展示HN：Llmswap – 通过按项目的人工智能记忆解决“多个第二大脑”问题
我发现许多开发者（包括我自己）都在面临同样的问题：“我需要多个大脑来处理生活中的不同方面，但人工智能在会话之间总是忘记上下文。”<p>因此，我构建了 llmswap v5.1.0，采用了一个工作区系统，为每个项目提供持久的人工智能记忆。<p>它是如何工作的：<p><pre><code> - cd ~/work/api-platform → AI 加载企业模式和团队约定
- cd ~/learning/rust → AI 加载你的学习历程，以及你遇到的困难
- cd ~/personal/side-project → AI 加载个人偏好和实验
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每个工作区都有独立的记忆（context.md、learnings.md、decisions.md），在会话之间保持持久。你的人工智能导师实际上会记住你昨天、上周、上个月学到的内容。<p>主要功能：<p><pre><code> • 自动学习日志（AI 从每次对话中提取关键学习内容）
• 6种教学角色（在Guru、Socrates、Coach之间切换，以获得不同的视角）
• 兼容任何提供商（Claude Sonnet 4.5、IBM Watsonx、GPT-4 o1、Gemini、Groq、Ollama）
• Python SDK + CLI 一体化工具
• 无供应商锁定
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可以把它看作是“LLMs的cURL”——通用、简单、强大。<p>工作区系统是其与众不同之处。没有竞争对手（Claude Code、Cursor、Continue.dev）具备每个项目的持久记忆和自动学习跟踪功能。<p>专为以下开发者而建：<p><pre><code> - 管理多个项目并在上下文切换中迷失
- 厌倦了每次会话都要重新解释他们的技术栈
- 希望人工智能能在之前的学习基础上继续，而不是从零开始
- 需要不同的“模式”来处理工作/学习/副项目
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欢迎反馈！特别感兴趣的是：<p><pre><code> 1. 还有哪些工作区功能会有用？
2. 你目前如何管理跨项目的人工智能上下文？
3. 你会使用自动学习日志吗？
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GitHub: https://github.com/sreenathmmenon/llmswap<p>PyPI: pip install llmswap==5.1.0<p>文档: https://llmswap.org
查看原文
I kept seeing developers (including myself) struggle with the same problem: "I need multiple second brains for different aspects of my life, but AI keeps forgetting context between sessions."<p>So I built llmswap v5.1.0 with a workspace system that gives you persistent, per-project AI memory.<p>How it works:<p><pre><code> - cd ~/work/api-platform → AI loads enterprise patterns, team conventions
- cd ~/learning/rust → AI loads your learning journey, where you struggled
- cd ~/personal/side-project → AI loads personal preferences, experiments
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Each workspace has independent memory (context.md, learnings.md, decisions.md) that persists across sessions. Your AI mentor actually remembers what you learned yesterday, last week, last month.<p>Key features:<p><pre><code> • Auto-learning journals (AI extracts key learnings from every conversation)
• 6 teaching personas (rotate between Guru, Socrates, Coach for different perspectives)
• Works with ANY provider (Claude Sonnet 4.5, IBM Watsonx, GPT-4 o1, Gemini, Groq, Ollama)
• Python SDK + CLI in one tool
• Zero vendor lock-in
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Think of it as "cURL for LLMs" - universal, simple, powerful.<p>The workspace system is what makes this different. No competitor (Claude Code, Cursor, Continue.dev) has per-project persistent memory with auto-learning tracking.<p>Built for developers who:<p><pre><code> - Manage multiple projects and lose context switching
- Are tired of re-explaining their tech stack every session
- Want AI that builds on previous learnings, not starts from zero
- Need different "modes" for work/learning/side projects
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Open to feedback! Especially interested in:<p><pre><code> 1. What other workspace features would be useful?
2. How do you currently manage AI context across projects?
3. Would you use auto-learning journals?
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GitHub: https://github.com/sreenathmmenon/llmswap<p>PyPI: pip install llmswap==5.1.0<p>Docs: https://llmswap.org