Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import pipeline
 pipe=pipeline(model="vennify/t5-base-grammar-correction")
 st.title("Grammatical Error Checker")
 st.header("Text input:")
-text=st.text_area('Input sentence:')
+text=st.text_area('Input sentence:', key=1)
 if text:
     out=pipe(text)
     st.text_area(label="Output sentence:", value=out)
@@ -26,14 +26,14 @@ st.title("Language Translator")
 model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
 tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
 tokenizer.src_lang = "en_XX"
-text_l=st.text_area('Input sentence:')
+text_l=st.text_area('Input sentence:', key=2)
 encoded_en = tokenizer(text_l, return_tensors="pt")
 generated_tokens = model.generate(
     **encoded_en,
     forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"]
 )
-out_t=tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
-st.text_area(label="Output sentence:", value=out_t)
+out_l=tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+st.text_area(label="Output sentence:", value=out_l)
 
 pipe_p=pipeline(model="ramsrigouthamg/t5_sentence_paraphraser")
 st.title("Paraphraser")