Update app.py

app.py

@@ -26,12 +26,12 @@ def user_query_recommend(query, price_rng):
     # Recommend
     recommendations = reviews.copy()
     recommendations['sim'] = sim_scores.T
-    if price_rng == "$0-$50":
-        min_p, max_p = 0, 50
-    if price_rng == "$50-$100":
-        min_p, max_p = 50, 100
-    if price_rng == "$100+":
-        min_p, max_p = 100, 10000
+    if price_rng == "$0-$70":
+        min_p, max_p = 0, 70
+    if price_rng == "$70-$150":
+        min_p, max_p = 70, 150
+    if price_rng == "$150+":
+        min_p, max_p = 150, 10000
         
     op=recommendations\
             .groupby("name")\
@@ -45,13 +45,13 @@ def user_query_recommend(query, price_rng):
 
     op = op.sort_values('sim',ascending=False).loc[(op.price >= min_p) & (op.price <= max_p), ['name', 'price', 'description_sent']]
 
-    return op.reset_index(drop=True).head(5)
+    return op.reset_index(drop=True).head(6)
     
 interface = gr.Interface(
     user_query_recommend, 
     inputs=[gr.inputs.Textbox(lines=5, label = "enter flavour profile"),
             gr.inputs.Radio(choices = ["$0-$50", "$50-$100", "$100+"], default="$0-$50", type="value", label='Price range')],
-    outputs=gr.outputs.Dataframe(max_rows=1, overflow_row_behaviour="paginate", type="pandas", label="Scotch recommendations"),
+    outputs=gr.outputs.Dataframe(max_rows=3, overflow_row_behaviour="paginate", type="pandas", label="Scotch recommendations"),
     title = "Scotch Recommendation",
     description = "Looking for scotch recommendations and have some flavours in mind? \nGet recommendations at a preferred price range using semantic search :) ",
     examples=[["very sweet with lemons and oranges and marmalades", "$0-$50"],