Create app.py

app.py

@@ -0,0 +1,56 @@
+import os
+import torch
+import gradio as gr
+from TTS.api import TTS
+import noisereduce as nr
+import soundfile as sf
+import numpy as np
+import time
+import re
+
+# Agreements
+os.environ['COQUI_TOS_AGREED'] = '1'
+
+# Load Model
+print("⏳ Loading Engine...")
+device = "cuda" if torch.cuda.is_available() else "cpu"
+# Using a faster model for the first run
+tts = TTS("tts_models/multilingual/multi-dataset/your_tts").to(device)
+print("✅ Engine Loaded!")
+
+def generate_api_voice(text, reference_audio):
+    if not text or not reference_audio:
+        return None, "Error: Text aur Reference Audio dono zaroori hain!"
+    
+    try:
+        # 1. Noise Reduction
+        data, rate = sf.read(reference_audio)
+        if len(data.shape) > 1: data = data.mean(axis=1)
+        clean_data = nr.reduce_noise(y=data, sr=rate)
+        ref_path = "clean_ref.wav"
+        sf.write(ref_path, clean_data, rate)
+
+        # 2. Chunking Text
+        output_file = "output_voice.wav"
+        tts.tts_to_file(text=text, speaker_wav=ref_path, language="en", file_path=output_file)
+        
+        return output_file, "✅ Audio Generated Successfully!"
+    except Exception as e:
+        return None, f"⚠️ Error: {str(e)}"
+
+# Interface
+iface = gr.Interface(
+    fn=generate_api_voice,
+    inputs=[
+        gr.Textbox(label="Script daalo", placeholder="Yahan apna text likho..."),
+        gr.Audio(type="filepath", label="Voice Sample upload karo")
+    ],
+    outputs=[
+        gr.Audio(label="Glowmation AI Voice"),
+        gr.Textbox(label="Status")
+    ],
+    title="🎙️ Glowmation AI Engine v1",
+    description="Permanent API for Glowmation App"
+)
+
+iface.launch()