Update app.py

app.py

@@ -1,21 +1,31 @@
+import os
 import gradio as gr
+from transformers import pipeline
 import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
 
-# Ensure necessary NLTK data is downloaded
+# Initialize the English text classification pipeline for AI detection
+pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
+
+# Function to predict the label and score for English text (AI Detection)
+def predict_en(text):
+    res = pipeline_en(text)[0]
+    return res['label'], res['score']
+
+# Ensure necessary NLTK data is downloaded for Humanifier
 nltk.download('wordnet')
 nltk.download('omw-1.4')
 
-# Ensure the SpaCy model is installed
+# Ensure the SpaCy model is installed for Humanifier
 try:
     nlp = spacy.load("en_core_web_sm")
 except OSError:
     subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"])
     nlp = spacy.load("en_core_web_sm")
 
-# Function to get synonyms using NLTK WordNet
+# Function to get synonyms using NLTK WordNet (Humanifier)
 def get_synonyms_nltk(word, pos):
     synsets = wordnet.synsets(word, pos=pos)
     if synsets:
@@ -23,7 +33,7 @@ def get_synonyms_nltk(word, pos):
         return [lemma.name() for lemma in lemmas]
     return []
 
-# Function to capitalize the first letter of sentences and proper nouns
+# Function to capitalize the first letter of sentences and proper nouns (Humanifier)
 def capitalize_sentences_and_nouns(text):
     doc = nlp(text)
     corrected_text = []
@@ -41,7 +51,7 @@ def capitalize_sentences_and_nouns(text):
 
     return ' '.join(corrected_text)
 
-# Paraphrasing function using SpaCy and NLTK
+# Paraphrasing function using SpaCy and NLTK (Humanifier)
 def paraphrase_with_spacy_nltk(text):
     doc = nlp(text)
     paraphrased_words = []
@@ -74,7 +84,7 @@ def paraphrase_with_spacy_nltk(text):
     
     return corrected_text
 
-# Combined function: Paraphrase -> Capitalization
+# Combined function: Paraphrase -> Capitalization (Humanifier)
 def paraphrase_and_correct(text):
     # Step 1: Paraphrase the text
     paraphrased_text = paraphrase_with_spacy_nltk(text)
@@ -84,16 +94,24 @@ def paraphrase_and_correct(text):
     
     return final_text
 
-# Gradio interface for paraphrasing and text correction
-with gr.Blocks() as paraphrase_interface:
-    with gr.Row():
-        with gr.Column():
-            text_input = gr.Textbox(lines=5, label="Input Text")
-            paraphrase_button = gr.Button("Paraphrase & Correct")
-        with gr.Column():
-            output_text = gr.Textbox(label="Paraphrased Text")
+# Gradio app setup with two tabs
+with gr.Blocks() as demo:
+    with gr.Tab("AI Detection"):
+        t1 = gr.Textbox(lines=5, label='Text')
+        button1 = gr.Button("🤖 Predict!")
+        label1 = gr.Textbox(lines=1, label='Predicted Label 🎃')
+        score1 = gr.Textbox(lines=1, label='Prob')
+
+        # Connect the prediction function to the button
+        button1.click(predict_en, inputs=[t1], outputs=[label1, score1], api_name='predict_en')
+    
+    with gr.Tab("Humanifier"):
+        text_input = gr.Textbox(lines=5, label="Input Text")
+        paraphrase_button = gr.Button("Paraphrase & Correct")
+        output_text = gr.Textbox(label="Paraphrased Text")
 
-    paraphrase_button.click(paraphrase_and_correct, inputs=text_input, outputs=output_text)
+        # Connect the paraphrasing function to the button
+        paraphrase_button.click(paraphrase_and_correct, inputs=text_input, outputs=output_text)
 
-# Launch the Gradio app for paraphrasing and text correction
-paraphrase_interface.launch(debug=False)
+# Launch the app with both functionalities
+demo.launch()