Update app.py

Download the pretrained model from huggingface

app.py

@@ -8,20 +8,24 @@ import numpy as np
 import soundfile as sf
 import gradio as gr
 import time
+from huggingface_hub import snapshot_download
+
+repo_id = "amphion/anyaccomp"
+local_dir = "anyaccomp_model"
+
+print(f"Downloading model files from {repo_id}...")
+model_dir = snapshot_download(repo_id=repo_id, local_dir=local_dir)
+print(f"Model files downloaded to: {model_dir}")
+
+CFG_PATH = os.path.join(model_dir, "config/flow_matching.json")
+CHECKPOINT_PATH = os.path.join(model_dir, "pretrained/flow_matching")
+VOCODER_CHECKPOINT_PATH = os.path.join(model_dir, "pretrained/vocoder")
+VOCODER_CFG_PATH = os.path.join(model_dir, "config/vocoder.json")
+
+base_dir = os.path.dirname(os.path.abspath(__file__))
+INFER_DST = os.path.join(base_dir, "output_gradio")
+EXAMPLE_DIR = os.path.join(base_dir, "example/gradio")
 
-base_dir = os.path.dirname(
-    os.path.abspath(__file__)
-)
-
-CFG_PATH = os.path.join(base_dir, "./config/flow_matching.json")
-CHECKPOINT_PATH = os.path.join(
-    base_dir, "./pretrained/flow_matching"
-)
-VOCODER_CHECKPOINT_PATH = os.path.join(
-    base_dir, "./pretrained/vocoder"
-)
-VOCODER_CFG_PATH = os.path.join(base_dir, "./config/vocoder.json")
-INFER_DST = os.path.join(base_dir, "./example/output_gradio")
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
 os.makedirs(INFER_DST, exist_ok=True)
@@ -135,15 +139,10 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                 sources=["upload", "microphone"],
             )
 
-            example1_path = os.path.join(
-                base_dir, "./example/gradio/example1.mp3"
-            )
-            example2_path = os.path.join(
-                base_dir, "./example/gradio/example2.wav"
-            )
-            example3_path = os.path.join(
-                base_dir, "./example/gradio/example3.wav"
-            )
+            example1_path = os.path.join(EXAMPLE_DIR, "example1.mp3")
+            example2_path = os.path.join(EXAMPLE_DIR, "example2.wav")
+            example3_path = os.path.join(EXAMPLE_DIR, "example3.wav")
+            
             gr.Examples(
                 examples=[[example1_path], [example2_path], [example3_path]],
                 inputs=[vocal_input],
@@ -185,13 +184,11 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     submit_btn.click(
         fn=sing2song_inference,
         inputs=[vocal_input, n_timesteps_slider, cfg_slider, seed_input],
-        # The function will now update the status text as its third output
         outputs=[accompaniment_output, mixture_output, status_text],
     )
 
     random_seed_btn.click(fn=randomize_seed, inputs=None, outputs=seed_input)
 
-demo.queue()
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=8091)
+    demo.launch()