thinkwee / HiMe

What is HiMe?

HiMe delivers a self-hosted AI agent that ingests real-time Apple Watch and iPhone health data—heart rate, HRV, SpO2, sleep stages, workouts, and 50+ metrics—then runs autonomous analyses with scheduled checks and event triggers. Chat over Telegram or Feishu for evidence-backed responses, plus on-demand personalized pages and reusable skills for workflows. Python-based with Docker Compose stacks, iOS/watchOS apps for syncing, and a setup.sh wizard that handles LLM keys, IM credentials, and deployment in minutes. Think one-stop personal services for health tracking, like a github home for your wearable data.

Why is it gaining traction?

Full local privacy without cloud lock-in sets it apart from subscription trackers—your data stays on your server. The pixel-art cat digital twin adds personality to dashboards and chats, while OpenClaw-style interactions feel natural. Early buzz from 24 stars comes from devs seeking alternatives to felipe hime github clones or generic himel tools, especially with Feishu/Telegram gateways bridging East-West workflows.

Who should use this?

Apple ecosystem tinkerers analyzing personal biometrics without Big Tech oversight. Self-hosting enthusiasts building custom health dashboards or skills playbooks. Devs prototyping local LLM agents on time-series data, akin to one stop personalized career & education advisor github projects but for fitness metrics—not clinicians or production apps.

Verdict

Worth self-hosting for privacy-focused Apple users (grab the App Store binary), but 1.0% credibility reflects research-grade maturity: 24 stars, noncommercial license caps business use, and no diagnostics. Solid docs and hime.sh CLI for restarts/logs/reset make it dev-friendly; pair with Gemini/Claude for best results. Try if local health AI hooks you—skip for polished alternatives. (198 words)