Bring the Space up to the pyharp example standard (taxonomy tags, __main__ guard, show_error, v0.4.0)

README.md

@@ -4,7 +4,7 @@ emoji: ✂️
 colorFrom: pink
 colorTo: red
 sdk: gradio
-sdk_version: 5.28.0
+sdk_version: 6.24.0
 python_version: '3.13'
 app_file: app.py
 pinned: false

app.py

@@ -11,7 +11,7 @@ import librosa
 import torch
 import soundfile as sf
 from huggingface_hub import hf_hub_download
-from pyharp import ModelCard, build_endpoint
+from pyharp import ModelCard, build_endpoint, Subcategory
 
 from models.resunet import ResUNet30
 from models.clap_encoder import CLAP_Encoder
@@ -69,7 +69,7 @@ model_card = ModelCard(
     name="AudioSep",
     description="Separate any sound from a mixture using a natural language text description.",
     author="Xubo Liu, Qiuqiang Kong, Yan Zhao, Haohe Liu, Yi Yuan, Yuzhuo Liu, Rui Xia, Yuxuan Wang, Mark D. Plumbley, Wenwu Wang",
-    tags=["audio separation", "text-queried", "source separation"],
+    tags=[Subcategory.TARGET_SOURCE_EXTRACTION, 'audio separation', 'text-queried', 'source separation'],
 )
 
 
@@ -108,22 +108,23 @@ def process_fn(audio_path: str, text_query: str):
     return out_path
 
 
-with gr.Blocks() as demo:
-    input_components = [
-        gr.Audio(type="filepath", label="Input Audio (Mixture)").harp_required(True),
-        gr.Textbox(label="Text Query", placeholder="e.g. a dog barking"),
-    ]
-    output_components = [
-        gr.Audio(type="filepath", label="Separated Audio").set_info(
-            "Separated audio at 32 kHz matching the text description."
-        ),
-    ]
-
-    build_endpoint(
-        model_card=model_card,
-        input_components=input_components,
-        output_components=output_components,
-        process_fn=process_fn,
-    )
+if __name__ == "__main__":
+    with gr.Blocks() as demo:
+        input_components = [
+            gr.Audio(type="filepath", label="Input Audio (Mixture)").harp_required(True),
+            gr.Textbox(label="Text Query", placeholder="e.g. a dog barking"),
+        ]
+        output_components = [
+            gr.Audio(type="filepath", label="Separated Audio").set_info(
+                "Separated audio at 32 kHz matching the text description."
+            ),
+        ]
+
+        build_endpoint(
+            model_card=model_card,
+            input_components=input_components,
+            output_components=output_components,
+            process_fn=process_fn,
+        )
 
-demo.queue().launch()
+    demo.queue().launch(pwa=True, show_error=True, share=True)

requirements.txt

@@ -1,4 +1,4 @@
-git+https://github.com/TEAMuP-dev/pyharp.git@v0.3.0
+git+https://github.com/TEAMuP-dev/pyharp.git@v0.4.0
 torch==2.6.0
 torchaudio==2.6.0
 torchvision==0.21.0
@@ -9,3 +9,4 @@ ftfy
 braceexpand
 torchlibrosa
 huggingface_hub
+spaces>=0.51.1