Update app.py

app.py

@@ -68,7 +68,7 @@ def predict(text, model, human_readable=True):
         if not human_readable:
             answer.append(result[index][1])
         else:
-            answer.append(labels_description[result[index][1]] + " {:.2f}%".format(100 * result[index][0]))
+            answer.append(labels_description[result[index][1]] + " - {:.2f}%".format(100 * result[index][0]))
         index += 1
 
     return answer
@@ -78,17 +78,27 @@ tokenizer = DistilBertTokenizer.from_pretrained(vocab_path)
 model = torch.load(model_path, map_location=torch.device(device))
 
 st.markdown("### Hi! This is a service for determining the subject of an article.")
-st.image(img)
-st.markdown("### Just write the title and content in the areas below and click the \"Analyze\" button.")
+st.markdown("It can predict the following topics:\n"
+            "* Computer Science\n"
+            "* Economics\n"
+            "* Electrical Engineering and Systems Science\n"
+            "* Mathematics\n"
+            "* Physics\n"
+            "* Quantitative Biology\n"
+            "* Quantitative Finance\n"
+            "* Statistics\n")
+st.markdown("#### Just write the title and abstract in the areas below and click the \"Analyze\" button.")
 
-text1 = st.text_area("Title")
+title = st.text_area("Title")
 
-text2 = st.text_area("Summary")
+abstract = st.text_area("Abstract")
 
 if st.button('Analyse'):
     with st.spinner("Wait..."):
-        if text1 or text2:
-                pred = predict(text1+"\n"+text2, model.to(device))
-                st.success("\n\n".join(pred))
+        if not title and not abstract:
+            st.error(f"You haven't written anything.")
+        elif not title:
+            st.error(f"You haven't written a title.")
         else:
-            st.error(f"You haven't written anything.")
+            pred = predict(title+"\n"+abstract, model.to(device))
+            st.success("\n\n".join(pred))