Update app.py

app.py

@@ -73,11 +73,10 @@ def main():
     	+ This is a Natural Language Processing(NLP) Based App useful for basic NLP task
          NER,Sentiment, Spell Corrections and Summarization
     	""")
+    message = st.text_area("Enter the Text","Type please ..")	
 	# Entity Extraction
 	if st.checkbox("Show Named Entities"):
 		st.subheader("Analyze Your Text")
-
-		message = st.text_area("Enter your Text","Typing Here ..")
 		if st.button("Extract"):
 			entity_result = entity_analyzer(message)
 			st.json(entity_result)
@@ -85,7 +84,6 @@ def main():
 	# Sentiment Analysis
 	elif st.checkbox("Show Sentiment Analysis"):
 		st.subheader("Analyse Your Text")
-		message = st.text_area("Enter Text plz, Type Here ...")
 		if st.button("Analyze"):
 			blob = TextBlob(message)
 			result_sentiment = blob.sentiment
@@ -93,16 +91,14 @@ def main():
     #Text Corrections
 	elif st.checkbox("Spell Corrections"):
 		st.subheader("Correct Your Text")
-		message = st.text_area("Enter the Text","Type please ..")
 		if st.button("Spell Corrections"):
 			st.text("Using TextBlob ..")
 			st.success(TextBlob(message).correct())
 	elif st.checkbox("Text Generation"):
 		st.subheader("Generate Text")
-		message = st.text_area("Enter the Text","Type please ..")
-		tokenizer, model = load_models()
-		input_ids = tokenizer(message, return_tensors='pt').input_ids
 		if st.button("Generate"):
+		    tokenizer, model = load_models()
+		    input_ids = tokenizer(message, return_tensors='pt').input_ids
 		    st.text("Using Hugging Face Trnsformer, Contrastive Search ..")
 		    output = model.generate(input_ids, max_length=128)
 		    st.success(tokenizer.decode(output[0], skip_special_tokens=True))