Update app.py

app.py

@@ -1,4 +1,7 @@
 # app.py
+import os
+os.system('python download.py')
+
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 import gradio as gr
 import nltk
@@ -6,11 +9,6 @@ from nltk.tokenize import sent_tokenize, word_tokenize
 from nltk.corpus import wordnet as wn
 from difflib import SequenceMatcher
 
-# Download necessary resources
-nltk.download('punkt')
-nltk.download('averaged_perceptron_tagger')
-nltk.download('wordnet')
-
 # Load a pre-trained T5 model specifically fine-tuned for grammar correction
 tokenizer = T5Tokenizer.from_pretrained("prithivida/grammar_error_correcter_v1")
 model = T5ForConditionalGeneration.from_pretrained("prithivida/grammar_error_correcter_v1")
@@ -73,14 +71,13 @@ def grammar_check(text):
 
     verb_forms_str = "\n".join(verb_forms_list)
 
-    # Return combined result
-    return f"{corrected_text}\n\n<b>Revised Verb Forms:</b>\n{verb_forms_str}"
+    return corrected_text, verb_forms_str
 
 # Create Gradio interface with a writing prompt
 interface = gr.Interface(
     fn=grammar_check,
     inputs="text",
-    outputs="html",  # Change output type to HTML
+    outputs=["html", "text"],  # Two output boxes: HTML for corrected text, Text for verb forms list
     title="Grammar Checker",
     description=(
         "Enter text to check for grammar mistakes.\n\n"
@@ -93,4 +90,3 @@ interface = gr.Interface(
 
 # Launch the interface
 interface.launch()
-