medkit

Browser-based ER + polyclinic clinical training simulator. You play the doctor: new patients arrive at triage, you talk to them in real time, order tests, treat, disposition. An attending physician (Claude Opus 4.7) watches and grades your decisions.

Hackathon submission. Cases are plausible but synthetic — no clinical claims.

About

Medkit is a voice-first AI patient simulator for medical students and newly graduated doctors. You take the history, order labs, read imaging, diagnose, and prescribe — talking to AI patients in real time. After each session, an attending grader powered by Claude Opus 4.7 marks your communication, history-taking, and clinical reasoning, citing published guidelines (NICE, ESC, AHA, GINA, GOLD) from a curated registry so the grading can't fabricate sources.

The format is modelled on OSCE training with standardised patients, which works well but is expensive, scheduled rarely, requires physical attendance, and isn't available in many countries — leaving most trainees globally with little or no access. Medkit makes the same kind of practice available on demand in the browser.

Built in three days for the Opus 4.7 hackathon by a medical-doctor-turned-software-engineer (@bedriyan), using Claude Code with Opus 4.7.

What's inside

Two flows: - ER — multiple beds, real-time voice with each patient, tests resolve over simulated minutes. - Polyclinic — one outpatient at a time, tests resolve instantly.

Prerequisites

• Node.js 22+ (TS files are run natively via type-stripping)
• Python 3.11+
• A modern browser with mic permission (Chrome/Edge recommended for WebRTC)

API keys you'll need

All keys are server-side only — the browser never sees them. Get one of each:

Setup

1. Frontend

npm install

2. Backend (two separate venvs)

The FastAPI server and the LiveKit voice worker have very different dependency trees, so they each get their own venv.

cd backend

# FastAPI server — small (FastAPI + Anthropic + livekit-api)
python -m venv .venv
.venv/Scripts/python -m pip install -r requirements.txt

# Voice worker — larger (livekit-agents + Deepgram/Cartesia/Silero plugins)
python -m venv .venv-voice
.venv-voice/Scripts/python -m pip install -r voice_agent_requirements.txt

On macOS/Linux replace .venv/Scripts/python with .venv/bin/python.

3. Configure secrets

cp backend/.env.example backend/.env.local

Fill in backend/.env.local:

ANTHROPIC_API_KEY=sk-ant-...
LIVEKIT_URL=wss://your-project.livekit.cloud
LIVEKIT_API_KEY=APIxxxx
LIVEKIT_API_SECRET=...
DEEPGRAM_API_KEY=...
CARTESIA_API_KEY=...

# Leave these blank on first run — see "Bootstrap the Managed Agent" below
MEDKIT_AGENT_ID=
MEDKIT_ENV_ID=

4. Bootstrap the Managed Agent (one-time)

Start the FastAPI server, then create the persistent attending agent:

backend/.venv/Scripts/python backend/server.py
# In another terminal:
curl -X POST http://127.0.0.1:8787/agent/bootstrap

The response contains an agent_id and environment_id. Paste them back into backend/.env.local as MEDKIT_AGENT_ID / MEDKIT_ENV_ID and restart the server. Subsequent runs are no-ops.

Run (three terminals)

# Terminal 1 — frontend
npm run dev
# Vite serves http://localhost:5173

# Terminal 2 — FastAPI backend
backend/.venv/Scripts/python backend/server.py
# Listens on http://127.0.0.1:8787 (proxied by Vite at /agent/* and /voice/*)

# Terminal 3 — LiveKit voice worker
backend/.venv-voice/Scripts/python backend/voice_agent.py dev
# Logs "registered worker" once connected to LiveKit Cloud

All three must be up for voice. The frontend works without the worker — you'll just lose real-time voice (text chat still works).

Open http://localhost:5173 and grant microphone permission when prompted.

Useful scripts

npm run build      # tsc + vite build
npm run preview    # preview production build
npm run verify     # deterministic invariants over src/data/* — run after editing cases/tests/treatments
npm run test       # custom-tools + loop-commands tests

Project layout

src/
  game/               # Store, types, single source of truth
  data/               # Patients, tests, treatments, medications, guidelines (pure data)
  components/         # React UI
  components/three/   # Three.js scenes (ER room, polyclinic)
  voice/              # LiveKit conversation + persona builders
  agents/             # Managed Agent client + custom-tool UI renderer
backend/
  server.py           # FastAPI: Managed Agents proxy + /voice/token
  voice_agent.py      # LiveKit Agents worker (Deepgram → Haiku → Cartesia)
.claude/skills/       # Authoring skills (patient generator, rubric author, guideline curator, ...)
scripts/verify/       # Deterministic data-integrity checks

Model routing

Notes

• Group policy on Windows: scripts call node node_modules/<pkg>/bin/<entry>.js instead of the .bin shims because some corporate machines block .exe wrappers under node_modules/. Keep this pattern when adding new scripts.
• Prompt caching is on in the patient-persona path — set cache_control: { type: 'ephemeral' } on system prompts when you add new Claude calls.
• Out of scope: multi-agent handoffs, persistent user accounts, anything claiming clinical accuracy.

License

Private — hackathon submission. Not licensed for redistribution.