Update app.py

app.py

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+import whisper
+import gradio as gr
+from gtts import gTTS
+import os
+
+# Load Whisper model
+model = whisper.load_model("base")
+
+# Function to transcribe audio to text
+def transcribe_audio(audio_file):
+    try:
+        audio = whisper.load_audio(audio_file)
+        audio = whisper.pad_or_trim(audio)
+        mel = whisper.log_mel_spectrogram(audio).to(model.device)
+        result = model.transcribe(mel)
+        return result["text"]
+    except Exception as e:
+        return f"Error in transcription: {e}"
+
+# Function to generate text-to-speech
+def generate_speech(text):
+    try:
+        tts = gTTS(text)
+        output_file = "response.mp3"
+        tts.save(output_file)
+        return output_file
+    except Exception as e:
+        return f"Error in TTS: {e}"
+
+# Voice-to-Voice chatbot function
+def voice_to_voice(audio_file):
+    try:
+        # Transcribe the audio input
+        transcribed_text = transcribe_audio(audio_file)
+        if "Error" in transcribed_text:
+            return transcribed_text, None
+        
+        # Generate a response (mock response for now)
+        response_text = f"You said: {transcribed_text}"
+        
+        # Convert response text to speech
+        audio_response = generate_speech(response_text)
+        if "Error" in audio_response:
+            return response_text, None
+        
+        return response_text, audio_response
+    except Exception as e:
+        return f"Error in processing: {e}", None
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=voice_to_voice,
+    inputs=gr.Audio(type="filepath"),  # Accepts audio input
+    outputs=[
+        gr.Textbox(label="Transcription"),  # Displays transcribed text
+        gr.Audio(type="filepath")  # Returns audio response
+    ],
+    title="Voice-to-Voice Chatbot",
+    description="Speak into the microphone, and the chatbot will respond with speech."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)