Create app.py

app.py

@@ -0,0 +1,19 @@
+import pandas as pd
+dataset = pd.read_csv('a1_RestaurantReviews_HistoricDump.tsv', delimiter = '\t', quoting = 3)
+import pickle
+tokenizer=pickle.load(open("tokenizer.pkl","rb"))
+from keras.utils import pad_sequences
+model=pickle.load(open("model.pkl","rb"))
+def calc(abc):
+  abc=[abc]
+  seq=tokenizer.texts_to_sequences(abc)
+  inp=pad_sequences(seq,padding='post',maxlen=51)
+  score=(model.predict(inp))[0][0]
+  if score>0.6:
+    return("positive")
+  elif score <0.4:
+    return("negative")
+  else:
+    return("neutral")
+import gradio as gr
+gr.Interface(fn=calc,inputs=gr.inputs.Textbox(placeholder="Input the feeedback to be reviewed"),outputs="textbox").launch();