Update app.py

app.py

@@ -11,9 +11,12 @@ from transformers import (
 from huggingface_hub import snapshot_download, login
 
 # ----------------- Hugging Face Authentication -----------------
-HF_TOKEN = "YOUR_HUGGINGFACE_TOKEN_HERE"  # 🔐 Replace with your real token
-login(token=HF_TOKEN)
-print("🔑 Logged into Hugging Face successfully.")
+HF_TOKEN = os.getenv("HF_TOKEN")  # ✅ Read securely from environment variable
+if HF_TOKEN:
+    login(token=HF_TOKEN)
+    print("🔑 Logged into Hugging Face successfully.")
+else:
+    print("⚠️ No Hugging Face token found. Please set it in your environment variables.")
 
 # ----------------- Basic Environment Setup -----------------
 print("🔧 Initializing environment (CPU mode)...")
@@ -27,11 +30,8 @@ device = "cpu"
 
 # ----------------- Model Download -----------------
 folder_path = './xcodec_mini_infer'
-if not os.path.exists(folder_path):
-    os.mkdir(folder_path)
-    print(f"📦 Folder created: {folder_path}")
-else:
-    print(f"📦 Folder already exists: {folder_path}")
+os.makedirs(folder_path, exist_ok=True)
+print(f"📦 Folder ready: {folder_path}")
 
 snapshot_download(
     repo_id="m-a-p/xcodec_mini_infer",
@@ -47,11 +47,10 @@ from mmtokenizer import _MMSentencePieceTokenizer
 from models.soundstream_hubert_new import SoundStream
 
 # ----------------- Load YuE Model -----------------
-print("🧠 Loading YuE model on CPU (8-bit)...")
-
+print("🧠 Loading YuE model on CPU (small version)...")
 try:
     model = AutoModelForCausalLM.from_pretrained(
-        "m-a-p/YuE-s1-1B-mini-en-cot",  # ✅ smaller model for CPU
+        "m-a-p/YuE-s1-1B-mini-en-cot",
         torch_dtype=torch.float32,
         attn_implementation="eager",
         low_cpu_mem_usage=True,
@@ -66,7 +65,6 @@ except Exception as e:
 
 # ----------------- Load Codec -----------------
 print("🎧 Loading codec model...")
-
 basic_model_config = './xcodec_mini_infer/final_ckpt/config.yaml'
 resume_path = './xcodec_mini_infer/final_ckpt/ckpt_00100000.pth'