text generation.py

def generate_text(seed_text, next_words, model, max_sequence_len):
    for _ in range(next_words):
        token_list = tokenizer.texts_to_sequences([seed_text])[0]
        token_list = pad_sequences([token_list], maxlen=max_sequence_len-1, padding='pre')
        predicted = model.predict_classes(token_list, verbose=0)
        
        output_word = ""
        for word,index in tokenizer.word_index.items():
            if index == predicted:
                output_word = word
                break
        seed_text += " "+output_word
    return seed_text.title()
   
print (generate_text("united states", 5, model, max_sequence_len))
print (generate_text("preident trump", 4, model, max_sequence_len))
print (generate_text("donald trump", 4, model, max_sequence_len))
print (generate_text("india and china", 4, model, max_sequence_len))
print (generate_text("new york", 4, model, max_sequence_len))
print (generate_text("science and technology", 5, model, max_sequence_len))