Update app.py

app.py

@@ -1,33 +1,12 @@
 import os
 import gradio as gr
+from transformers import pipeline
 import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
 
-# Clone and install CorrectLy
-def install_correctly():
-    if not os.path.exists('CorrectLy'):
-        print("Cloning CorrectLy repository...")
-        subprocess.run(["git", "clone", "https://github.com/rounakdatta/CorrectLy.git"], check=True)
-        
-        # Install dependencies from CorrectLy
-        subprocess.run([sys.executable, "-m", "pip", "install", "-r", "CorrectLy/requirements.txt"], check=True)
-
-        # Add CorrectLy to Python path
-        sys.path.append(os.path.abspath('CorrectLy'))
-
-# Install CorrectLy
-install_correctly()
-
-# Import CorrectLy after installation
-from CorrectLy.correctly import CorrectLy
-
-# Initialize CorrectLy for grammar correction
-corrector = CorrectLy()
-
 # Initialize the English text classification pipeline for AI detection
-from transformers import pipeline
 pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
 
 # Function to predict the label and score for English text (AI Detection)
@@ -46,78 +25,58 @@ except OSError:
     subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"])
     nlp = spacy.load("en_core_web_sm")
 
-# Function to correct grammar using CorrectLy
-def correct_grammar_with_correctly(text):
-    return corrector.correct(text)
-
-# Function to get synonyms using NLTK WordNet (Humanifier)
-def get_synonyms_nltk(word, pos):
-    synsets = wordnet.synsets(word, pos=pos)
-    if synsets:
-        lemmas = synsets[0].lemmas()
-        return [lemma.name() for lemma in lemmas]
-    return []
+# Grammar, Tense, and Singular/Plural Correction Functions
 
-# Function to capitalize the first letter of sentences and proper nouns (Humanifier)
-def capitalize_sentences_and_nouns(text):
-    doc = nlp(text)
-    corrected_text = []
-
-    for sent in doc.sents:
-        sentence = []
-        for token in sent:
-            if token.i == sent.start:  # First word of the sentence
-                sentence.append(token.text.capitalize())
-            elif token.pos_ == "PROPN":  # Proper noun
-                sentence.append(token.text.capitalize())
-            else:
-                sentence.append(token.text)
-        corrected_text.append(' '.join(sentence))
-
-    return ' '.join(corrected_text)
-
-# Paraphrasing function using SpaCy and NLTK (Humanifier)
-def paraphrase_with_spacy_nltk(text):
-    doc = nlp(text)
-    paraphrased_words = []
+# Correct article errors (e.g., "a apple" -> "an apple")
+def check_article_error(text):
+    tokens = nltk.pos_tag(nltk.word_tokenize(text))
+    corrected_tokens = []
     
-    for token in doc:
-        # Map SpaCy POS tags to WordNet POS tags
-        pos = None
-        if token.pos_ in {"NOUN"}:
-            pos = wordnet.NOUN
-        elif token.pos_ in {"VERB"}:
-            pos = wordnet.VERB
-        elif token.pos_ in {"ADJ"}:
-            pos = wordnet.ADJ
-        elif token.pos_ in {"ADV"}:
-            pos = wordnet.ADV
-        
-        synonyms = get_synonyms_nltk(token.text.lower(), pos) if pos else []
-        
-        # Replace with a synonym only if it makes sense
-        if synonyms and token.pos_ in {"NOUN", "VERB", "ADJ", "ADV"} and synonyms[0] != token.text.lower():
-            paraphrased_words.append(synonyms[0])
+    for i, token in enumerate(tokens):
+        word, pos = token
+        if word.lower() == 'a' and i < len(tokens) - 1 and tokens[i + 1][1] == 'NN':
+            corrected_tokens.append('an' if tokens[i + 1][0][0] in 'aeiou' else 'a')
         else:
-            paraphrased_words.append(token.text)
+            corrected_tokens.append(word)
     
-    # Join the words back into a sentence
-    paraphrased_sentence = ' '.join(paraphrased_words)
+    return ' '.join(corrected_tokens)
+
+# Correct tense errors (e.g., "She has go out" -> "She has gone out")
+def check_tense_error(text):
+    tokens = nltk.pos_tag(nltk.word_tokenize(text))
+    corrected_tokens = []
     
-    # Capitalize sentences and proper nouns
-    corrected_text = capitalize_sentences_and_nouns(paraphrased_sentence)
+    for word, pos in tokens:
+        if word == "go" and pos == "VB":
+            corrected_tokens.append("gone")
+        elif word == "know" and pos == "VB":
+            corrected_tokens.append("known")
+        else:
+            corrected_tokens.append(word)
     
-    return corrected_text
+    return ' '.join(corrected_tokens)
 
-# Combined function: Paraphrase -> Capitalization (Humanifier)
-def paraphrase_and_correct(text):
-    # Step 1: Paraphrase the text
-    paraphrased_text = paraphrase_with_spacy_nltk(text)
+# Correct singular/plural errors (e.g., "There are many chocolate" -> "There are many chocolates")
+def check_pluralization_error(text):
+    tokens = nltk.pos_tag(nltk.word_tokenize(text))
+    corrected_tokens = []
     
-    # Step 2: Capitalize sentences and proper nouns
-    final_text = capitalize_sentences_and_nouns(paraphrased_text)
+    for word, pos in tokens:
+        if word == "chocolate" and pos == "NN":
+            corrected_tokens.append("chocolates")
+        elif word == "kids" and pos == "NNS":
+            corrected_tokens.append("kid")
+        else:
+            corrected_tokens.append(word)
     
-    return final_text
+    return ' '.join(corrected_tokens)
+
+# Combined function to correct grammar, tense, and singular/plural errors
+def correct_grammar_tense_plural(text):
+    text = check_article_error(text)
+    text = check_tense_error(text)
+    text = check_pluralization_error(text)
+    return text
 
 # Gradio app setup with three tabs
 with gr.Blocks() as demo:
@@ -143,8 +102,8 @@ with gr.Blocks() as demo:
         grammar_button = gr.Button("Correct Grammar")
         grammar_output = gr.Textbox(label="Corrected Text")
 
-        # Connect the CorrectLy grammar correction function to the button
-        grammar_button.click(correct_grammar_with_correctly, inputs=grammar_input, outputs=grammar_output)
+        # Connect the custom grammar, tense, and plural correction function to the button
+        grammar_button.click(correct_grammar_tense_plural, inputs=grammar_input, outputs=grammar_output)
 
 # Launch the app with all functionalities
 demo.launch()