Update app.py

app.py

@@ -84,7 +84,7 @@ Semantic Search is a way to generate search results based on the actual meaning
 
 Enjoy and Search like you mean it!! 
 """
-example_queries = ["Success, rags to riches","murder, crime scene investigation thriller"]
+example_audio = [[path.as_posix()] for path in sorted(pathlib.Path('audio_examples').rglob('*.wav'))]
 
 twitter_link = """
 [![](https://img.shields.io/twitter/follow/nickmuchi?label=@nickmuchi&style=social)](https://twitter.com/nickmuchi)
@@ -99,40 +99,41 @@ h1#title {
 demo = gr.Blocks(css=css)
 
 with demo:
-    gr.Markdown(title)
-    gr.Markdown(description)
-    gr.Markdown(twitter_link)
-    
-    top_k = gr.Slider(minimum=3,maximum=10,value=5,step=1,label='Number of Suggestions to Generate')
-    
-
-    with gr.Row():
-        audio = gr.Audio(source='microphone',type='filepath',label='Audio Input: Describe the Netflix show you would like to watch..')
-        
-    with gr.Row():
-        query = gr.Textbox(label='Transcribed Text')
-        audio.change(asr,audio,query)
-            
-    with gr.Row():
-        
-        bi_output = gr.DataFrame(headers=['Similarity Score','Type','Title','Country','Description','Release Year','Rating','Duration','Category Listing','Cast'],
-        label=f'Top-{top_k} Bi-Encoder Retrieval hits', wrap=True)
-        
-    with gr.Row():
-        
-        cross_output = gr.DataFrame(headers=['Similarity Score','Type','Title','Country','Description','Release Year','Rating','Duration','Category Listing','Cast'],
-        label=f'Top-{top_k} Cross-Encoder Re-ranker hits', wrap=True)
+    with gr.Box():
+        gr.Markdown(title)
+        gr.Markdown(description)
+        gr.Markdown(twitter_link)
         
-    with gr.Row():
-        examples = gr.Examples(examples=example_queries,inputs=[query])
+        top_k = gr.Slider(minimum=3,maximum=10,value=5,step=1,label='Number of Suggestions to Generate')
         
     
-    sem_but = gr.Button('Search')
-     
+        with gr.Row():
+            audio = gr.Audio(source='microphone',type='filepath',label='Audio Input: Describe the Netflix show you would like to watch..')
             
-    sem_but.click(semantic_search,inputs=[query,top_k],outputs=[bi_output,cross_output],queue=True)
-
-    gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=nickmuchi-netflix-shows-semantic-search)")
+        with gr.Row():
+            query = gr.Textbox(label='Transcribed Text')
+            audio.change(asr,audio,query)
+                
+        with gr.Row():
+            
+            bi_output = gr.DataFrame(headers=['Similarity Score','Type','Title','Country','Description','Release Year','Rating','Duration','Category Listing','Cast'],
+            label=f'Top-{top_k} Bi-Encoder Retrieval hits', wrap=True)
+            
+        with gr.Row():
+            
+            cross_output = gr.DataFrame(headers=['Similarity Score','Type','Title','Country','Description','Release Year','Rating','Duration','Category Listing','Cast'],
+            label=f'Top-{top_k} Cross-Encoder Re-ranker hits', wrap=True)
+            
+        with gr.Row():
+            examples = gr.Examples(examples=example_audio,inputs=[query])
+            
+        
+        sem_but = gr.Button('Search')
+         
+                
+        sem_but.click(semantic_search,inputs=[query,top_k],outputs=[bi_output,cross_output],queue=True)
+    
+        gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=nickmuchi-netflix-shows-semantic-search)")
 
     
 demo.launch(debug=True,enable_queue=True)