Create app.py

app.py

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+import gradio as gr
+import os
+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
+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" 
+# ---------------------
+
+def inference(audio_path):
+    if not audio_path:
+        return None
+
+    print("Downloading model files if missing...")
+    model_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_FILENAME)
+    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
+    separator = Separator(
+        model_file_path=model_path,
+        config_file_path=config_path,
+        output_dir=".",
+        output_format="FLAC"
+    )
+
+    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 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)
+    
+    process_btn = gr.Button("Remove Reverb")
+    process_btn.click(fn=inference, inputs=input_audio, outputs=output_audio)
+
+demo.launch()