Relay: log upstream events + forward error envelopes to device for diagnostics

Plan 3 smoke surfaced 'session_ended reason=error' on every wake with no
context. The relay now logs every upstream event type at INFO and forwards
any upstream 'error' event to the device as 'error code=upstream_<code>'
so it appears in the Pi's journal alongside the wake/session_ended pair.

Also extends the client's wakeword.predict with per-frame RMS + score
diagnostics and the bridge loop with a 5 s heartbeat for triage.
This commit is contained in:
2026-06-12 06:28:58 +00:00
parent 82ea164695
commit d01b78b225
3 changed files with 46 additions and 2 deletions
+23 -1
View File
@@ -65,11 +65,15 @@ public class RealtimeSession
try
{
var enabled = _registry.EnabledFor(_cfg.EnabledTools).ToList();
_logger.LogInformation(
"relay opening session: model={Model} voice={Voice} tools=[{Tools}]",
_cfg.Model, _cfg.Voice, string.Join(",", enabled.Select(t => t.Name)));
await _upstream.SendJsonAsync(RealtimeEvents.SessionUpdate(_cfg, enabled), ct);
var ack = await WaitForUpstreamTypeAsync("session.updated", ct);
if (ack is null)
{
_logger.LogWarning("upstream closed before session.updated");
_endReason = EndReason.Error;
return;
}
@@ -274,7 +278,25 @@ public class RealtimeSession
{
var evt = await _upstream.ReceiveJsonAsync(ct);
if (evt is null) return null;
if ((string?)evt["type"] == type) return evt;
var evtType = (string?)evt["type"];
_logger.LogInformation("upstream evt={EvtType}", evtType);
if (evtType == "error")
{
var err = evt["error"] as JsonObject;
var code = (string?)err?["code"] ?? "unknown";
var msg = (string?)err?["message"] ?? evt.ToJsonString();
_logger.LogWarning("upstream error code={Code} message={Message}", code, msg);
await _output.WriteEnvelopeAsync(new JsonObject
{
["type"] = "error",
["code"] = "upstream_" + code,
["message"] = msg,
["fatal"] = false,
}, ct);
_endReason = EndReason.Error;
return null;
}
if (evtType == type) return evt;
}
}
}
+17
View File
@@ -43,11 +43,28 @@ def _build_bridge_thread(
stop_event: threading.Event,
) -> threading.Thread:
def run():
frame_counter = 0
recent_rms_max = 0.0
while not stop_event.is_set():
try:
pcm16_bytes = mic_queue.get(timeout=0.25)
except queue.Empty:
continue
frame_counter += 1
raw = np.frombuffer(pcm16_bytes, dtype=np.int16)
rms = float(np.sqrt(np.mean(raw.astype(np.float32) ** 2)))
if rms > recent_rms_max:
recent_rms_max = rms
# Every ~5 s emit a heartbeat so we can see if the InputStream is
# actually producing frames and what state we're routing to.
if frame_counter % 62 == 0:
_log.info(
"bridge frames=%d state=%s wake_en=%s up_en=%s qsize=%d rms_max_5s=%.0f",
frame_counter, sm.state.name,
sm.wakeword_enabled, sm.uplink_enabled, mic_queue.qsize(),
recent_rms_max,
)
recent_rms_max = 0.0
if sm.wakeword_enabled:
frame = np.frombuffer(pcm16_bytes, dtype=np.int16)
if frame.size != FRAME_SAMPLES:
+6 -1
View File
@@ -39,9 +39,14 @@ class WakewordDetector:
def predict(self, frame_16k_int16: np.ndarray) -> bool:
scores = self._model.predict(frame_16k_int16)
score = float(scores.get(WAKEWORD, 0.0))
rms = float(np.sqrt(np.mean(frame_16k_int16.astype(np.float32) ** 2)))
now = time.monotonic()
# Diagnostic: log any non-trivial score so we can see what's getting
# close to firing.
if score >= 0.1:
_log.info("score=%.3f rms=%.0f", score, rms)
if score >= self._threshold and (now - self._last_fired) >= self._cooldown_s:
self._last_fired = now
_log.info("wakeword fired score=%.3f", score)
_log.info("wakeword fired score=%.3f rms=%.0f", score, rms)
return True
return False