change to cpu

app.py

@@ -53,21 +53,22 @@ mistral_llm = Llama(model_path=mistral_model_path,n_gpu_layers=35,max_new_tokens
 
 # Load XTTS Model
 print("Loading XTTS model")
-os.environ["COQUI_TOS_AGREED"] = "1"
-tts_model_name = "tts_models/multilingual/multi-dataset/xtts_v2"
-ModelManager().download_model(tts_model_name)
-tts_model_path = os.path.join(get_user_data_dir("tts"), tts_model_name.replace("/", "--"))
-config = XttsConfig()
-config.load_json(os.path.join(tts_model_path, "config.json"))
-xtts_model = Xtts.init_from_config(config)
-xtts_model.load_checkpoint(
-    config,
-    checkpoint_path=os.path.join(tts_model_path, "model.pth"),
-    vocab_path=os.path.join(tts_model_path, "vocab.json"),
-    eval=True,
-    use_deepspeed=True,
-)
-xtts_model.cuda()
+#os.environ["COQUI_TOS_AGREED"] = "1"
+#tts_model_name = "tts_models/multilingual/multi-dataset/xtts_v2"
+#ModelManager().download_model(tts_model_name)
+#tts_model_path = os.path.join(get_user_data_dir("tts"), tts_model_name.replace("/", "--"))
+#config = XttsConfig()
+#config.load_json(os.path.join(tts_model_path, "config.json"))
+#xtts_model = Xtts.init_from_config(config)
+#xtts_model.load_checkpoint(
+#    config,
+#    checkpoint_path=os.path.join(tts_model_path, "model.pth"),
+#    vocab_path=os.path.join(tts_model_path, "vocab.json"),
+#    eval=True,
+#    use_deepspeed=True,
+#)
+#xtts_model.cuda()
+print("UN-Loading XTTS model")
 
 ###### Set up Gradio Interface ######
 
@@ -141,10 +142,11 @@ with gr.Blocks(title="Voice chat with LLM") as demo:
         def handle_speech_generation(sentence, chatbot_history, chatbot_voice):
             if sentence != "":
                 print("Processing sentence")
-                generated_speech = generate_speech_for_sentence(chatbot_history, chatbot_voice, sentence, xtts_model, xtts_supported_languages=config.languages, return_as_byte=True)
-                if generated_speech is not None:
-                    _, audio_dict = generated_speech
-                    yield (sentence, chatbot_history, audio_dict["value"])
+                yield (sentence, chatbot_history, None)
+               # generated_speech = generate_speech_for_sentence(chatbot_history, chatbot_voice, sentence, xtts_model, xtts_supported_languages=config.languages, return_as_byte=True)
+               # if generated_speech is not None:
+               #     _, audio_dict = generated_speech
+               #     yield (sentence, chatbot_history, audio_dict["value"])
 
         if initial_greeting:
             # Process only the initial greeting if specified