Update app.py

app.py

@@ -159,12 +159,7 @@ async def load_model_data():
     sys.path.append('./content/piper/src/python')
     models_path = "./content/piper/src/python"
     logging.basicConfig(level=logging.DEBUG)
-    providers = [
-        "CPUExecutionProvider"
-        if use_gpu is False
-        else ("CUDAExecutionProvider", {"cudnn_conv_algo_search": "DEFAULT"})
-    ]
-    sess_options = onnxruntime.SessionOptions()
+  
 
     # Collect data for all models in the directory and populate model_configurations
     model_names, config_names = detect_onnx_models(models_path)
@@ -229,34 +224,39 @@ async def main(
     # ... (previous code)
 
     if selected_model in onnx_models:
-        model_name = selected_model
-        onnx_model = selected_model  # Replace with the actual key for your ONNX model file
-        if config:
-            model, config = load_onnx(onnx_model, sess_options, providers)
-            speaker_id_map = config.get("speaker_id_map", {})
-
-            auto_play = play
-            audio = inferencing(model, config, 1, text_input, speed_slider, noise_scale_slider, noise_scale_w_slider, auto_play)
-            temp_dir = tempfile.mkdtemp()
-            renamed_audio_file = os.path.join(temp_dir, "download.mp3")
-            audio.export(renamed_audio_file, format="mp3")
-
-            # Generate a unique file ID
-            file_id = str(uuid.uuid4())
-
-            # Store the file path with the generated file ID
-            files[file_id] = renamed_audio_file
-
-            # Create a URL to download the file
-            file_url = f'/download?fileId={file_id}'
-
-            # Restore the form and return the response
-            response_html = """
-            <script>
-            document.getElementById("loading-message").innerText = "Audio generated successfully!";
-            document.getElementById("synthesize_button").disabled = false;
-            </script>
-            """
+      #  model_name = selected_model
+      #  onnx_model = selected_model  # Replace with the actual key for your ONNX model file
+        
+        providers = ["CPUExecutionProvider"
+        if use_gpu is False
+        else ("CUDAExecutionProvider", {"cudnn_conv_algo_search": "DEFAULT"})
+        ]
+        sess_options = onnxruntime.SessionOptions()
+        model, config = load_onnx(selected_model, sess_options, providers)
+        speaker_id_map = config.get("speaker_id_map", {})
+
+        auto_play = play
+        audio = inferencing(model, config, selected_speaker_id, text_input, speed_slider, noise_scale_slider, noise_scale_w_slider, auto_play)
+        temp_dir = tempfile.mkdtemp()
+        renamed_audio_file = os.path.join(temp_dir, "download.mp3")
+        audio.export(renamed_audio_file, format="mp3")
+
+        # Generate a unique file ID
+        file_id = str(uuid.uuid4())
+
+        # Store the file path with the generated file ID
+        files[file_id] = renamed_audio_file
+
+        # Create a URL to download the file
+        file_url = f'/download?fileId={file_id}'
+
+        # Restore the form and return the response
+        response_html = """
+        <script>
+        document.getElementById("loading-message").innerText = "Audio generated successfully!";
+        document.getElementById("synthesize_button").disabled = false;
+        </script>
+        """
 
     else:
         # The selected_model is not found in the list; handle this case as needed