Update app.py

app.py

@@ -212,18 +212,33 @@ def post_test_data():
 
 @app.route('/api/voice', methods=['POST'])
 def post_api_voice():
-    data = request.json
-    encoded_audio = data['base64']
-    mel_spectrogram, length = process_audio(encoded_audio)
-    with torch.no_grad():
-        output = voice_binary_model(mel_spectrogram,length)
-        prob  = torch.nn.functional.softmax(output[0], dim=0)
-        pred = torch.argmax(prob).item()
-        category = binary_labels[pred]
-        probs_dict = {binary_labels[i]:prob[i] for i in range(len(binary_labels))}
-    response = {
-        'message': 'Data received!',
-        'class' : category,
-        'probs' : probs_dict
-    }
-    return jsonify(response), 201
+    try:
+        data = request.json
+        if not data or 'base64' not in data:
+            return jsonify({'error': 'Invalid input. No base64 data provided.'}), 400
+        
+        encoded_audio = data['base64']
+        
+        # Process the audio to get Mel spectrogram and length
+        mel_spectrogram, length = process_audio(encoded_audio)
+        
+        # Ensure the model and input dimensions are correct
+        with torch.no_grad():
+            output = voice_binary_model(mel_spectrogram, length)
+            prob = torch.nn.functional.softmax(output[0], dim=0)
+            pred = torch.argmax(prob).item()
+            category = binary_labels[pred]
+            probs_dict = {binary_labels[i]: prob[i].item() for i in range(len(binary_labels))}
+        
+        response = {
+            'message': 'Data received!',
+            'class': category,
+            'probs': probs_dict
+        }
+        return jsonify(response), 201
+    
+    except KeyError as e:
+        return jsonify({'error': f'Missing key: {str(e)}'}), 400
+    
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500