Cognitive Twin

This repository is not a model. It is the model card / project home for Cognitive Twin — a local-first personal AI twin. Published here so anyone running a local LLM can understand, fork, or critique the agent without cloning first. The runnable code lives on GitHub; nothing here downloads weights.

A personal AI twin that runs on your own machine — a digital version of you. It learns who you are (a persona you create), reasons with a local model, and calls skills to do real things. Local-first by default; nothing leaves the machine unless you allow it.

What it does

  • Be you — a persona (likes, dislikes, values, style) so it reasons and speaks as you, not a generic assistant.
  • Remember you — private, on-device memory of how you actually behave. Clearable anytime.
  • Pick the right brain — routes each request to the best local model by task.
  • Talk — a native macOS Siri-style app: speak to it, it speaks back.
  • Act — bounded, permissioned tool-calling (web research, screen reading, open apps/URLs) with confirmation.

Choose your model backend

The twin drives more than one local backend and lets you switch models live:

Backend How models appear Notes
Ollama (default) llama3.2, qwen2.5:3b bare names
OpenAI-compatible lmstudio/qwen2.5-7b-instruct LM Studio, llama.cpp --api, Jan, vLLM, LocalAI
Apple Intelligence Apple Intelligence (on-device) fully on-device, no server

Tool/function calling is translated between the Ollama and OpenAI APIs, so skills work the same on either backend. Enable the OpenAI-compatible backend:

# LM Studio: load a model, then Developer ▸ Start Server (defaults to :1234)
CTWIN_USE_LMSTUDIO=1 python -m cognitive_twin voice --web
# …or any OpenAI-compatible base URL:
CTWIN_OPENAI_BASE=http://localhost:8080/v1 python -m cognitive_twin voice --web

Quick start

git clone https://github.com/sinhaankur/cognitive-twin-agent
cd cognitive-twin-agent
# Ollama path: install Ollama (https://ollama.com) and pull a tool-capable model
ollama pull llama3.2
python -m cognitive_twin "good morning"

See the GitHub repo for the full README, the native macOS Twin Voice app, model routing, and the skill system.

Why local-first

Local models already handle a large share of everyday queries. The gap is the software around them: a persona, a skill system, and a reliable loop that turns "do X" into real actions — locally, privately, on hardware you own.

License

MIT. Inspired by OpenJarvis ("Personal AI, on personal devices") — an original implementation, same spirit.

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