feat: run per node QA

api/services/workflow/qa/metrics.py

@@ -0,0 +1,37 @@
+"""Call metrics computation from raw event logs."""
+
+from pipecat.utils.enums import RealtimeFeedbackType
+
+
+def compute_call_metrics(
+    logs: list[dict], call_duration_seconds: float | None = None
+) -> dict:
+    """Pre-compute quantitative metrics from raw call logs."""
+    latencies = []
+    ttfb_values = []
+
+    for event in logs:
+        if event["type"] == RealtimeFeedbackType.LATENCY_MEASURED.value:
+            latencies.append(event["payload"]["latency_seconds"])
+        elif event["type"] == RealtimeFeedbackType.TTFB_METRIC.value:
+            ttfb_values.append(event["payload"]["ttfb_seconds"])
+
+    turns = set()
+    for event in logs:
+        if event["type"] in (
+            RealtimeFeedbackType.USER_TRANSCRIPTION.value,
+            RealtimeFeedbackType.BOT_TEXT.value,
+        ):
+            turns.add(event.get("turn", 0))
+
+    return {
+        "call_duration_seconds": call_duration_seconds,
+        "num_turns": len(turns),
+        "avg_latency_seconds": (
+            round(sum(latencies) / len(latencies), 2) if latencies else None
+        ),
+        "avg_ttfb_seconds": (
+            round(sum(ttfb_values) / len(ttfb_values), 2) if ttfb_values else None
+        ),
+        "max_latency_seconds": round(max(latencies), 2) if latencies else None,
+    }