Update app.py

app.py

@@ -112,11 +112,13 @@ def get_strange(n=4):
         labels = st.session_state.labels
         preds = pd.Series(st.session_state.preds,index=embeddings.index).loc[labels.index].rename('pred')
         data = pd.concat([labels, preds],axis=1)
-        
+        st.toast(data.columns)
         
         data['diff'] = data['pred'] - data['label']
-        data = data.sort_values('diff')['diff']
-        return data.iloc[:n].to_dict(),data.iloc[-n:].to_dict() 
+        data = data.sort_values('diff',ascending=False)['diff'] 
+        surprising_dislikes = data.iloc[:n].to_dict()
+        surprising_likes = data.iloc[-n:].to_dict()
+        return surprising_dislikes,surprising_likes
         
         
 
@@ -160,18 +162,18 @@ if st.session_state.name:
 
         cc1.subheader('Where you confused me')
 
-        best,worst = get_strange()
+        surprising_dislikes,surprising_likes = get_strange()
         
         cc1.write("You didn't like my picks")
-        cs = cc1.columns(len(best))
-        for c,(file,pred) in zip(cs,best.items()):
-            c.metric("", "",f'{pred:.0%}')
+        cs = cc1.columns(len(surprising_dislikes))
+        for c,(file,pred) in zip(cs,surprising_dislikes.items()):
+            c.metric("", "",f'{-pred:.0%}')
             c.image(get_s3_url(file), width = 100)
 
         cc1.write("You liked these more than I thought")
-        cs = cc1.columns(len(worst))
-        for c,(file,pred) in zip(cs,worst.items()):
-            c.metric("","", f'{pred:.0%}')
+        cs = cc1.columns(len(surprising_likes))
+        for c,(file,pred) in zip(cs,surprising_likes.items()):
+            c.metric("","", f'{-pred:.0%}')
             c.image(get_s3_url(file), width = 100)