update app.py

app.py

@@ -65,18 +65,18 @@ def get_predict_result(index,score,threshold,max_len):
     res = merge_set_to_list([set(i) for i in y_dict[res_index]])
     return res,x_dict[res_index]
 
-vec = np.empty(shape=[0,768],dtype="float32")
-bsize = 256
-with torch.no_grad():
-    for i in range(0,len(x),bsize):
-        tmp = model.encode(x[i:i+bsize])
-        vec = np.concatenate([vec,tmp])
-
-
-index = faiss.IndexFlatIP(768)
-faiss.normalize_L2(vec)
-index.add(vec)
-faiss.write_index(index,"all_index.faiss")
+# vec = np.empty(shape=[0,768],dtype="float32")
+# bsize = 256
+# with torch.no_grad():
+#     for i in range(0,len(x),bsize):
+#         tmp = model.encode(x[i:i+bsize])
+#         vec = np.concatenate([vec,tmp])
+
+
+# index = faiss.IndexFlatIP(768)
+# faiss.normalize_L2(vec)
+# index.add(vec)
+# faiss.write_index(index,"all_index.faiss")
 index = faiss.read_index("all_index.faiss")
 
 def predict_label(x,threshold=0.85,n_nearest=10,max_result_len=3):