Create app.py

app.py

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+import json
+import torch
+from TTS.api import TTS
+import gradio as gr
+
+# Load the language dictionary from the JSON file
+with open("language_dictionary.json", "r") as f:
+    language_dict = json.load(f)
+
+# Get device
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Function to generate audio
+def generate_audio(text, language):
+    model_name = f"tts_models/{language}/fairseq/vits"
+    tts = TTS(model_name=model_name, progress_bar=False).to(device)
+    output_path = "output_file.wav"
+    tts.tts_to_file(text=text, file_path=output_path)
+    return output_path
+
+# Create a list of language names for the dropdown
+languages = list(language_dict.values())
+iso_codes = list(language_dict.keys())
+
+# Create Gradio interface
+def run_interface():
+    def update_iso_code(language):
+        # Map selected language to its ISO code
+        iso_code = iso_codes[languages.index(language)]
+        return iso_code
+
+    with gr.Blocks() as demo:
+        with gr.Row():
+            text_input = gr.Textbox(label="Enter Text", lines=4, placeholder="Type your text here...")
+            language_dropdown = gr.Dropdown(label="Select Language", choices=languages)
+
+        generate_button = gr.Button("Generate Audio")
+        output_audio = gr.Audio(label="Generated Audio", type="filepath")
+
+        generate_button.click(
+            fn=lambda text, lang: generate_audio(text, update_iso_code(lang)),
+            inputs=[text_input, language_dropdown],
+            outputs=[output_audio]
+        )
+
+    demo.launch()
+
+# Run the Gradio interface
+if __name__ == "__main__":
+    run_interface()