text generation.py

def create_model(max_sequence_len, total_words):
    input_len = max_sequence_len - 1
    model = Sequential()
    
    # Add Input Embedding Layer
    model.add(Embedding(total_words, 10, input_length=input_len))
    
    # Add Hidden Layer 1 - LSTM Layer
    model.add(LSTM(100))
    model.add(Dropout(0.1))
    
    # Add Output Layer
    model.add(Dense(total_words, activation='softmax'))

    model.compile(loss='categorical_crossentropy', optimizer='adam')
    
    return model

model = create_model(max_sequence_len, total_words)
model.summary()