Update app.py

app.py

@@ -5,6 +5,19 @@ import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
+import language_tool_python
+tool = language_tool_python.LanguageTool('en-US')
+
+# Function to correct tense errors using LanguageTool
+def correct_tense_errors(text):
+    # Check for grammar mistakes, which includes tense errors
+    matches = tool.check(text)
+    corrected_text = language_tool_python.utils.correct(text, matches)
+    return corrected_text
+
+
+
+    
 
 # Initialize the English text classification pipeline for AI detection
 pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
@@ -52,18 +65,14 @@ def capitalize_sentences_and_nouns(text):
     return ' '.join(corrected_text)
 
 # Function to correct tense errors in a sentence (Tense Correction)
-def correct_tense_errors(text):
-    doc = nlp(text)
-    corrected_text = []
-    for token in doc:
-        # Check for tense correction based on modal verbs
-        if token.pos_ == "VERB" and token.dep_ in {"aux", "auxpass"}:
-            # Replace with appropriate verb form
-            lemma = wordnet.morphy(token.text, wordnet.VERB) or token.text
-            corrected_text.append(lemma)
-        else:
-            corrected_text.append(token.text)
-    return ' '.join(corrected_text)
+#def correct_tense_errors(text):
+#    doc = nlp(text)
+###       if token.pos_ == "VERB" and token.dep_ in {"aux", "auxpass"}:
+##            lemma = wordnet.morphy(token.text, wordnet.VERB) or token.text
+#            corrected_text.append(lemma)
+ #       else:
+  #          corrected_text.append(token.text)
+  #  return ' '.join(corrected_text)
 
 # Function to correct singular/plural errors (Singular/Plural Correction)
 def correct_singular_plural_errors(text):
@@ -141,18 +150,17 @@ def paraphrase_with_spacy_nltk(text):
 
 # Combined function: Paraphrase -> Grammar Correction -> Capitalization (Humanifier)
 def paraphrase_and_correct(text):
-    # Step 1: Paraphrase the text
-    paraphrased_text = paraphrase_with_spacy_nltk(text)
+   paraphrased_text = paraphrase_with_spacy_nltk(text)
     
     # Step 2: Apply grammatical corrections on the paraphrased text
     corrected_text = correct_article_errors(paraphrased_text)
     
-    corrected_text = capitalize_sentences_and_nouns(corrected_text)
+    # Use the new stronger tense correction method
+    corrected_text = correct_tense_errors(corrected_text)
     
+    # Step 3: Correct singular/plural issues and capitalization
     corrected_text = correct_singular_plural_errors(corrected_text)
-    
-    # Step 3: Capitalize sentences and proper nouns (final correction step)
-    final_text = correct_tense_errors(corrected_text)
+    final_text = capitalize_sentences_and_nouns(corrected_text)
     
     return final_text