app.py

from transformers import AutoProcessor, MusicgenForConditionalGeneration
import scipy
import streamlit as st

BASE_MODEL = "facebook/musicgen-small"


processor = AutoProcessor.from_pretrained(BASE_MODEL)
model = MusicgenForConditionalGeneration.from_pretrained(BASE_MODEL)

def generate_audio(text):
    inputs = processor(
        text=[text],
        padding=True,
        return_tensors="pt",
    )
    audio_values = model.generate(**inputs, do_sample=True, guidance_scale=3, max_new_tokens=256)
    cleaned_text = text.replace(" ", "_")
    sampling_rate = model.config.audio_encoder.sampling_rate
    scipy.io.wavfile.write(f'${cleaned_text}.wav', rate=sampling_rate, data=audio_values[0, 0].numpy())
    return f'${cleaned_text}.wav'

# Streamlit app title and description
st.title("Text-to-Audio Generation")

# User input for text prompt
text = st.text_area("Enter Text Prompt:")

# Generate audio when the user clicks the button
if st.button("Generate Audio"):
    if text:
        # Generate audio using the ModelManager
        audio_file_path = generate_audio(text)

        # Display the audio player
        audio_data = open(audio_file_path, "rb").read()
        st.audio(audio_data, format="audio/wav")

        # Provide a download link for the audio file
        st.write("Audio Generated Successfully!")
        st.success(f"Download the audio file [here](/{audio_file_path}).")
    else:
        st.warning("Please enter a text prompt.")