Update app.py

app.py

@@ -51,4 +51,84 @@ iface = gr.Interface(
 )
 
 # Launch the Gradio app
-iface.launch()
+iface.launch()
+
+
+
+# Import libraries
+import whisper
+import os
+from gtts import gTTS
+import gradio as gr
+from groq import Groq
+
+# Load Whisper model for transcription
+model = whisper.load_model("base")
+
+# Set up Groq API client (ensure GROQ_API_KEY is set in your environment)
+GROQ_API_KEY = "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"
+client = Groq(api_key=GROQ_API_KEY)  
+
+# Function to get the LLM response from Groq
+def get_llm_response(user_input):
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": user_input}],
+            model="llama3-8b-8192"  # Replace with your desired model
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        return f"Error: {e}"
+
+# Function to convert text to speech using gTTS
+def text_to_speech(text, output_audio="output_audio.mp3"):
+    try:
+        tts = gTTS(text)
+        tts.save(output_audio)
+        return output_audio
+    except Exception as e:
+        return f"Error generating audio: {e}"
+
+# Main chatbot function to handle audio input and output
+def chatbot(audio):
+    # Step 1: Transcribe the audio using Whisper
+    try:
+        result = model.transcribe(audio)
+        user_text = result["text"]
+    except Exception as e:
+        return f"Error in transcription: {e}", None
+
+    # Step 2: Get LLM response from Groq
+    response_text = get_llm_response(user_text)
+
+    # Step 3: Convert the response text to speech
+    output_audio = text_to_speech(response_text)
+
+    return response_text, output_audio
+
+# Gradio interface for dual input (microphone and file upload)
+with gr.Blocks() as demo:
+    gr.Markdown("# Voice-to-Voice Chatbot")
+    
+    # Input section
+    with gr.Row():
+        microphone_input = gr.Audio(source="microphone", type="filepath", label="Speak into the microphone")
+        file_upload_input = gr.Audio(source="upload", type="filepath", label="Upload an audio file")
+    
+    # Output section
+    chatbot_response_text = gr.Textbox(label="Chatbot Response")
+    chatbot_response_audio = gr.Audio(type="filepath", label="Response Audio")
+    
+    # Buttons to process each input
+    mic_button = gr.Button("Process Microphone Input")
+    file_button = gr.Button("Process Uploaded Audio")
+    
+    # Actions for buttons
+    mic_button.click(chatbot, inputs=microphone_input, outputs=[chatbot_response_text, chatbot_response_audio])
+    file_button.click(chatbot, inputs=file_upload_input, outputs=[chatbot_response_text, chatbot_response_audio])
+
+# Launch the Gradio app
+demo.launch()
+
+
+