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Update app.py
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app.py
CHANGED
@@ -17,9 +17,6 @@ def predict_en(text):
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# Ensure necessary NLTK data is downloaded for Humanifier
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nltk.download('wordnet')
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nltk.download('omw-1.4')
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nltk.download('punkt')
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nltk.download('averaged_perceptron_tagger')
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# Ensure the SpaCy model is installed for Humanifier
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try:
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@@ -28,59 +25,6 @@ except OSError:
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subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"])
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nlp = spacy.load("en_core_web_sm")
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# Grammar, Tense, and Singular/Plural Correction Functions
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# Correct article errors (e.g., "a apple" -> "an apple")
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def check_article_error(text):
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tokens = nltk.pos_tag(nltk.word_tokenize(text))
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corrected_tokens = []
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for i, token in enumerate(tokens):
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word, pos = token
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if word.lower() == 'a' and i < len(tokens) - 1 and tokens[i + 1][1] == 'NN':
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corrected_tokens.append('an' if tokens[i + 1][0][0] in 'aeiou' else 'a')
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else:
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corrected_tokens.append(word)
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return ' '.join(corrected_tokens)
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# Correct tense errors (e.g., "She has go out" -> "She has gone out")
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def check_tense_error(text):
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tokens = nltk.pos_tag(nltk.word_tokenize(text))
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corrected_tokens = []
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for word, pos in tokens:
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if word == "go" and pos == "VB":
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corrected_tokens.append("gone")
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elif word == "know" and pos == "VB":
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corrected_tokens.append("known")
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else:
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corrected_tokens.append(word)
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return ' '.join(corrected_tokens)
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# Correct singular/plural errors (e.g., "There are many chocolate" -> "There are many chocolates")
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def check_pluralization_error(text):
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tokens = nltk.pos_tag(nltk.word_tokenize(text))
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corrected_tokens = []
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for word, pos in tokens:
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if word == "chocolate" and pos == "NN":
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corrected_tokens.append("chocolates")
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elif word == "kids" and pos == "NNS":
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corrected_tokens.append("kid")
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else:
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corrected_tokens.append(word)
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return ' '.join(corrected_tokens)
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# Combined function to correct grammar, tense, and singular/plural errors
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def correct_grammar_tense_plural(text):
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text = check_article_error(text)
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text = check_tense_error(text)
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text = check_pluralization_error(text)
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return text
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# Function to get synonyms using NLTK WordNet (Humanifier)
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def get_synonyms_nltk(word, pos):
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synsets = wordnet.synsets(word, pos=pos)
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@@ -140,20 +84,17 @@ def paraphrase_with_spacy_nltk(text):
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return corrected_text
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# Combined function: Paraphrase -> Capitalization
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def paraphrase_and_correct(text):
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# Step 1: Paraphrase the text
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paraphrased_text = paraphrase_with_spacy_nltk(text)
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# Step 2: Capitalize sentences and proper nouns
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# Step 3: Correct grammar, tense, and pluralization
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final_text = correct_grammar_tense_plural(capitalized_text)
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return final_text
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# Gradio app setup with
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with gr.Blocks() as demo:
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with gr.Tab("AI Detection"):
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t1 = gr.Textbox(lines=5, label='Text')
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# Connect the paraphrasing function to the button
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paraphrase_button.click(paraphrase_and_correct, inputs=text_input, outputs=output_text)
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with gr.Tab("Grammar Correction"):
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grammar_input = gr.Textbox(lines=5, label="Input Text")
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grammar_button = gr.Button("Correct Grammar")
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grammar_output = gr.Textbox(label="Corrected Text")
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# Connect the custom grammar, tense, and plural correction function to the button
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grammar_button.click(correct_grammar_tense_plural, inputs=grammar_input, outputs=grammar_output)
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# Launch the app with
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demo.launch(
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# Ensure necessary NLTK data is downloaded for Humanifier
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nltk.download('wordnet')
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nltk.download('omw-1.4')
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# Ensure the SpaCy model is installed for Humanifier
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try:
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subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"])
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nlp = spacy.load("en_core_web_sm")
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# Function to get synonyms using NLTK WordNet (Humanifier)
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def get_synonyms_nltk(word, pos):
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synsets = wordnet.synsets(word, pos=pos)
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return corrected_text
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# Combined function: Paraphrase -> Capitalization (Humanifier)
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def paraphrase_and_correct(text):
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# Step 1: Paraphrase the text
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paraphrased_text = paraphrase_with_spacy_nltk(text)
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# Step 2: Capitalize sentences and proper nouns
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final_text = capitalize_sentences_and_nouns(paraphrased_text)
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return final_text
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# Gradio app setup with two tabs
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with gr.Blocks() as demo:
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with gr.Tab("AI Detection"):
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t1 = gr.Textbox(lines=5, label='Text')
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# Connect the paraphrasing function to the button
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paraphrase_button.click(paraphrase_and_correct, inputs=text_input, outputs=output_text)
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# Launch the app with the remaining functionalities
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demo.launch()
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