Update app.py

app.py

@@ -1,40 +1,9 @@
 import os
 from huggingface_hub import login
-import torch
-import torchaudio
-from einops import rearrange
-import gradio as gr
-from stable_audio_tools import get_pretrained_model
-from stable_audio_tools.inference.generation import generate_diffusion_cond
 
-# Authenticate using HF token from secrets
-login(token=os.getenv("HUGGINGFACE_TOKEN"), add_to_git_credential=False)
+token = os.getenv("HUGGINGFACE_TOKEN")
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model, config = get_pretrained_model("stabilityai/stable-audio-open-small")
-model = model.to(device)
-sample_rate = config["sample_rate"]
-sample_size = config["sample_size"]
+if token is None or token == "":
+    raise RuntimeError("HUGGINGFACE_TOKEN is not set or is empty.")
 
-def generate_audio(prompt):
-    conditioning = [{"prompt": prompt, "seconds_total": 11}]
-    with torch.no_grad():
-        output = generate_diffusion_cond(
-            model,
-            steps=8,
-            conditioning=conditioning,
-            sample_size=sample_size,
-            device=device
-        )
-    output = rearrange(output, "b d n -> d (b n)")
-    output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu()
-    path = "output.wav"
-    torchaudio.save(path, output, sample_rate)
-    return path
-
-gr.Interface(
-    fn=generate_audio,
-    inputs=gr.Textbox(label="Enter your sound prompt"),
-    outputs=gr.Audio(type="filepath"),
-    title="Stable Audio Generator"
-).launch()
+login(token=token, add_to_git_credential=False)