Update app.py

app.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-# GhostAI Music Generator for Hugging Face Spaces
+# GhostAI Music Generator Hugging Face Spaces Version
 import os, sys, gc, time, warnings, tempfile
 import torch, torchaudio, numpy as np, gradio as gr
 from pydub import AudioSegment
@@ -8,47 +8,44 @@ from huggingface_hub import login
 
 warnings.filterwarnings("ignore")
 
-# Hugging Face token authentication
 HF_TOKEN = os.getenv("HF_TOKEN")
 if not HF_TOKEN:
     sys.exit("ERROR: HF_TOKEN not set.")
 login(HF_TOKEN)
 
-# Simple GPU check suitable for Hugging Face
 device = "cuda" if torch.cuda.is_available() else "cpu"
 print(f"Running on {device.upper()}")
 
-def clean_resources():
-    if device == "cuda":
-        torch.cuda.empty_cache()
-    gc.collect()
-
-clean_resources()
+# Fix transformers compatibility manually
+os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "max_split_size_mb:128"
 
-# Load MusicGen model explicitly on correct device
-print("Loading MusicGen 'medium' model...")
 musicgen = MusicGen.get_pretrained("medium")
 musicgen.lm.to(device)
 musicgen.set_generation_params(duration=10)
 
-# Core generation logic
+def clean_resources():
+    if device == "cuda":
+        torch.cuda.empty_cache()
+    gc.collect()
+
 def generate_music(prompt, cfg, top_k, top_p, temp, total_len, chunk_len, crossfade):
     if not prompt.strip():
         return None, "⚠️ Enter a valid prompt."
 
-    segments, sr = [], musicgen.sample_rate
+    sample_rate = musicgen.sample_rate
+    segments = []
+
     chunks = max(1, total_len // chunk_len)
-    
     for _ in range(chunks):
         with torch.no_grad():
             audio = musicgen.generate(
                 [prompt],
-                progress=False,
                 temperature=temp,
                 cfg_coef=cfg,
                 top_k=top_k,
                 top_p=top_p,
-                duration=chunk_len
+                duration=chunk_len,
+                progress=False
             )[0].cpu().float()
 
         if audio.dim() == 1:
@@ -57,14 +54,13 @@ def generate_music(prompt, cfg, top_k, top_p, temp, total_len, chunk_len, crossf
             audio = audio.repeat(2, 1)
 
         with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
-            torchaudio.save(tmp.name, audio, sr)
+            torchaudio.save(tmp.name, audio, sample_rate)
             segment = AudioSegment.from_wav(tmp.name)
         os.unlink(tmp.name)
         segments.append(segment)
 
         clean_resources()
 
-    # Concatenate audio segments
     final = segments[0]
     for seg in segments[1:]:
         final = final.append(seg, crossfade=crossfade)
@@ -74,9 +70,8 @@ def generate_music(prompt, cfg, top_k, top_p, temp, total_len, chunk_len, crossf
     out_path = "output_cleaned.mp3"
     final.export(out_path, format="mp3", bitrate="128k", tags={"title": "GhostAI Track", "artist": "GhostAI"})
 
-    return out_path, "✅ Music Generation Complete!"
+    return out_path, "✅ Done!"
 
-# Simple Gradio Interface
 demo = gr.Interface(
     fn=generate_music,
     inputs=[