return only dict

app.py

@@ -71,48 +71,57 @@ def generate_dummy_metadata(stem_choice: str, username: str) -> Dict:
         "labels": [vars(label) for label in label_list.labels]
     }
 
-
 def process_fn_stem(
     audio_file_path: str,
     demucs_model: str,
     stem_choice: str,
     profile: gr.OAuthProfile | None = None
-) -> tuple:
+) -> dict:
+    # Get user info
     username = profile.username if profile else "anonymous"
-    print(f"Processing for user: {username}")
 
+    # Separate stem
     stem_signal = separate_stem(audio_file_path, model_name=demucs_model, stem_choice=stem_choice)
+
+    # Save output
     stem_filename = f"{stem_choice.lower().replace(' ', '_')}.wav"
     stem_path = save_audio(stem_signal, stem_filename)
 
-    metadata = generate_dummy_metadata(stem_choice, username)
-    return stem_path, metadata
+    # Return flat dict with primitive types only
+    return {
+        "stem_file": stem_path,
+        "stem": stem_choice,
+        "user": username,
+        "timestamp": 0.0,
+        "amplitude": 0.7,
+        "description": f"Start of {stem_choice}"
+    }
 
 
-# Gradio Interface
-
 
+# Gradio Interface
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# 🎧 Demucs Stem Separator")
-    gr.Markdown("Sign in with your Hugging Face account to use this tool.")
+    gr.Markdown("Log in with your Hugging Face account to separate stems from audio files.")
 
     gr.LoginButton()
 
-    with gr.Row():
-        model_dropdown = gr.Dropdown(label="Select Demucs Model", choices=DEMUX_MODELS, value="mdx_extra_q")
-        stem_dropdown = gr.Dropdown(label="Select Stem", choices=list(STEM_CHOICES.keys()), value="Vocals")
-
+    model_dropdown = gr.Dropdown(label="Select Demucs Model", choices=DEMUX_MODELS, value="mdx_extra_q")
+    stem_dropdown = gr.Dropdown(label="Select Stem", choices=list(STEM_CHOICES.keys()), value="Vocals")
     audio_input = gr.Audio(label="Upload Audio", type="filepath")
-    stem_output = gr.File(label="Separated Stem (.wav)")
-    metadata_output = gr.JSON(label="Separation Metadata")
+    output_file = gr.File(label="Separated Stem File (.wav)")
+    output_json = gr.JSON(label="Metadata")
 
-    run_button = gr.Button("Separate Stem")
+    run_button = gr.Button("Run Separation")
 
     run_button.click(
         fn=process_fn_stem,
         inputs=[audio_input, model_dropdown, stem_dropdown],
-        outputs=[stem_output, metadata_output]
+        outputs=[output_file, output_json]
     )
 
-demo.queue()
-demo.launch()
+    demo.queue()
+
+# Launch the app
+demo.launch(show_error=True)