handling labellist

app.py

@@ -66,23 +66,34 @@ def separate_stem(audio_file_path: str, model_name: str, stem_choice: str):
     stem_signal = AudioSignal(stem.cpu().numpy().astype('float32'), sample_rate=sr)
     return stem_signal
 
+
+def label_list_to_dict(label_list: LabelList) -> dict:
+    """
+    Converts a LabelList (with nested dataclasses) into a plain dictionary
+    that Gradio + OAuth schema can serialize.
+    """
+    return {
+        "meta": label_list.meta,
+        "labels": [vars(label) for label in label_list.labels]
+    }
+
 def process_fn_stem(
     audio_file_path: str,
     demucs_model: str,
     stem_choice: str,
-    request: gr.Request  # Needed for OAuth
+    request: gr.Request
 ) -> Tuple[str, Dict]:
     """
-    PyHARP process function (OAuth-safe):
-    - Separates a stem from audio using Demucs.
-    - Returns a path to the output WAV + dummy metadata.
+    OAuth-safe PyHARP process function.
+    - Separates audio into a selected stem using Demucs.
+    - Returns output WAV path + label metadata as a plain dict.
     """
 
-    # Get user's HF OAuth token if available (optional usage)
+    # Get HF user token if available (optional)
     user_token = request.headers.get("Authorization", None)
     if user_token:
         user_token = user_token.replace("Bearer ", "")
-        print(f"User is authenticated with token (truncated): {user_token[:10]}...")
+        print(f"Authenticated user token: {user_token[:10]}...")
 
     # Run stem separation
     stem_signal = separate_stem(
@@ -91,16 +102,14 @@ def process_fn_stem(
         stem_choice=stem_choice
     )
 
-    # Save output audio file
+    # Save stem output
     stem_filename = f"{stem_choice.lower().replace(' ', '_')}.wav"
     stem_path = save_audio(stem_signal, stem_filename)
 
-    # Return stem path + basic metadata (dict that Gradio can serialize)
-    return stem_path, {
-        "stem": stem_choice,
-        "model": demucs_model,
-        "auth_status": "authenticated" if user_token else "unauthenticated"
-    }
+    # Build a basic label list (you can customize this later)
+    label_list = LabelList(labels=[])
+
+    return stem_path, label_list_to_dict(label_list)
 
 
 # Define the model card
@@ -134,4 +143,4 @@ with gr.Blocks() as demo:
     )
 
 demo.queue()
-#demo.launch(show_error=True)
+demo.launch(show_error=True,share=True)

requirements.txt

@@ -15,3 +15,4 @@ numpy<2
 scipy  
 soundfile  
 hydra-core>=1.1  
+typing