Update app.py

app.py

@@ -6,6 +6,12 @@ from sklearn.feature_extraction.text import TfidfVectorizer
 
 os.environ["WANDB_DISABLED"] = "true"
 
+label2id =  {
+    0: "negative",
+    1: "neutral",
+    2: "positive"
+  }
+
 model_file_name = "xgb_reg.pkl"
 vectorizer_file_name = 'vectorizer.pk'
 
@@ -15,10 +21,9 @@ vectorizer_loaded = pickle.load(open(vectorizer_file_name, "rb"))
 
 # predict
 def predict_sentiment(predict_texts):
-    predictions_loaded = xgb_model_loaded.predict(
-    vectorizer_loaded.transform(predict_texts))
-    return vectorizer_loaded
-    #le.inverse_transform(predictions_loaded)
+    predictions_loaded = xgb_model_loaded.predict(vectorizer_loaded.transform([predict_texts]))
+    print(predictions_loaded)
+    return label2id[predictions_loaded[0]]
 
 interface = gr.Interface(
     fn=predict_sentiment,