Smart Assistant

Voice assistant on a Raspberry Pi talking to the OpenAI Realtime API via an ASP.NET backend deployed on Coolify.

See docs/superpowers/specs/2026-06-11-smart-assistant-design.md for the full design. Implementation plans:

Plan 1 — docs/superpowers/plans/2026-06-11-smart-assistant-backend-foundation.md (Identity, devices, pairing, install endpoints).
Plan 2 — docs/superpowers/plans/2026-06-11-smart-assistant-device-hub-realtime-tools.md (device WebSocket hub, OpenAI Realtime relay, tools registry).

Repo layout

backend/ — ASP.NET 9 backend (Identity, Devices, Pairing, Install).
backend.tests/ — xUnit integration + unit tests via WebApplicationFactory.
client/ — Python client. Plan 1 ships placeholders only; the full wakeword + Realtime client lands in Plan 3.
Dockerfile + docker-compose.yml — multi-stage build; produces one image with the published ASP.NET app + a bundled client.tar.gz in wwwroot/client.tar.gz.
deploy.json — Coolify config (gitignored; contains the OpenAI key).
docs/superpowers/ — specs and plans.

Local development

dotnet test                              # all backend tests
dotnet run --project backend             # starts on http://localhost:5252

Hit http://localhost:5252/health to verify it's up.

Smoke test against a live deploy

The full pairing flow can be exercised with curl — no UI needed yet.

DOMAIN="https://assistant.volcanic.tes.gd"          # or your domain
COOKIE=$(mktemp)

# Register the first user (becomes Admin automatically) and sign in
curl -sf -c "$COOKIE" -X POST "$DOMAIN/api/auth/register" \
  -H 'content-type: application/json' \
  -d '{"email":"you@example.com","password":"Passw0rd!"}'
curl -sf -c "$COOKIE" -b "$COOKIE" -X POST "$DOMAIN/api/auth/login" \
  -H 'content-type: application/json' \
  -d '{"email":"you@example.com","password":"Passw0rd!"}'

# Generate a pairing code (auth required)
CODE=$(curl -sf -c "$COOKIE" -b "$COOKIE" -X POST "$DOMAIN/api/pair-code" \
  -H 'content-type: application/json' \
  -d '{"name":"kitchen"}' \
  | python3 -c 'import sys,json; print(json.load(sys.stdin)["code"])')
echo "code=$CODE"

# Pair as a device (public endpoint) and capture the token
curl -sf -X POST "$DOMAIN/api/pair" \
  -H 'content-type: application/json' \
  -d "{\"code\":\"$CODE\",\"hostname\":\"smoke\",\"client_version\":\"0.1\"}" \
  | python3 -m json.tool

# Verify the install script and client bundle are served
curl -sf "$DOMAIN/install.sh" | head -5
curl -sIf "$DOMAIN/client.tar.gz"

Expected: {"ok":true} on /health, JSON with device_id/device_token/backend_ws from /api/pair, the bash shebang from /install.sh, and a 200 OK with Content-Type: application/gzip for the bundle.

Plan 1 ships a placeholder Python bundle — running the bundled client.main will exit with the placeholder message. Plan 3 replaces it with the real wakeword + Realtime client.

Deploying

Use the Coolify v4 API. The deploy.json file (gitignored) carries the project + server UUIDs and the OpenAI key.

APP=$(python3 -c "import json; print(json.load(open('deploy.json'))['app']['uuid'])")
curl -sf -X POST "$COOLIFY_URL/api/v1/deploy?uuid=$APP" \
  -H "Authorization: Bearer $COOLIFY_KEY"

Fire-and-forget; the API returns a deployment_uuid immediately. Don't poll (per the global Coolify rule in CLAUDE.md).

Plan 2: device hub + Realtime relay

wss://<domain>/device — bearer-token WebSocket. Pair a device first to get a token.
Handshake: client sends {type:"hello", device_id, client_version}, backend replies hello_ack with per-device config (voice, model, system prompt, idle timeout, enabled tools).
Heartbeat: client sends {type:"ping"} every 15 s, backend replies pong and updates Devices.LastSeenAt.
Wake: {type:"wake"} opens a Realtime session against OpenAI; backend emits session_started (with conversation_id), forwards response.audio.delta as binary frames to the device, persists response.audio_transcript.done as an assistant turn, persists conversation.item.input_audio_transcription.completed as a user turn, and emits assistant_done after each response.done.
Tools shipped (per-device toggle via DeviceConfig.EnabledToolsJson):
- get_current_time (server-side, returns {"now":"<ISO-UTC>"}),
- end_session (closes the session after the current response.done completes; emits session_ended(reason="tool")),
- set_volume (round-trips a tool_call/tool_result envelope to the Pi; the Pi side will run amixer in Plan 3).
Idle timeout: server-side. With no input_audio_buffer.speech_started upstream event for IdleTimeoutSeconds, the relay emits session_ended(reason="idle").

The Python Pi client (Plan 3) is the production consumer of this surface. A quick handshake-only smoke against the live deploy:

DOMAIN="https://assistant.volcanic.tes.gd"
# Reuse the curl recipe above to log in, generate a pair-code, and pair
# a "smoke" device — capture $TOKEN from the /api/pair response.
python3 - <<PY
import asyncio, json, websockets
URL, TOKEN = "wss://assistant.volcanic.tes.gd/device", "$TOKEN"
async def main():
    async with websockets.connect(
        URL, additional_headers={"Authorization": f"Bearer {TOKEN}"}
    ) as ws:
        await ws.send(json.dumps({
            "type":"hello","device_id":"00000000-0000-0000-0000-000000000000",
            "client_version":"0.1"}))
        print("ack:", json.loads(await ws.recv())["type"])
        await ws.send(json.dumps({"type":"ping"}))
        print("pong:", json.loads(await ws.recv())["type"])
asyncio.run(main())
PY

Don't send wake from the smoke — it would open a real OpenAI session and burn budget. Plan 3 exercises that end-to-end.

What's next

Plan 3 — full Python client on the Pi (wakeword, VAD, audio plumbing, state machine, install + pair CLIs). This is the production caller of /device and the integration test for everything above.
Plan 4 — React management UI for the admin dashboard, per-device config editor, and conversation history viewer.

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