commit Gi

app.py

@@ -240,7 +240,9 @@ searcher = scann.scann_ops_pybind.builder(np.array(indice), 10, "dot_product").t
 import matplotlib.pyplot as plt
 
 def predict(text):
-    campos=str(text).lower()
+    ##GI
+    campos=re.sub(r'[\W\s]', ' ', ''.join(unidecode.unidecode(str(text).lower()))).replace("  ", " ")
+    ##GI
     query=np.sum([model.user_model(tf.constant(campos.split()[i])) for i in range(0,len(campos.split()))],axis=0)
     neighbors, distances = searcher.search_batched([query])
     xx = df.iloc[neighbors[0],:].nome_vaga