Create app.py

app.py

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+import gradio as gr
+import torch
+from transformers import VitsModel, AutoTokenizer
+import scipy.io.wavfile as wav
+import numpy as np
+import tempfile
+
+# Load the MMS-TTS Urdu model
+model_name = "facebook/mms-tts-urd-script_devanagari"
+model = VitsModel.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Function to generate speech from text
+def text_to_speech(urdu_text):
+    inputs = tokenizer(urdu_text, return_tensors="pt")
+    
+    with torch.no_grad():
+        output = model(**inputs).waveform.numpy()
+
+    # Save audio as a temporary file
+    temp_wav_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
+    wav.write(temp_wav_file.name, model.config.sampling_rate, output)
+
+    return temp_wav_file.name  # Return file path for playback & download
+
+# Gradio interface
+iface = gr.Interface(
+    fn=text_to_speech,
+    inputs=gr.Textbox(label="Enter Urdu Text", placeholder="یہاں اردو متن درج کریں"),
+    outputs=gr.Audio(label="Generated Speech"),
+    title="Urdu Text-to-Speech (MMS-TTS)",
+    description="یہ ایپلیکیشن آپ کے اردو متن کو مصنوعی آواز میں تبدیل کرتی ہے۔",
+    theme="compact"
+)
+
+# Launch the app
+iface.launch()