Update app.py

app.py

@@ -0,0 +1,39 @@
+import pandas as pd
+import numpy as np
+import gradio as gr 
+
+import tensorflow as tf
+from tensorflow.keras.layers import TextVectorization
+
+df = pd.read_csv('/content/CommentToxicity/jigsaw-toxic-comment-classification-challenge/train.csv/train.csv')
+df.shape
+
+X = df['comment_text']
+y = df[df.columns[2:]].values
+
+max_features = 2000000
+
+vecterizor = TextVectorization(max_tokens=max_features,output_sequence_length=1800,output_mode='int')
+
+vecterizor.adapt(X.values)
+
+model_path = 'commenttoxicity (1).h5'
+
+model = tf.keras.models.load_model(model_path)
+
+
+def score_comment(comment):
+    vectorized_comment = vecterizor([comment])
+    results = model.predict(vectorized_comment)
+
+    text = ''
+    for idx, col in enumerate(df.columns[2:]):
+        text += '{}: {}\n'.format(col, results[0][idx]>0.5)
+
+    return text
+
+interface = gr.Interface(fn=score_comment,
+                         inputs=gr.Textbox(lines=2, placeholder='Comment to score'),
+                        outputs='text')
+
+interface.launch(share=True)