Update app.py

app.py

@@ -26,6 +26,26 @@ app = Flask(__name__, template_folder='templates')
 CORS(app)
 chat_history = []
 
+
+cls_model = AutoModelForSequenceClassification.from_pretrained("riskclassification_finetuned_xlnet_model_ld")
+tokenizer_cls = AutoTokenizer.from_pretrained("xlnet-base-cased")
+label_encoder_path = "riskclassification_finetuned_xlnet_model_ld/encoder_labels.pkl"
+label_encoder = LabelEncoder()
+
+# Assuming 'label_column values' is the column you want to encode
+label_column_values = ["risks","opportunities","neither"]
+
+
+label_encoder.fit_transform(label_column_values)
+
+joblib.dump(label_encoder, label_encoder_path)
+
+
+model_summ = T5ForConditionalGeneration.from_pretrained("t5-small")
+tokenizer_summ = T5Tokenizer.from_pretrained("t5-small")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
 model_name = "deepset/tinyroberta-squad2"
 nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
 
@@ -256,23 +276,6 @@ def home():
         print("Form Data:", request.form)
         input_submitted = True
         print(url_input)
-        cls_model = AutoModelForSequenceClassification.from_pretrained("riskclassification_finetuned_xlnet_model_ld")
-        tokenizer_cls = AutoTokenizer.from_pretrained("xlnet-base-cased")
-        label_encoder_path = "riskclassification_finetuned_xlnet_model_ld/encoder_labels.pkl"
-        label_encoder = LabelEncoder()
-
-        # Assuming 'label_column values' is the column you want to encode
-        label_column_values = ["risks","opportunities","neither"]
-
-
-        label_encoder.fit_transform(label_column_values)
-
-        joblib.dump(label_encoder, label_encoder_path)
-
-
-        model_summ = T5ForConditionalGeneration.from_pretrained("t5-small")
-        tokenizer_summ = T5Tokenizer.from_pretrained("t5-small")
-        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
         if url_input.startswith("http"):
             current_request_timestamp = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')