GlucoPilot

A self-hosted, single-user personal health platform centered on Type 1 diabetes. It unifies continuous glucose monitoring, insulin pump data, wearables, menstrual cycle tracking, lab work, and a daily symptom journal into one private app — then lets you talk to all of it.

The centerpiece is a health Companion: a chat grounded in your real data that remembers your lived experience and reasons across every domain at once — glucose, labs, hormones, sleep, symptoms, medications. Around it sit pattern detection, cross-domain insights, a printable clinician report, and a read-only login to share with a doctor.

Everything runs on your server with your API keys. With a local model, no health data ever leaves the machine.

Not a medical device. GlucoPilot is for personal data exploration and education. It does not diagnose, recommend insulin dosing, or control any device. Always consult your care team for treatment decisions.

_{A walkthrough of the built-in demo — all synthetic sample data, no real health information.}

What it does

Data sources (each connected from the in-app Connections page):

Source	Data	Notes
Dexcom Share	real-time glucose	the follower feed; near-live
Dexcom API v3	historical glucose + events	official API, ~1 h delay
Nightscout	glucose + treatments + profile	if you run one
Tandem Source	pump boluses / basal / suspends	t:slim X2 & Mobi, via tconnectsync
Glooko	pump treatments	Tandem & Omnipod 5 fallback
Oura Ring	sleep / readiness / HRV / HR / SpO₂ / temperature	OAuth
Fitbit / Google Health	steps / heart rate (near-real-time) / sleep / SpO₂ / breathing rate	OAuth; Google Health is Fitbit's successor API
CSV / Base44 export	bulk import	glucose, treatments, Oura, cycle

Talk to your data

• Companion — a health chat grounded in bounded, source-linked Evidence Bundles across glucose, labs, cycle, wearables, medications, and symptoms. It classifies personal observations/calculations/correlations/hypotheses, keeps general medical references and user memory separate, and provides Show evidence, What argues against this?, and What changed? controls. It remembers what you tell it across conversations, keeps multiple threads, and lets you switch between a quick local model and a deeper one. Not a doctor: it surfaces patterns and questions for your care team — never diagnoses or dosing.
• Overview — a cross-domain AI health summary that spots connections across your whole picture, not just glucose.
• Records — upload lab reports and imaging (PDF/photo); a local vision model extracts values into per-analyte trend charts.
• Visit Report — a printable 90-day clinical summary (AGP, TIR, per-phase metrics, labs, conditions, medications, symptoms) with an AI "quarter in review" narrative.
• Share-safe exports — preview and download role-appropriate private, clinician, emergency, deidentified research, or synthetic-demo JSON through explicit field allowlists with watermarks, expiration metadata, and secret exclusion.
• Contradiction review — deterministic checks keep conflicting glucose, pump, lab, timing, and revised-source evidence side by side, with attributed resolution history and no silent winner.
• Health hypotheses — tentative patient, algorithm, or clinician ideas stay visibly separate from diagnoses, retain supporting, opposing, and missing evidence plus attributable confidence changes, and require clinician review before they can be marked confirmed or ruled against.

Track & analyze

• Dashboard — real-time glucose, TIR/GMI/CV metrics, AGP, treatment timeline, live heart rate, wearable overlays.
• Explorer — a zoomable/pannable canvas chart of glucose with insulin, basal bands, and IOB estimation.
• Patterns — statistical + AI detection of recurring highs/lows, post-meal spikes, dawn phenomenon, etc.
• Insights — cross-domain correlations: glucose × sleep × readiness × activity × cycle.
• Insulin — total daily dose, estimated insulin resistance, and correction-response/absorption stats.
• Cycle — menstrual phases inferred automatically from Oura nightly temperature, tied to glucose/insulin.
• Wearables — sleep, activity, HR/HRV, and SpO₂ deep-dives with glucose overlays.
• Symptom journal — a nightly check-in (severity, duration, notes) that feeds the Companion, the analytics, and the report.
• Platform diagnostics — a privacy-safe operational view of source sync/data-through status, import quality, graph and analytics freshness, storage, and visible backup age. Source staleness also qualifies Companion and Visit Report context without becoming a health finding.

Your clinical picture

• Conditions, medications & allergies, profile — entered once in Settings, woven into the AI's context and printed on the Visit Report.
• Provider login — a read-only second account to share with a clinician.

Try the demo

Spin up a throwaway instance seeded with realistic synthetic data (no login, no real health info) to explore every feature:

docker compose -f docker-compose.demo.yml up -d --build
# then open http://localhost:8100

The demo auto-seeds ~90 days of glucose, treatments, wearables, cycle, and labs. Never enable DEMO_MODE on an instance holding real data — it skips login.

Screenshots

Explorer — zoomable glucose + insulin	Visit Report — printable clinician summary
Insights — cross-domain correlations	Cycle — phases inferred from Oura temperature
Patterns — statistical + AI detection	Records — lab trends from uploaded reports

Architecture

• Backend — FastAPI + SQLite. A generic JSON entity store, session auth with a read-only provider role, per-source sync modules, a background scheduler, and a pluggable LLM layer (Anthropic API or any local OpenAI-compatible server).
• Frontend — React + Vite + Tailwind (shadcn/ui), built and served by the backend.
• One container, docker compose up. State lives in a single Docker volume.

See docs/ARCHITECTURE.md for the module map.

Quick start

Easiest — run it on your own machine

You only need Docker. Then:

git clone https://github.com/Paco5687/GlucoPilot glucopilot && cd glucopilot
./install.sh

The installer checks Docker, generates your config (with a random secret key), asks a couple of quick questions (port, timezone, an optional AI key), starts the app, and prints the link — usually http://localhost:8000. Open it, create your login, and finish setup on the Settings page. That's the whole thing.

Server deploy (with a domain + HTTPS)

For a public deployment behind a reverse proxy:

git clone https://github.com/Paco5687/GlucoPilot glucopilot && cd glucopilot
cp .env.example .env          # set APP_SECRET_KEY and APP_PUBLIC_URL
docker compose up -d          # prebuilt image; add --build to build from source

Open your APP_PUBLIC_URL and complete the first-run admin setup. Then add integration credentials and AI provider on the Settings page, and connect sources on Connections. See docs/DEPLOY.md for reverse-proxy setup and docs/LOCAL_MODELS.md for a fully-private AI setup.

Forgot the admin password? docker compose exec glucopilot python -m server.reset_password.

Privacy & safety

Your data stays yours. GlucoPilot runs entirely on your server. There is no telemetry and no phone-home — the app only talks to the services you connect (CGM, pump, wearables, etc.) and, for AI features, the model provider you choose. Pick the local model and your health data — including uploaded lab reports and imaging — never leaves your machine. Everything lives in one SQLite database in a Docker volume you control; there is no shared backend and the maintainers never see your data.

AI web grounding is optional and off by default. When you enable it (Settings → AI web grounding), the Companion looks up general medical facts from trusted sources (NIH's MedlinePlus and PubMed, plus an optional web-search provider) and cites them — only the general medical topic of your question is sent, never your records or personal data. With it off, nothing about your questions leaves the machine.

It is deliberately single-user / single-tenant — one owner per deployment, so you're the sole custodian. It is not built to host other people's health data multi-tenant; run one instance per person.

⚕️ Not a medical device. GlucoPilot is for personal data exploration and education. It does not diagnose, recommend insulin dosing, or control any device, and its analytics are estimates — not clinical guidance. Always consult your care team for treatment decisions.

Found a security or privacy issue in the code? Please report it privately — see SECURITY.md.

Third-party integrations

Several connectors use unofficial APIs maintained by the diabetes DIY community (Dexcom Share, Tandem Source via tconnectsync, Glooko). These can change without notice; treat them as best-effort. GlucoPilot is not affiliated with Dexcom, Tandem, Insulet, Glooko, Oura, Fitbit, or Nightscout.

License

MIT — see LICENSE.