import torch import torchaudio from einops import rearrange import gradio as gr import spaces import os import uuid # Importing the model-related functions from stable_audio_tools import get_pretrained_model from stable_audio_tools.inference.generation import generate_diffusion_cond # Function to set up, generate, and process the audio @spaces.GPU(duration=120) # Allocate GPU only when this function is called def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7): device = "cuda" if torch.cuda.is_available() else "cpu" # Fetch the Hugging Face token from the environment variable hf_token = os.getenv('HF_TOKEN') if not hf_token: raise EnvironmentError("HF_TOKEN environment variable not set") # Download and set up the model model, model_config = get_pretrained_model("stabilityai/stable-audio-open-1.0", use_auth_token=hf_token) sample_rate = model_config["sample_rate"] sample_size = model_config["sample_size"] model = model.to(device) # Set up text and timing conditioning conditioning = [{ "prompt": prompt, "seconds_start": 0, "seconds_total": seconds_total }] # Generate stereo audio output = generate_diffusion_cond( model, steps=steps, cfg_scale=cfg_scale, conditioning=conditioning, sample_size=sample_size, sigma_min=0.3, sigma_max=500, sampler_type="dpmpp-3m-sde", device=device ) # Rearrange audio batch to a single sequence output = rearrange(output, "b d n -> d (b n)") # Peak normalize, clip, convert to int16 output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu() # Generate a unique filename for the output unique_filename = f"output_{uuid.uuid4().hex}.wav" # Save to file torchaudio.save(unique_filename, output, sample_rate) # Return the path to the generated audio file return unique_filename # Setting up the Gradio Interface interface = gr.Interface( fn=generate_audio, inputs=[ gr.Textbox(label="Prompt", placeholder="Enter your text prompt here"), gr.Slider(0, 47, value=30, label="Duration in Seconds"), gr.Slider(10, 300, value=100, step=10, label="Number of Diffusion Steps"), gr.Slider(1, 15, value=7, step=0.1, label="CFG Scale") ], outputs=gr.Audio(type="filepath", label="Generated Audio"), title="Stable Audio Generator", description="Generate variable-length stereo audio at 44.1kHz from text prompts using Stable Audio Open 1.0." ) # Launch the Interface interface.launch()