Update app.py

app.py

@@ -29,20 +29,23 @@ def user_query_recommend(query, min_p, max_p):
     recommendations = recommendations.sort_values('sim', ascending=False)
     recommendations = recommendations.loc[(recommendations.price >= min_p) &
                                           (recommendations.price <= max_p),
-                                          ['name', 'price', 'description']].head(3)
+                                          ['name', 'price', 'description']].head(10)
 
     return recommendations.reset_index(drop=True)
     
 interface = gr.Interface(
     user_query_recommend, 
-    inputs=[gr.inputs.Textbox(),
+    inputs=[gr.inputs.Textbox(lines=5),
             gr.inputs.Slider(minimum=1, maximum=100, default=30, label='Min Price'),
             gr.inputs.Slider(minimum=1, maximum=1000, default=70, label='Max Price')],
-    outputs="dataframe",
+    outputs=gr.outputs.Dataframe(max_rows=3, overflow_row_behaviour="paginate", type="pandas", label="Recommendations"),
     title = "Scotch Recommendation",
-    examples=[["very sweet with lemons and oranges and marmalades", 20,50], 
-              ["smoky peaty earthy and spicy",50,100]],
-    theme="huggingface",
+    description = "Looking for scotch recommendations and have some flavours in mind? Get recommendations using semantic search through distilRoberta embeddings at a preferred price range :) ",
+    examples=[["very sweet with lemons and oranges and marmalades", 10,40], 
+              ["smoky peaty earthy and spicy",50,100],
+              ["salty and spicy with exotic fruits", 50,500], 
+              ],
+    theme="grass",
 )
 
 interface.launch(