Added design to the outputs

app.py

@@ -29,7 +29,7 @@ def str_to_numpy(array_string):
 
 @st.cache_data  # 👈 Add the caching decorator
 def load_data():
-    vectors_df = pd.read_csv('restaurants_dataframe_with_embeddings.csv')
+    vectors_df = pd.read_csv('restaurants_dataframe_with_embeddings.csv',  encoding="utf-8")
     embeds = dict(enumerate(vectors_df['Embeddings']))
     rest_names = list(vectors_df['Names'])
     vectors_df['Weights'] = [1]*len(vectors_df)
@@ -40,18 +40,6 @@ restaurants_embeds, rest_names, init_df = load_data()
 
 model, tokenizer = get_models()
 
-# query_params = st.experimental_get_query_params()
-# st.write("query_params")
-# st.write(query_params)
-
-# def update_params():
-#     st.experimental_set_query_params(
-#         sorting=st.session_state.sort_by)
-
-# if query_params:        
-#     sort_by = query_params["sorting"][0]
-#     st.session_state.sort_by = sort_by
-
 #a function that takes a sentence and converts it into embeddings
 def get_bert_embeddings(sentence, model, tokenizer):
     inputs = tokenizer(sentence, return_tensors="pt", padding=True, truncation=True)
@@ -233,6 +221,28 @@ st.title("GoTogether!")
 st.markdown("Tell us about your preferences!")
 st.caption("In section 'Others', you can describe any wishes.")
 
+
+# Define custom CSS styles for the orange and blue rectangles
+css = """
+<style>
+    .orange-box {
+        background-color: orange;
+        border: 2px solid darkred;
+        border-radius: 10px;
+        display: inline-block;
+        padding: 5px 10px;
+    }
+    
+    .blue-box {
+        background-color: lightblue;
+        border: 2px solid navy;
+        border-radius: 10px;
+        display: inline-block;
+        padding: 5px 10px;
+    }
+</style>
+"""
+
 # options_disability_1 = st.multiselect(
 #      'Do you need a wheelchair?',
 #      ['Yes', 'No'], ['No'], key=101)
@@ -280,7 +290,7 @@ if ambiance_2 == 'Other':
 
 options_food_2 = st.multiselect(
     'Do you have any dietary restrictions?',
-    ['Vegan', 'Vegetarian', 'Halal', 'Other'], key=7)
+    ['Vegan', 'Vegetarian', 'Halal'], key=7)
 
 additional_2 = st.text_input(label="Your description", placeholder="Anything else you wanna share?", key=8) 
      
@@ -334,18 +344,45 @@ if submit or (not st.session_state.precalculated_df.empty):
             k = 10
             st.write(f"Here are the best {k} matches to your preferences:")
             i = 1
+            nums = list(range(1, 11))
+            words = ['one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine', 'one: :zero']
+            nums_emojis = dict(zip(nums, words))
             for name, score in results.items():
-                st.write("Top", i, ':', name, score)
+                
                 condition = st.session_state.precalculated_df['Names'] == name
+                rating = st.session_state.precalculated_df.loc[condition, 'Rating'].values[0]
+                st.write(f":{nums_emojis[i]}: **{name}** **({str(rating)}**:star:) :", 'match score:', score)
+    
                 # Use the condition to extract the value(s)
-                description = st.session_state.precalculated_df.loc[condition, 'Strings']
-                st.write(description)
-                i+=1
+                # description = st.session_state.precalculated_df.loc[condition, 'Strings']
+                # st.write(description)
+                
+                type = [item for item in eval(st.session_state.precalculated_df.loc[condition, 'Category'].values[0])]
+                # Display HTML with the custom styles
+                for word in type:
+                    st.markdown(css, unsafe_allow_html=True)
+                    st.markdown(f'<div class="blue-box">{word}</div>', unsafe_allow_html=True)
+                # st.write("Restaurant type:", str(type))
+                
+                keywords = [item[0] for item in eval(st.session_state.precalculated_df.loc[condition, 'Keywords'].values[0])]
+                for pair in keywords[:3]:
+                    st.markdown(css, unsafe_allow_html=True)
+                    st.markdown(f'<div class="orange-box">{pair[0]} {pair[1]}</div>', unsafe_allow_html=True)
+                # st.write("Restaurant type:", str(type))
+                
+                
+                url = st.session_state.precalculated_df.loc[condition, 'URL'].values[0]
+                st.write("_Check on the map:_", url)
+                            
+                # st.markdown("This is a text with <span style='font-size: 20px;'>bigger</span> and <i>italic</i> text.", unsafe_allow_html=True)
+                # st.markdown("<span style='font-size: 24px;'>This is larger text</span>", unsafe_allow_html=True)
+
         
 
         
 stop = st.button("New search!", type='primary', key=500)  
 if stop:               
+    st.write("New search is launched. Please specify your preferences in the form!")
     st.session_state.preferences_1, st.session_state.preferences_2 = [], []
     st.session_state.restrictions = []
     st.session_state.sort_by = ""