Update app.py

app.py

@@ -1,27 +1,18 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSequenceClassification, GPT2LMHeadModel
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 import math
 
-# -------------------------------
-# Load Models
-# -------------------------------
-
-# RoBERTa AI Detector (pretrained model from Hugging Face)
-detector_name = "Hello-SimpleAI/AI-Text-Detector-RoBERTa"
+# Load the ChatGPT detector model
+detector_name = "Hello-SimpleAI/chatgpt-detector-roberta"
 detector_tokenizer = AutoTokenizer.from_pretrained(detector_name)
 detector_model = AutoModelForSequenceClassification.from_pretrained(detector_name)
 
-# GPT-2 for perplexity calculation
+# Load GPT-2 for perplexity calculation
 gpt2_name = "gpt2"
 gpt2_tokenizer = AutoTokenizer.from_pretrained(gpt2_name)
 gpt2_model = GPT2LMHeadModel.from_pretrained(gpt2_name)
 
-
-# -------------------------------
-# Helper Functions
-# -------------------------------
-
 def compute_perplexity(text: str) -> float:
     """Calculate perplexity using GPT-2 language model."""
     enc = gpt2_tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
@@ -30,12 +21,11 @@ def compute_perplexity(text: str) -> float:
         loss = gpt2_model(input_ids, labels=input_ids).loss
     return math.exp(loss.item())
 
-
 def analyze_text(user_text: str):
     if not user_text.strip():
         return {"error": "Please enter some text to analyze."}
 
-    # Model 1: RoBERTa detector
+    # Model 1: ChatGPT detector
     inputs = detector_tokenizer(user_text, return_tensors="pt", truncation=True, max_length=512)
     with torch.no_grad():
         logits = detector_model(**inputs).logits
@@ -52,17 +42,12 @@ def analyze_text(user_text: str):
     final_human = 1 - final_ai
 
     return {
-        "RoBERTa AI Probability": round(ai_prob * 100, 2),
+        "ChatGPT AI Probability": round(ai_prob * 100, 2),
         "Perplexity-based AI Probability": round(ppl_score * 100, 2),
         "Final AI Probability (avg)": round(final_ai * 100, 2),
         "Final Human Probability (avg)": round(final_human * 100, 2),
     }
 
-
-# -------------------------------
-# Gradio UI
-# -------------------------------
-
 with gr.Blocks() as demo:
     gr.Markdown("# 🔍 Free AI vs Human Text Detector (Demo)")
 
@@ -78,6 +63,5 @@ with gr.Blocks() as demo:
 
     run_btn.click(analyze_text, inputs=user_input, outputs=output)
 
-
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)