Create app.py

app.py

@@ -0,0 +1,40 @@
+import tensorflow as tf
+import numpy as np 
+import pickle
+import string
+import gradio as gr
+
+@tf.keras.utils.register_keras_serializable()
+def custom_standardization(input_string):
+    """ Remove html line-break tags and handle punctuation """
+    no_uppercased = tf.strings.lower(input_string, encoding='utf-8')
+    no_stars = tf.strings.regex_replace(no_uppercased, "\*", " ")
+    no_repeats = tf.strings.regex_replace(no_stars, "devamını oku", "")    
+    no_html = tf.strings.regex_replace(no_repeats, "", "")
+    no_digits = tf.strings.regex_replace(no_html, "\w*\d\w*","")
+    no_punctuations = tf.strings.regex_replace(no_digits, f"([{string.punctuation}])", r" ")
+    #remove stop words
+    #no_stop_words = ' '+no_punctuations+ ' '
+    #for each in tr_stop_words.values:
+    #  no_stop_words = tf.strings.regex_replace(no_stop_words, ' '+each[0]+' ' , r" ")
+    no_extra_space = tf.strings.regex_replace(no_punctuations, " +"," ")
+    #remove Turkish chars
+    no_I = tf.strings.regex_replace(no_extra_space, "ı","i")
+    no_O = tf.strings.regex_replace(no_I, "ö","o")
+    no_C = tf.strings.regex_replace(no_O, "ç","c")
+    no_S = tf.strings.regex_replace(no_C, "ş","s")
+    no_G = tf.strings.regex_replace(no_S, "ğ","g")
+    no_U = tf.strings.regex_replace(no_G, "ü","u")
+    return no_U
+
+end_to_end_model=tf.keras.models.load_model('MCTC_Conv1D_E2E')
+
+with open('id_to_category.pkl', 'rb') as fp:
+    id_to_category = pickle.load(fp)
+
+def text_classifier(text):
+  predictions=end_to_end_model.predict(examples)
+  for pred in predictions:
+    return(id_to_category[np.argmax(pred)])
+
+iface= gr.Interface(fn=text_classifier, inputs="text", outputs="text").launch()