feat: Added required files

app.py

@@ -6,16 +6,12 @@ import tensorflow as tf
 from tensorflow.keras.preprocessing.text import Tokenizer
 from tensorflow.keras.preprocessing.sequence import pad_sequences
 
+
 # Static constants
-vocab_size = 103
 max_seq_len = 18
-model = tf.keras.Sequential([
-            tf.keras.layers.Embedding(vocab_size, 120, input_length=max_seq_len-1),
-            tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(120)),
-            tf.keras.layers.Dense(vocab_size, activation='softmax')
-])
-model.load_weights("model_weight/")
-word_token = json.load("word_token.json")
+model = tf.keras.models.load_model('poembot_weight.h5')
+with open("word_token.json") as wt:
+    word_token = json.load(wt)
 # Main function
 def text_generator(seed_text,n):
 
@@ -24,7 +20,7 @@ def text_generator(seed_text,n):
         token_list = pad_sequences([token_list], maxlen=max_seq_len-1, padding='pre')
         predicted = np.argmax(model.predict(token_list), axis=-1)
         output_word = ""
-        output_word = word_token[predicted[0]]
+        output_word = word_token.get(str(predicted[0]))
         if "0" in output_word[-1]: 
             output_word = output_word[:-1]
             seed_text += " " + output_word +"."
@@ -38,4 +34,4 @@ iface = gr.Interface(
     title="Poem Bot",
     live=False
     )
-iface.launch()
+iface.launch(debug=True)

poembot_weight.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7bbcc1ade1290a9d2cbd5544e56539d1e2d74a5b2c3d878e54440dbf1579d5f5
+size 1097832