Update app.py

app.py

@@ -4,15 +4,9 @@ from huggingface_hub import hf_hub_download
 from audio_separator.separator import Separator
 
 # --- Configuration ---
-# REPO_ID: The repository containing the model weights
 REPO_ID = "anvuew/dereverb_room"
-
-# MODEL_FILENAME: specific .ckpt or .pth file in that repo
-# IMPORTANT: Check the repo and replace this with the actual filename
+# Filenames taken from your logs
 MODEL_FILENAME = "dereverb_room_anvuew_sdr_13.7432.ckpt" 
-
-# CONFIG_FILENAME: specific .yaml file in that repo
-# IMPORTANT: Check the repo and replace this with the actual filename
 CONFIG_FILENAME = "dereverb_room_anvuew.yaml" 
 # ---------------------
 
@@ -25,28 +19,25 @@ def inference(audio_path):
     config_path = hf_hub_download(repo_id=REPO_ID, filename=CONFIG_FILENAME)
 
     print("Initializing separator...")
-    # Initialize the separator with the specifically downloaded model and config
+    # Initialize WITHOUT model paths first
     separator = Separator(
-        model_file_path=model_path,
-        config_file_path=config_path,
         output_dir=".",
         output_format="FLAC"
     )
 
+    print(f"Loading model: {MODEL_FILENAME}...")
+    # Load the specific model and config using their absolute downloaded paths
+    separator.load_model(model_filename=model_path, config_filename=config_path)
+
     print("Starting inference...")
-    # The model works by separating 'reverb' from the audio. 
-    # We want the audio *without* reverb, which is usually the primary stem.
     output_files = separator.separate(audio_path)
     
     print(f"Separation complete. Outputs: {output_files}")
-    # Return the first output file (usually the dereverbed/clean audio)
+    # Return the first output file
     return output_files[0]
 
-# Create Gradio Interface
 with gr.Blocks(title="Dereverb Room Web UI") as demo:
     gr.Markdown("# Dereverb Room Inference")
-    gr.Markdown(f"Inference using model from [{REPO_ID}](https://huggingface.co/{REPO_ID})")
-    
     with gr.Row():
         input_audio = gr.Audio(label="Upload Audio", type="filepath")
         output_audio = gr.Audio(label="Dereverbed Audio", type="filepath", interactive=False)