Update app.py

app.py

@@ -1,4 +1,28 @@
-import tensorflow as tf
-from tensorflow import keras
+import numpy as np
+from keras.models import load_model
 
-loaded_model = keras.models.load_model('LithicAI-Education-Model.h5')
+# Load the model
+model = load_model('LithicAI-Education-Model.h5')
+
+# Function to generate text
+def generate_text(seed_text, next_words, model, max_sequence_len):
+    for _ in range(next_words):
+        # Convert seed text to sequence
+        token_list = tokenizer.texts_to_sequences([seed_text])[0]
+        # Pad the sequence
+        token_list = pad_sequences([token_list], maxlen=max_sequence_len-1, padding='pre')
+        # Predict the next word
+        predicted = model.predict_classes(token_list, verbose=0)
+        # Convert predicted word index to word
+        output_word = ""
+        for word, index in tokenizer.word_index.items():
+            if index == predicted:
+                output_word = word
+                break
+        # Add the predicted word to the seed text
+        seed_text += " "+output_word
+    return seed_text.title()
+
+# Generate text
+generated_text = generate_text("the quick brown", 5, model, 10)
+print(generated_text)