Update app.py

app.py

@@ -3,6 +3,7 @@ import torch
 from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 from gtts import gTTS
 import os
+import librosa
 
 # Load Wav2Vec2 model and processor for speech-to-text
 processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-large-960h")
@@ -25,7 +26,6 @@ def speech_to_text(audio_file):
 
 def generate_response(text):
     # Using Hugging Face to generate a text-based response
-    # Use any model like DialoGPT for text response generation
     conversational_pipeline = pipeline("text-generation", model="microsoft/DialoGPT-medium")
     response = conversational_pipeline(text, max_length=50)
     return response[0]['generated_text']
@@ -51,8 +51,8 @@ def process_audio(audio_file):
 # Create Gradio interface for audio input/output
 iface = gr.Interface(
     fn=process_audio,
-    inputs=gr.inputs.Audio(source="microphone", type="file"),
-    outputs=[gr.outputs.Textbox(), gr.outputs.Audio(type="file")],
+    inputs=gr.Audio(source="microphone", type="file"),  # Updated for Gradio v3.x
+    outputs=[gr.Textbox(), gr.Audio(type="file")],  # Updated for Gradio v3.x
     live=True,
     title="Voice Bot with Wav2Vec2.0",
     description="Speak to the bot and get a response!"