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app.py

@@ -16,11 +16,9 @@ _client_utils.get_type = _get_type_handle_bool
 
 import librosa
 import matplotlib
+matplotlib.use("Agg")  # Non-interactive backend
 import matplotlib.pyplot as plt
 import numpy as np
-from transformers import pipeline
-
-matplotlib.use("Agg")  # Non-interactive backend
 
 # Dataset metadata
 DATASET_INFO = {
@@ -49,17 +47,17 @@ model = None
 
 
 def load_model():
-    """Lazy load the audio classification model."""
+    """Lazy load the audio classification model. Uses placeholder if transformers unavailable."""
     global model
     if model is None:
         try:
+            from transformers import pipeline
             model = pipeline(
                 "audio-classification",
                 model=MODEL_NAME,
             )
         except Exception as e:
-            print(f"Warning: Could not load model {MODEL_NAME}: {e}")
-            print("Using placeholder predictions for demo.")
+            print(f"Using placeholder predictions (no model): {e}")
             model = "placeholder"
     return model
 

requirements.txt

@@ -1,6 +1,5 @@
-gradio==4.35.0
-librosa==0.10.2
-matplotlib==3.8.2
-numpy==1.26.4
-soundfile==0.12.1
-huggingface_hub==0.19.4
+gradio>=4.35.0
+librosa>=0.10.0
+matplotlib>=3.7.0
+numpy>=1.24.0
+soundfile>=0.12.0