app.py

import gradio as gr
import speech_recognition as sr
from pydub import AudioSegment

# Function to transcribe audio to text
def transcribe_audio(audio_input):
    recognizer = sr.Recognizer()
    audio_file = sr.AudioFile(audio_input)
    with audio_file as source:
        audio_data = recognizer.record(source)
    try:
        text = recognizer.recognize_google(audio_data)
    except sr.UnknownValueError:
        text = "Sorry, I couldn't understand the audio."
    except sr.RequestError:
        text = "Sorry, there was a problem with the request."
    return text

# Function to generate a response (you'll need to implement this)
def generate_response(user_input):
    # Placeholder for the text response generation and TTS part
    text_response = f"Responding as Tommy Vercetti: {user_input}"
    # Generate audio path based on text_response
    output_path = "response.wav"  # Placeholder path
    # Implement TTS and save to output_path
    return text_response, output_path

# Function to process the audio input and return both text and audio response
def respond(audio_input):
    user_input = transcribe_audio(audio_input)
    text_response, output_path = generate_response(user_input)

    audio = AudioSegment.from_wav(output_path)
    duration = len(audio) / 1000

    return text_response, output_path

input_audio = gr.Audio(
    sources=["microphone"],
    waveform_options=gr.WaveformOptions(
        waveform_color="#01C6FF",
        waveform_progress_color="#0066B4",
        skip_length=2,
        show_controls=False,
    ),
)

gr.Interface(
    fn=respond,
    inputs=input_audio,
    outputs=["text", "audio"],
    title="Tommy Vercetti Chatbot",
    description="Chat with Tommy Vercetti from GTA Vice City. Get responses in both text and voice!"
).launch(debug=True)