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app.py

@@ -20,6 +20,42 @@ import numpy as np
 import plotly.graph_objects as go
 import soundfile as sf
 
+try:
+    import _plotly_utils.basevalidators as _plotly_basevalidators
+
+    def _plotly_to_scalar_or_list_without_pandas(value):
+        np_mod = _plotly_basevalidators.get_module("numpy", should_load=False)
+        if np_mod and np_mod.isscalar(value) and hasattr(value, "item"):
+            return _plotly_basevalidators.to_non_numpy_type(np_mod, value)
+        if isinstance(value, (list, tuple)):
+            return [_plotly_to_scalar_or_list_without_pandas(item) for item in value]
+        if np_mod and isinstance(value, np_mod.ndarray):
+            if value.ndim == 0:
+                return _plotly_basevalidators.to_non_numpy_type(np_mod, value)
+            return [_plotly_to_scalar_or_list_without_pandas(item) for item in value]
+        if _plotly_basevalidators.is_numpy_convertable(value):
+            np_mod = _plotly_basevalidators.get_module("numpy", should_load=True)
+            if np_mod:
+                return _plotly_to_scalar_or_list_without_pandas(np_mod.array(value))
+        return value
+
+    def _plotly_is_homogeneous_array_without_pandas(value):
+        np_mod = _plotly_basevalidators.get_module("numpy", should_load=False)
+        if np_mod and isinstance(value, np_mod.ndarray):
+            return True
+        if isinstance(value, _plotly_basevalidators.nw.Series):
+            return True
+        if _plotly_basevalidators.is_numpy_convertable(value):
+            np_mod = _plotly_basevalidators.get_module("numpy", should_load=True)
+            if np_mod:
+                return np_mod.array(value).shape != ()
+        return False
+
+    _plotly_basevalidators.to_scalar_or_list = _plotly_to_scalar_or_list_without_pandas
+    _plotly_basevalidators.is_homogeneous_array = _plotly_is_homogeneous_array_without_pandas
+except Exception:
+    pass
+
 # ── paths ────────────────────────────────────────────────────────────────────
 
 SAMPLES     = os.path.join(os.path.dirname(__file__), "samples", "1089")
@@ -358,17 +394,19 @@ def make_waveform_figure(
 ) -> go.Figure:
     """Overlay waveform plot: original vs. protected audio."""
     n = min(len(original), len(protected), sr * 5)  # cap at 5 s
-    t = np.arange(n) / sr
+    t = (np.arange(n) / sr).tolist()
+    original_wave = original[:n].tolist()
+    protected_wave = protected[:n].tolist()
 
     fig = go.Figure()
     fig.add_trace(go.Scatter(
-        x=t, y=original[:n],
+        x=t, y=original_wave,
         name="Original",
         line=dict(color="#1565c0", width=1),
         opacity=0.85,
     ))
     fig.add_trace(go.Scatter(
-        x=t, y=protected[:n],
+        x=t, y=protected_wave,
         name="Protected",
         line=dict(color="#c62828", width=1),
         opacity=0.85,