Upload app.py

app.py

@@ -32,7 +32,7 @@ from quread.metrics import (
     MetricThresholds,
 )
 from quread.layout_mapper import parse_layout_csv_text
-from quread.trends import compute_metric_trends
+from quread.trends import compute_metric_trends, compute_drift_alerts, alerts_to_csv
 
 # --- Qubit cap (configurable) ---
 DEFAULT_MAX_QUBITS = 16  # safe default for CPU Spaces; change if you want
@@ -498,6 +498,59 @@ def _plot_metric_trends(series, labels, ranking_rows, metric_key, top_k):
     return fig
 
 
+def _drift_alert_summary(alert_rows):
+    total = len(alert_rows)
+    critical = sum(1 for r in alert_rows if str(r.get("level")) == "critical")
+    warning = sum(1 for r in alert_rows if str(r.get("level")) == "warning")
+    ok = max(0, total - critical - warning)
+    if critical > 0:
+        badge = "critical drift detected"
+    elif warning > 0:
+        badge = "warning drift detected"
+    else:
+        badge = "stable"
+    return f"Auto-flag summary: critical={critical}, warning={warning}, ok={ok} ({badge})."
+
+
+def _mitigation_hint_for_metric(metric_key, level):
+    severity = str(level or "ok")
+    if metric_key == "gate_error":
+        return "Prioritize gate pulse recalibration and schedule RB/IRB validation."
+    if metric_key == "readout_error":
+        return "Run readout discriminator retuning and measurement calibration refresh."
+    if metric_key == "decoherence_risk":
+        return "Reduce circuit depth on flagged qubits and revisit idle decoupling timing."
+    if metric_key in {"fidelity", "state_fidelity", "process_fidelity"}:
+        return "Re-characterize fidelity with tomography/benchmarking and re-tune control stack."
+    if metric_key == "coherence_health":
+        return "Investigate T1/T2 drift, thermal environment, and schedule recalibration windows."
+    if severity == "critical":
+        return "Lock flagged qubits out of high-depth paths and escalate full calibration."
+    if severity == "warning":
+        return "Increase monitoring cadence and rebalance workloads away from flagged qubits."
+    return "No immediate action required; continue scheduled monitoring."
+
+
+def _drift_recommendations_markdown(alert_rows, metric_key, max_items=6):
+    if not alert_rows:
+        return "No recommendations available yet. Run drift analysis first."
+
+    actionable = [r for r in alert_rows if str(r.get("level")) in {"critical", "warning"}]
+    if not actionable:
+        return "### Recommended Actions\n- No active drift alerts. Maintain regular calibration cadence."
+
+    lines = ["### Recommended Actions"]
+    k = max(1, min(int(max_items), len(actionable)))
+    for row in actionable[:k]:
+        q = int(row.get("qubit", -1))
+        level = str(row.get("level", "warning"))
+        hint = _mitigation_hint_for_metric(str(metric_key), level)
+        triggers = row.get("triggers") or []
+        reason = ", ".join(str(t) for t in triggers[:2]) if triggers else "trend threshold crossing"
+        lines.append(f"- q{q} ({level}): {hint} Trigger: {reason}.")
+    return "\n".join(lines)
+
+
 # ---------- Styling ----------
 CSS = """
 #title h1 { font-size: 38px !important; margin-bottom: 4px; letter-spacing: -0.02em; }
@@ -540,6 +593,7 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
     selected_gate_state = gr.State()
     explanation_md = gr.State("")
     last_explained_hash = gr.State("")
+    drift_alert_rows_state = gr.State([])
 
     with gr.Row(elem_classes=["app-shell"]):
         # Sidebar
@@ -755,6 +809,12 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
                             )
                             trend_top_k = gr.Slider(1, 32, value=8, step=1, label="Trend lines (top qubits)")
                             trend_btn = gr.Button("Analyze drift", variant="secondary")
+                        with gr.Row():
+                            drift_delta_warning = gr.Slider(0.0, 1.0, value=0.08, step=0.01, label="Drift delta warning")
+                            drift_delta_critical = gr.Slider(0.0, 1.0, value=0.18, step=0.01, label="Drift delta critical")
+                            drift_slope_warning = gr.Slider(0.0, 0.5, value=0.02, step=0.005, label="Drift slope warning")
+                            drift_slope_critical = gr.Slider(0.0, 0.5, value=0.05, step=0.005, label="Drift slope critical")
+                            drift_alert_top_k = gr.Slider(1, 64, value=16, step=1, label="Auto-flag rows")
                         with gr.Accordion("Snapshot Input", open=False):
                             trend_snapshots_file = gr.File(
                                 label="Snapshots file (.json/.jsonl/.txt)",
@@ -768,12 +828,20 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
                             )
                             gr.Markdown("<div class='small-note'>If both are provided, file input is used.</div>")
                         trend_status = gr.Markdown("Upload snapshots and click Analyze drift.")
+                        drift_alert_csv_dl = gr.DownloadButton("Download auto-flag CSV")
                         trend_plot = gr.Plot()
                         trend_table = gr.Dataframe(
                             headers=["qubit", "latest", "baseline", "delta"],
                             interactive=False,
-                            label="Latest ranking (highest selected metric first)",
+                            label="Latest ranking (highest metric risk first)",
+                        )
+                        drift_alert_status = gr.Markdown("Auto-flag summary: awaiting trend analysis.")
+                        drift_alert_table = gr.Dataframe(
+                            headers=["qubit", "alert", "latest_risk", "risk_delta", "risk_slope", "triggers"],
+                            interactive=False,
+                            label="Auto-flag panel",
                         )
+                        drift_reco_md = gr.Markdown("Recommendations appear after drift analysis.")
 
                 with gr.Tab("Explain"):
                     with gr.Group(elem_classes=["card"]):
@@ -1175,6 +1243,11 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
         snapshots_text,
         trend_metric_value,
         trend_top_qubits,
+        drift_delta_warn,
+        drift_delta_crit,
+        drift_slope_warn,
+        drift_slope_crit,
+        drift_alert_rows_max,
         activity_w,
         gate_error_w,
         readout_error_w,
@@ -1193,7 +1266,15 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
             ax.text(0.5, 0.5, "Provide calibration snapshots (JSON/JSONL).", ha="center", va="center")
             ax.axis("off")
             fig.tight_layout()
-            return fig, "No snapshots provided.", []
+            return (
+                fig,
+                "No snapshots provided.",
+                [],
+                "Auto-flag summary: no data.",
+                [],
+                [],
+                "No recommendations available yet. Run drift analysis first.",
+            )
 
         csv_text = to_csv(qc.history)
         weights, thresholds = _metric_controls_to_models(
@@ -1222,7 +1303,15 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
             ax.text(0.5, 0.5, f"Unable to parse snapshots: {exc}", ha="center", va="center")
             ax.axis("off")
             fig.tight_layout()
-            return fig, f"Drift analysis failed: {exc}", []
+            return (
+                fig,
+                f"Drift analysis failed: {exc}",
+                [],
+                f"Auto-flag summary unavailable: {exc}",
+                [],
+                [],
+                f"Recommendation generation unavailable: {exc}",
+            )
 
         fig = _plot_metric_trends(
             series,
@@ -1241,14 +1330,47 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
                     round(float(row["delta"]), 6),
                 ]
             )
+        alerts = compute_drift_alerts(
+            ranking,
+            warning_threshold=float(warning_thr),
+            critical_threshold=float(critical_thr),
+            delta_warning=float(drift_delta_warn),
+            delta_critical=float(drift_delta_crit),
+            slope_warning=float(drift_slope_warn),
+            slope_critical=float(drift_slope_crit),
+        )
+        max_rows = max(1, min(int(drift_alert_rows_max), len(alerts)))
+        alert_table_rows = []
+        for row in alerts[:max_rows]:
+            alert_table_rows.append(
+                [
+                    int(row["qubit"]),
+                    str(row["level"]),
+                    round(float(row["latest_risk"]), 6),
+                    round(float(row["risk_delta"]), 6),
+                    round(float(row["risk_slope"]), 6),
+                    "; ".join(row["triggers"]) if row["triggers"] else "-",
+                ]
+            )
+        alert_status = _drift_alert_summary(alerts)
+        recommendation_md = _drift_recommendations_markdown(
+            alerts,
+            str(meta.get("metric", trend_metric_value)),
+            max_items=6,
+        )
         status = (
             f"Snapshots parsed: {int(meta.get('parsed', 0))}"
             f" | Skipped: {int(meta.get('skipped', 0))}"
             f" | Format: {meta.get('format', 'unknown')}"
             f" | Points: {int(meta.get('points', 0))}"
             f" | Metric: {meta.get('metric', trend_metric_value)}"
+            f" | Risk mode: {meta.get('risk_mode', 'unknown')}"
         )
-        return fig, status, table_rows
+        return fig, status, table_rows, alert_status, alert_table_rows, alerts, recommendation_md
+
+    def _dl_drift_alert_csv(alert_rows):
+        rows = alert_rows or []
+        return _write_tmp("drift_alerts.csv", alerts_to_csv(rows))
 
     heat_btn.click(
         fn=_heat_and_hotspots_from_current,
@@ -1301,6 +1423,11 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
             trend_snapshots_text,
             trend_metric,
             trend_top_k,
+            drift_delta_warning,
+            drift_delta_critical,
+            drift_slope_warning,
+            drift_slope_critical,
+            drift_alert_top_k,
             w_activity,
             w_gate,
             w_readout,
@@ -1309,7 +1436,21 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
             thr_warning,
             thr_critical,
         ],
-        outputs=[trend_plot, trend_status, trend_table],
+        outputs=[
+            trend_plot,
+            trend_status,
+            trend_table,
+            drift_alert_status,
+            drift_alert_table,
+            drift_alert_rows_state,
+            drift_reco_md,
+        ],
+    )
+
+    drift_alert_csv_dl.click(
+        fn=_dl_drift_alert_csv,
+        inputs=[drift_alert_rows_state],
+        outputs=[drift_alert_csv_dl],
     )
 
     synopsys_tcl_dl.click(