GlycemicGPT: Self-Hosted AI Diabetes Monitor with BYOAI and Plugin SDK

GlycemicGPT is an open-source diabetes management platform built for self-hosting. It connects continuous glucose monitors (CGM) and insulin pumps to an AI analysis layer that runs on your own infrastructure. The project was created by a Type 1 diabetic software engineer who needed a tool to review data between endocrinologist visits.

Supported Devices

• Dexcom G7 – via cloud API (verified)
• Tandem t:slim X2 – direct BLE + cloud API (verified)
• Tandem Mobi – BLE (protocol-compatible, not verified on physical hardware)
• Nightscout – point at your existing instance

AI Layer Features

• Daily briefs summarizing overnight and 24-hour patterns
• Meal response analysis
• Conversational chat backed by RAG with clinical knowledge
• Predictive alerting with configurable thresholds and caregiver escalation

Important: GlycemicGPT does not deliver insulin, control pumps, or function as a closed-loop system. It reads data and provides insights only.

Architecture

• Self-hosted via Docker or Kubernetes – runs entirely on your hardware
• BYOAI – bring your own AI provider: Ollama for fully local operation (zero data leaves your hardware), or any OpenAI-compatible endpoint (Claude, OpenAI, etc.)
• Data flows directly from your instance to the chosen provider; no centralized project-operated services

Stack

• Backend API: FastAPI, Python 3.12, PostgreSQL 16, Redis 7
• Web Dashboard: Next.js 15, React 19, Tailwind CSS, shadcn/ui
• AI Sidecar: TypeScript, Express, multi-provider proxy
• Android App: Kotlin, Jetpack Compose, BLE
• Wear OS: Kotlin, Wear Compose, Watch Face Push API
• Plugin SDK: Kotlin interfaces, capability-based, sandboxed

Quick Start

Deploy with Docker Compose, configure a .env file with your device credentials and AI provider endpoint, then run:
docker compose up -d

You can point it at an existing Nightscout instance for immediate data ingestion.

Who It's For

Developers with diabetes who want to self-host their own AI-powered monitoring stack, and contributors interested in BLE/Android or diabetes device integrations.