Update app.py

app.py

@@ -2,15 +2,19 @@ import streamlit as st
 from sentence_transformers.util import cos_sim
 from sentence_transformers import SentenceTransformer
 
+def process(sent1, sent2):
+  if sent1 and sent2:
+    encodings = model.encode([sent1, sent2])
+    sim = cos_sim(encodings[0], encodings[1]).numpy().tolist()[0][0]
+    st.write('Cosine Similarity: {0:.4f}'.format(sim))
+
 st.title("Sentence Embedding for Spanish with Bertin")
 st.write("Sentence embedding for spanish trained on NLI. Used for Sentence Textual Similarity.")
+model = SentenceTransformer('hackathon-pln-es/bertin-roberta-base-finetuning-esnli')
 
-sent1 = st.text_area('Enter sentence 1 ...')
-sent2 = st.text_area('Enter sentence 2 ...')
+sent1 = st.text_area('Enter sentence 1')
+sent2 = st.text_area('Enter sentence 2')
+
+st.button('Compute similarity', key=None, help=None, on_click=process, args=(sent1, sent2))
 
-model = SentenceTransformer('hackathon-pln-es/bertin-roberta-base-finetuning-esnli')
 
-if sent1 and sent2:
-  encodings = model.encode([sent1, sent2])
-  sim = cos_sim(encodings[0], encodings[1]).numpy().tolist()[0][0]
-  st.write('Cosine Similarity: {0:.4f}'.format(sim))