app.py added

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+import pickle
+
+from nltk.tokenize import word_tokenize
+import nltk
+nltk.download('all')
+
+with open('LogisticRegression_classifier.pickle','rb') as fp:
+  LogisticRegression_classifier = pickle.load(fp)
+
+with open('word_features5k.pickle','rb') as fp:
+  word_features = pickle.load(fp)
+
+
+def find_features(news):
+  words = word_tokenize(news)  
+  features = {}
+  for w in word_features:
+    features[w] = (w in words)
+  return features
+
+def fn(news):
+    return LogisticRegression_classifier.classify(find_features(news))
+
+iface = gr.Interface(
+        fn = fn,
+        inputs = 'text',
+        outputs = 'text'
+)
+
+url = iface.launch(share=True)
+# return url[]