Upload app.py

app.py

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+import tensorflow as tf
+import gradio as gr
+import pickle
+import os
+
+# define variables
+checkpoint_folder = './'
+bi_gru_name = "test_25_128_2564_15_32_10_16_05_D_64_15.pickle"
+tokenizer_path = os.path.join(checkpoint_folder, 'tokenizer_tP4suwZ.pickle')
+model_path = os.path.join(checkpoint_folder, bi_gru_name)
+INDEX_CLASS = {0:'suicide', 1:'non-suicide'}
+MAX_SEQ_DF = 64
+
+
+# load the tokenizer from pickle
+with open(tokenizer_path, 'rb') as tokenizer_file:
+    tokenizer = pickle.load(tokenizer_file)
+# load the mode from pickle and read the model
+with open(model_path, 'rb') as model_file:
+    model_json = pickle.load(model_file)
+model = tf.keras.models.model_from_json(model_json)
+
+# define prediction function
+def predict(input_text):
+    # preprocessing
+    tokenized_data = tokenizer.texts_to_sequences([input_text])
+    text_data_padded = tf.keras.preprocessing.sequence.pad_sequences(tokenized_data, maxlen = MAX_SEQ_DF, padding = 'post')
+
+    # make prediction
+    pred = model.predict(text_data_padded)
+    prediction = INDEX_CLASS[round(pred[0][0])]
+
+    return prediction
+
+
+gr_intrfc = gr.Interface(fn=predict, inputs="text", title='Suicide Detection',
+            examples=['I Just want it to stop, what the point anyway',
+                      'Thanks for the help, i do nont feel depressed anymore'],
+                      outputs="text", theme='dark')
+gr_intrfc.launch(debug=True, )
+