Update app.py

app.py

@@ -6,9 +6,9 @@ import pandas as pd
 import gradio as gr
 
 # -----------------------------
-# STRONGEST MODEL
+# STRONGEST AVAILABLE PUBLIC MODEL (WORKING)
 # -----------------------------
-MODEL_NAME = "Hello-SimpleAI/HC3-Plus-OpenAI-Detector"
+MODEL_NAME = "openai-community/roberta-base-openai-detector"
 
 # -----------------------------
 # LOAD MODEL
@@ -21,7 +21,7 @@ model.to(device).eval()
 
 
 # -----------------------------
-# PARAGRAPH TOKENIZER
+# PARAGRAPH SPLITTER
 # -----------------------------
 def paragraph_split(text):
     paragraphs = [p.strip() for p in text.split("\n") if p.strip()]
@@ -29,7 +29,7 @@ def paragraph_split(text):
 
 
 # -----------------------------
-# INFERENCE FUNCTION
+# AI DETECTION FUNCTION
 # -----------------------------
 def classify_text(text):
     if not text.strip():
@@ -64,12 +64,13 @@ def classify_text(text):
         pred_label = preds[i].item()
         confidence = probs[i, pred_label].item()
 
-        label = "AI" if pred_label == 0 else "Human"
+        label = "AI" if pred_label == 1 else "Human"  
+        # NOTE: roberta-base-openai-detector → label 1 = Fake (AI), 0 = Real (Human)
+
         conf_text = f"{confidence:.2f}"
 
         results.append([p, label, conf_text])
 
-        # Highlighting
         if label == "AI":
             highlighted_paragraphs.append(
                 f"<p style='color:red; font-weight:bold; margin-bottom:10px'>{p}</p>"
@@ -83,7 +84,7 @@ def classify_text(text):
     # DOCUMENT LEVEL SCORE
     # -----------------------------
     avg = torch.mean(probs, dim=0)
-    ai_likelihood = avg[0].item() * 100  # class 0 = AI
+    ai_likelihood = avg[1].item() * 100   # class 1 = AI
 
     highlighted_html = "\n".join(highlighted_paragraphs)
     df = pd.DataFrame(results, columns=["Paragraph", "Classification", "Confidence"])
@@ -92,7 +93,7 @@ def classify_text(text):
 
 
 # -----------------------------
-# GRADIO INTERFACE
+# GRADIO UI
 # -----------------------------
 with gr.Blocks() as demo:
     gr.Markdown("## 🧠 Writenix Advanced AI Detection (Paragraph-Level)")
@@ -112,6 +113,5 @@ with gr.Blocks() as demo:
 
     classify_btn.click(classify_text, inputs=text_input, outputs=[ai_score, highlighted, table])
 
-
 if __name__ == "__main__":
     demo.launch()