Update app.py

app.py

@@ -1,3 +1,38 @@
-from transformers import TTSForConditionalGeneration, AutoModelForSeq2SeqLM
+from transformers import TTSForConditionalGeneration, AutoModelForSeq2SeqLM, AutoModelForCausalLM
 from datasets import load_dataset
-from gradio import Interface
+from gradio import Interface
+
+
+tts_model = TTSForConditionalGeneration.from_pretrained("facebook/s2s-wav2vec2-ft")
+whisper_model = AutoModelForSeq2SeqLM.from_pretrained("openai/whisper-medium")
+gpt2_xl_model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2-xl")
+
+
+def voice_chat(user_voice):
+    messages = [{"role": "system", "content": "You are a kind helpful assistant."}]
+    user_message = whisper_model.generate(user_voice)["generated_text"]
+    messages.append({"role": "user", "content": user_message})
+    print(messages)
+
+    # Utilize gpt2-xl locally for chat completion
+    with gpt2_xl_model.no_grad():
+        input_ids = gpt2_xl_model.tokenizer(messages, return_tensors="pt").input_ids
+        outputs = gpt2_xl_model.generate(input_ids, max_length=100)
+        chat_response = gpt2_xl_model.tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    reply = chat_response
+    messages.append({"role": "assistant", "content": reply})
+    audio = tts_model.generate(text=reply, return_tensors="pt").tolist()[0][0]
+    return reply, audio
+
+
+text_reply = Interface.Textbox(label="ChatGPT Text")
+voice_reply = Interface.Audio(type="audio/wav")
+
+Interface(
+    title="AI Voice Assistant with ChatGPT AI",
+    fn=voice_chat,
+    inputs=[Interface.Audio(source="microphone", type="filepath")],
+    outputs=[text_reply, voice_reply],
+    live=True,
+).launch(debug=True)