模型助手。想象一下,除了它能提供大模型的基本问答外,它能够记住你提起过的任何事情,并且在任何时间回忆起来有多么酷!
这是一个真正的贾维斯,私有化部署,无身份识别,数据安全。如此之外,它还有以下有点:
1,突破大模型上下文限制,不再出现“鱼的七秒记忆”。
2,记忆自动发掘,无需手动标记,交谈间助手将会自己发掘并记忆。
3,记忆迭代,助手会自动更新记忆,以适应新的对话,例如你的名字,喜欢的颜色。
4:记忆关联,例如助手记住了你的生日,而后你告知你不喜欢自己的星座,根据关联计算出你的星座是X,助手将一并记忆你不喜欢X。
基于 Qwen2-Max 大模型,使用 RAG 以及 embedding。并非通过携带上下文 tokens 实现,每一次对话都是一个 token。
场景1:
# 事件发生于 2022年某天
用户:我今天刚买了一个黑色的鼠标,它有三年的退换服务。
助手:我记住了。
# 事件发生于 2025年某天
用户:我的鼠标的按键有些使用故障,你知道如何处理吗?
助手:您在 2012 年购买过一个黑色鼠标,现在即将到期,您可以联系售后服务。
用户:我忘记了,什么鼠标?
助手:一个黑色的鼠标,购买时间是 2012年X月X日。场景2:
# 事件发生于某天。
用户:我是张三。
助手:你好,张三。
# 事件发生于几年后的某天,期间与助手经历过无数次对话,且助手应用时常关闭打开。
用户:我是谁?
助手:你是张三。
用户:我改名了,现在叫李四。
助手:好的,你的名字是李四。我们建议使用阿里云百炼大模型平台来获取大模型能力,这不仅可以得到最新流行的大模型,还可以获得更好的性能。通过以下链接获取
api_key:
https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key
进入项目目录,执行 docker-compose.yml 中的参数,尤其是 api_key。
执行 docker-compose up -d 启动应用。
而后通过访问 http://ip:8000/chat/text 实现文字对话,访问 http://ip:8000/chat/audio 实现语音对话。
如果您有任何建议或发现任何错误,请随时提交问题或拉取请求。
Afdian.net 是一个为创作者提供支持的平台。如果你喜欢这个项目,可以在 Afdian.net 上支持我。
感谢 JetBrains 提供优秀的 IDE。
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