Update app.py

app.py

@@ -15,7 +15,7 @@ embedding_table = cache_data["embeddings"]
 reviews = cache_data["data"]
 reviews['price'] = reviews.price.apply(lambda x: re.findall("\d+", x.replace(",","").replace(".00","").replace("$",""))[0]).astype('int')
 
-def user_query_recommend(query, min_p, max_p):
+def user_query_recommend(query, price_rng):
     # Embed user query
     embedding = model.encode(query)
 
@@ -27,20 +27,23 @@ def user_query_recommend(query, min_p, max_p):
     recommendations = reviews.copy()
     recommendations['sim'] = sim_scores.T
     recommendations = recommendations.sort_values('sim', ascending=False)
-    if max_p < min_p:
-        min_p = 0
+    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
     recommendations = recommendations.loc[(recommendations.price >= min_p) &
                                           (recommendations.price <= max_p),
-                                          ['name', 'price', 'description']].head(10)
+                                          ['name', 'price', 'description']].head(5)
 
     return recommendations.reset_index(drop=True)
     
 interface = gr.Interface(
     user_query_recommend, 
     inputs=[gr.inputs.Textbox(lines=5, label = "enter flavour profile"),
-            gr.inputs.Slider(minimum=10, maximum=1000, default=30, label='Min. Price'),
-            gr.inputs.Slider(minimum=30, maximum=1000, default=70, label='Max. Price')],
-    outputs=gr.outputs.Dataframe(max_rows=3, overflow_row_behaviour="paginate", type="pandas", label="Scotch recommendations"),
+            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"),
     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", 10,40],