Samantha

I built Samantha because ChatGPT did not know my notes, links, history, or Mac shortcuts. The first version was no-code; later I moved the core toward Python, LangChain, and a Tauri macOS app.

A generic ChatGPT setup does not know private context, notes, links, memory, or system tools. Every conversation starts from zero.

If an assistant knows private context and lives close to the operating system, it can become a tool for working with knowledge, not just another chat window.

• macOS Tauri app as the desktop assistant frontend.
• Python/Flask/Chainlit backend plus earlier Make/Airtable integrations.
• Intent routing for memory, notes, links, and actions.
• Integrations with Slack, Telegram, Siri Shortcuts, iPhone, and Apple Watch.
• Voice, ElevenLabs, and private persona experiments.

LangChain, GPT, and intent classification route the conversation to memory, notes, links, or actions. The goal was not “chat with AI”; it was access to my own context without starting from zero.

Tauri, Svelte, TypeScript, Tailwind, Python, Flask, Chainlit, LangChain, Airtable, Make, macOS Shortcuts, and ElevenLabs.

• Build a private system for real usage before turning anything into a product.
• One interface for memory, notes, links, and actions instead of many tiny tools.
• macOS as the center because most work and automation happens there.

Private system I use as my own knowledge layer: desktop, Slack, Telegram, Siri, iPhone, Apple Watch, and automations.

Unify the backend, clean local repo secrets, tighten permissions, and decide which parts make sense as a public product.