Update app.py

app.py

@@ -1,5 +1,3 @@
-
-
 import os
 import whisper
 from groq import Groq
@@ -8,7 +6,7 @@ import tempfile
 import gradio as gr
 
 # Step 1: Set up Whisper for transcription
-model = whisper.load_model("base")
+model = whisper.load_model("base")  # Ensure correct version of whisper is installed
 
 # Function to transcribe audio using Whisper
 def transcribe_audio(audio_file):
@@ -31,11 +29,9 @@ def get_groq_response(text):
 # Step 3: Convert text response from LLM to speech using GTTS
 def text_to_speech(text):
     tts = gTTS(text)
-    
     # Save the audio to a temporary file
     temp_file = tempfile.NamedTemporaryFile(delete=False)
     tts.save(temp_file.name)
-    
     # Return the file path for Gradio to play the audio
     return temp_file.name
 
@@ -43,18 +39,15 @@ def text_to_speech(text):
 def voice_chatbot(audio_input):
     # Step 1: Transcribe the audio using Whisper
     transcription = transcribe_audio(audio_input)
-    
     # Step 2: Get response from Groq API using the transcription
     response = get_groq_response(transcription)
-    
     # Step 3: Convert the response text to speech using GTTS
     audio_response = text_to_speech(response)
-    
     # Return the audio response (Gradio will play it)
     return audio_response
 
 # Step 5: Create the Gradio interface (microphone input and audio output)
-iface = gr.Interface(fn=voice_chatbot, 
+iface = gr.Interface(fn=voice_chatbot,
                      inputs=gr.Audio(type="filepath"),  # No source="microphone" argument
                      outputs=gr.Audio(),
                      live=True)