Update app.py

app.py

@@ -910,22 +910,39 @@ custom_css = """
 # Create the Gradio interface with proper output handling
 with gr.Blocks(title="Affective Virtual Environments - Chunked Processing", css=custom_css) as interface:
     gr.Markdown("# The Emotional Machine")
+    gr.Markdown(
+        """
+        An Affective Virtual Environment or AVE is a digital space composed of two components: An emotion recognition system and a virtual environment generator.
     
+        In this project, we use bimodal speech emotion recognition to predict categorical emotions from semantic and acoustic modes.
+    
+        Virtual Environments are generated using deepAI and MusicGEN.
+    
+        To interact, record your voice or upload an audio file. Define the length to Chunk your sample, and if you want to generate Audio for each chunk or not.
+    
+        Generate your Affective Virtual Environment and wait for the results.
+    
+        Download the HTML file with your creation.
+        """
+    )
+
+
+
     
     with gr.Row():
         with gr.Column(scale=2):
             audio_input = gr.Audio(label="Input Audio", type="filepath", sources=["microphone", "upload"])
             
             # Add example audio selection
-            example_selector = gr.Dropdown(
-                label="Select Example Audio",
-                choices=["Happy Speech", "Sad Story", "Neutral News"],
-                value=None,
-                info="Choose from pre-recorded example speeches"
-            )
+           # example_selector = gr.Dropdown(
+           #     label="Select Example Audio",
+           #     choices=["Happy Speech", "Sad Story", "Neutral News"],
+           #     value=None,
+           #     info="Choose from pre-recorded example speeches"
+           # )
             
             # Add button to load selected example
-            load_example_btn = gr.Button("Load Example", variant="secondary")
+            #load_example_btn = gr.Button("Load Example", variant="secondary")
         
         with gr.Column(scale=1):
             # Add chunk duration input
@@ -1045,14 +1062,14 @@ with gr.Blocks(title="Affective Virtual Environments - Chunked Processing", css=
             container['image'],
             container['image_360'],
             container['music']
-        ]] + [loading_indicator, chunk_duration_input, example_selector, viewer_html_output, js_output]
+        ]] + [loading_indicator, chunk_duration_input, viewer_html_output, js_output]
     )
     
-    load_example_btn.click(
-        fn=load_example,
-        inputs=[example_selector],
-        outputs=[audio_input, example_selector]
-    )
+    #load_example_btn.click(
+    #    fn=load_example,
+    #    inputs=[example_selector],
+    #    outputs=[audio_input, example_selector]
+    #)
     
     # Check if we're running on Hugging Face Spaces
     is_spaces = os.getenv('SPACE_ID') is not None