Update app.py

app.py

@@ -6,12 +6,20 @@ import traceback
 
 def detect_watermark(audio_data):
     try:
-        # Check if audio_data is a tuple and contains a NumPy array
-        if not isinstance(audio_data, tuple) or not isinstance(audio_data[0], np.ndarray):
-            return f"Invalid input type: {type(audio_data)}"
-
+        # Ensure that audio_data is a tuple with two elements
+        if not (isinstance(audio_data, tuple) and len(audio_data) == 2):
+            return f"Invalid input: expected a tuple with two elements, got {type(audio_data)} with length {len(audio_data)}"
+        
+        # Ensure the first element of the tuple is a NumPy array
         audio_array, sample_rate = audio_data
-
+        if not isinstance(audio_array, np.ndarray):
+            return f"Invalid input: expected the first element of the tuple to be a np.ndarray, got {type(audio_array)}"
+        
+        # Ensure the second element of the tuple is an integer (sample rate)
+        if not isinstance(sample_rate, int):
+            return f"Invalid input: expected the second element of the tuple to be an int (sample rate), got {type(sample_rate)}"
+
+        # Now we can proceed with the assurance that audio_array is an np.ndarray and sample_rate is an int
         # Ensure audio_array is 2D (channels, samples). If it's mono, add an axis.
         if audio_array.ndim == 1:
             audio_array = np.expand_dims(audio_array, axis=0)