Upload app.py

app.py

@@ -1,14 +1,10 @@
 import gradio as gr
 import pickle
-import re
-import string
 import tensorflow as tf
 import keras.ops as ops
 import keras
-from keras.saving import register_keras_serializable
 from keras import layers
 from keras.layers import TextVectorization
-from nltk.translate.bleu_score import sentence_bleu, SmoothingFunction
 
 
 # from gradio_webrtc import WebRTC
@@ -196,7 +192,6 @@ transformer = keras.models.load_model(
 id_vocab = id_vectorization.get_vocabulary()
 id_index_lookup = dict(zip(range(len(id_vocab)), id_vocab))
 max_decoded_sentence_lenth = 20
-smoothing_function = SmoothingFunction().method2
 
 def decode_sequence(input_sentence):
     tokenized_input_sentence = en_vectorization([input_sentence])
@@ -217,7 +212,7 @@ def decode_sequence(input_sentence):
         decoded_sentence += " " + sampled_token
         if sampled_token == "end":
             break
-    return decoded_sentence.replace("[start]", "").replace("end", "").trim()
+    return decoded_sentence.replace("[start]", "").replace("end", "").lstrip().rstrip()
 
 # image = WebRTC(label="Stream")