Update app.py

app.py

@@ -10,7 +10,7 @@ token=os.environ.get("key_")
 genai.configure(api_key=api_key)
 tokenizer = AutoTokenizer.from_pretrained("asg2024/vits-ar-sa-huba",token=token)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model=VitsModel.from_pretrained("asg2024/vits-ar-sa-huba",token=token).to(device)
+model_vits=VitsModel.from_pretrained("asg2024/vits-ar-sa-huba",token=token).to(device)
 
 
 generation_config = {
@@ -91,7 +91,7 @@ def   modelspeech(text):
      with torch.no_grad():
           inputs = tokenizer(text, return_tensors="pt")#.cuda()
 
-          wav = model(input_ids=inputs["input_ids"]).waveform.cpu().numpy().reshape(-1)
+          wav = model_vits(input_ids=inputs["input_ids"]).waveform.cpu().numpy().reshape(-1)
           # display(Audio(wav, rate=model.config.sampling_rate))
           return  model.config.sampling_rate,wav#remove_noise_nr(wav)
 
@@ -105,7 +105,7 @@ def clean_text(text):
 
 def text_to_speech(text):
     
-    response = dash2(text)
+    response = dash(text)
     pad_text=''
     k=0
     for chunk in response:
@@ -127,12 +127,7 @@ def dash(text):
     for chunk in  response:
         yield chunk.text
 
-def dash2(text):
-    
-    response=get_answer_ai(text)
-    for chunk in  response:
-        yield chunk.text
-    # return textai
+
 
 
 # demo = gr.Interface(fn=dash, inputs=["text"], outputs=['text'])