Update app.py

app.py

@@ -8,34 +8,23 @@ import spaces
 import cv2
 import numpy as np
 from PIL import Image
-import tempfile
+from gradio_client import Client, handle_file
 
-from parler_tts import ParlerTTSForConditionalGeneration
-from transformers import AutoTokenizer
-import soundfile as sf
+# Initialize TTS client
+tts_client = Client("dofbi/galsenai-xtts-v2-wolof-inference")
 
-device = "cuda:0" if torch.cuda.is_available() else "cpu"
-
-tts_model = ParlerTTSForConditionalGeneration.from_pretrained("CONCREE/Adia_TTS").to(device)
-tts_tokenizer = AutoTokenizer.from_pretrained("CONCREE/Adia_TTS")
-
-@spaces.GPU
 def tts(text):
-    output_wav_path = tempfile.mktemp(suffix=".wav")
-    # Description du style vocal
-    description = "A clear and educational voice, with a flow adapted to learning"
-    
-    # Génération
-    input_ids = tts_tokenizer(description, return_tensors="pt").input_ids.to(device)
-    prompt_ids = tts_tokenizer(text, return_tensors="pt").input_ids.to(device)
-    
-    audio = tts_model.generate(
-        input_ids=input_ids,
-        prompt_input_ids=prompt_ids,
-    )
-    sf.write(output_wav_path, audio.cpu().numpy().squeeze(), tts_model.config.sampling_rate)  # Fixed: was 'model.config'
-
-    return output_wav_path
+    """Generate TTS using Gradio API client"""
+    try:
+        result = tts_client.predict(
+            text=text,
+            audio_reference=handle_file('https://github.com/gradio-app/gradio/raw/main/test/test_files/audio_sample.wav'),
+            api_name="/predict"
+        )
+        return result
+    except Exception as e:
+        print(f"TTS API Error: {e}")
+        return None
 
 
 def progress_bar_html(label: str) -> str: