Update Prediction

Add a function to find the most common word instead of giving 'none'

predict.py

@@ -4,11 +4,16 @@ import numpy as np
 import pickle
 nltk.download('punkt')
 # Define predict_word function
+from collections import Counter
+
 def predict_word(model, last_word):
     if last_word in model:
-        return np.random.choice(model[last_word])
+        next_words = model[last_word]
+        freq_dist = Counter(next_words)
+        most_common_word = freq_dist.most_common(1)[0][0]
+        return most_common_word
     else:
-        return None
+        return ""
 # Load the model
 with open("model.pkl", "rb") as f:
     model = pickle.load(f)