Update app.py

app.py

@@ -1,4 +1,37 @@
-import transformers
+#Import required libraries
+import pickle
 import gradio as gr
-from transformers import pipeline
+import gradio.inputs
+import pandas as pd
+import numpy as np
+import tensorflow as tf 
+from tensorflow.keras.preprocessing.sequence import pad_sequences
 
+
+#Loading the tokenizer
+with open('tokenizer.pickle', 'rb') as f:
+    tokenizer = pickle.load(f)
+   
+
+
+def predict_sentiment(text):
+    sentiment = ['Do you really dislike the movie so much?','Hmm...your thoughts are neutral about the movie.','Wow! Your a big fan.']
+    sequence_test = tokenizer.texts_to_sequences([text])
+    padded_test = pad_sequences(sequence_test, maxlen= 52)
+    text=padded_test
+    model = tf.keras.models.load_model("huggingface/keras-io/bidirectional-lstm-imdb")
+    X = [text for _ in range(len(model.input))]
+    a=model.predict(X, verbose=0)
+    return sentiment[np.around(a, decimals=0).argmax(axis=1)[0]]
+description = "Give a review of a movie that you like(or hate, sarcasm intended XD) and the model will let you know just how much your review truely reflects your emotions. "
+
+
+#Gradio app     
+iface = gr.Interface(predict_sentiment,
+                     inputs= gradio.inputs.Textbox( lines=1, placeholder=None, default="", label=None),
+                     outputs='text',
+                     title="Sentiment analysis of movie reviews",
+                     description=description,
+                     theme="grass")
+iface.launch(enable_queue = True, inline=False, share = True)
+