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import gradio as gr
import os
import shutil
import spaces
import sys
# we will clone the repo and install the dependencies
# NOTE: Still fixing bugs, not release, do not try :) !
# os.system('pip install -r qa_mdt/requirements.txt')
# os.system('pip install xformers==0.0.26.post1')
# os.system('pip install torchlibrosa==0.0.9 librosa==0.9.2')
# os.system('pip install -q pytorch_lightning==2.1.3 torchlibrosa==0.0.9 librosa==0.9.2 ftfy==6.1.1 braceexpand')
# os.system('pip install torch==2.3.0+cu121 torchvision==0.18.0+cu121 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu121')
# only then import the necessary modules from qa_mdt
from qa_mdt.pipeline import MOSDiffusionPipeline
pipe = MOSDiffusionPipeline()
# this runs the pipeline with user input and saves the output as 'awesome.wav'
@spaces.GPU(duration=120)
def generate_waveform(description):
high_quality_description = "high quality " + description
pipe(high_quality_description)
generated_file_path = "./awesome.wav"
# if os.path.exists(generated_file_path):
# return generated_file_path
# else:
# return "Error: Failed to generate the waveform."
if os.path.exists(generated_file_path):
waveform_video = gr.make_waveform(audio=generated_file_path, bg_color="#000000", bars_color="#00FF00", bar_count=100, bar_width=1.5, animate=True)
return waveform_video, generated_file_path
else:
return "Error: Failed to generate the waveform."
intro = """
# 🎶 OpenMusic: Diffusion That Plays Music 🎧 🎹
Welcome to **OpenMusic**, a next-gen diffusion model designed to generate high-quality music audio from text descriptions!
Simply enter a few words describing the vibe, and watch as the model generates a unique track for your input.
Powered by the QA-MDT model, based on the new research paper linked below.
- [GitHub Repo](https://github.com/ivcylc/qa-mdt) by [@changli](https://github.com/ivcylc) 🎓.
- [Paper](https://arxiv.org/pdf/2405.15863) & [Paper Demo](https://qa-mdt.github.io/ )
- [HuggingFace](https://huggingface.co/jadechoghari/qa_mdt) [@jadechoghari](https://github.com/jadechoghari) 🤗.
Note: The music generation process will take 1-2 minutes 🎶
---
"""
# gradio interface
iface = gr.Interface(
fn=generate_waveform,
inputs=gr.Textbox(lines=2, placeholder="Enter a music description here..."),
# outputs=gr.Audio(label="Download the Music 🎼"),
outputs=[gr.Video(label="Watch the Waveform 🎼"), gr.Audio(label="Download the Music 🎶")],
description=intro,
examples=[
["A modern synthesizer creating futuristic soundscapes."],
["Acoustic ballad with heartfelt lyrics and soft piano."]
],
cache_examples="lazy"
# cache_examples=True
)
# Launch the Gradio app
if __name__ == "__main__":
iface.launch()
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