Create app.py

app.py

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+import gradio as gr
+import torch
+from TTS.api import TTS
+import os
+
+# Get device
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Initialize TTS model
+tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False).to(device)
+
+def voice_conversion(input_audio, target_voice):
+    output_path = "output.wav"
+    # Perform voice conversion
+    tts.voice_conversion_to_file(source_wav=input_audio, target_wav=target_voice, file_path=output_path)
+    return output_path
+
+# Get examples from Examples folder
+examples_folder = "Examples/"
+example_files = [f for f in os.listdir(examples_folder) if f.endswith(".wav")]
+
+# Define Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Voice Conversion using Coqui TTS")
+    
+    with gr.Row():
+        input_audio = gr.Audio(source="microphone", label="Record or Upload Your Voice", type="filepath")
+        target_voice = gr.Dropdown(choices=example_files, label="Select Target Voice from Examples", 
+                                   value=example_files[0], info="Located in Examples/ folder")
+
+    convert_button = gr.Button("Convert Voice")
+    output_audio = gr.Audio(label="Converted Voice", type="filepath")
+
+    with gr.Progress() as progress:
+        convert_button.click(voice_conversion, inputs=[input_audio, target_voice], outputs=output_audio, 
+                             progress=progress)
+
+# Launch with public=True for public URL access and share link
+demo.launch(share=True)