DivEye - PR (fix bugs x4)

app.py

@@ -20,7 +20,27 @@ theme = gr.Theme.from_hub("gstaff/xkcd")
 
 # ===========================================================
 @spaces.GPU
-def evaluate(text):
+def detect_ai_text(text):
+    global loaded
+    if not loaded:
+        return "❗ Model not loaded. We require a GPU to run DivEye.", 0.0, pd.DataFrame({
+            "Source": ["AI Generated", "Human Written"],
+            "Probability (%)": [0, 0]
+        })
+    
+    text = text.strip()
+    if not text or len(text.split()) < 15:
+        return (
+            "❗ Please enter some text with at least 15 words.",
+            0.0,
+            pd.DataFrame({
+                "Source": ["AI Generated", "Human Written"],
+                "Probability (%)": [0, 0]
+            })
+        )
+
+    # Call software
+    # ===========================================================
     global model, div_model, div_tokenizer, bi_model, bi_tokenizer
 
     # =====================================================================
@@ -91,29 +111,9 @@ def evaluate(text):
     for f in biscope_features:
         diveye_features.append(f)
 
-    return model.predict_proba([diveye_features])[:, 1][0].item()
+    ai_prob = model.predict_proba([diveye_features])[:, 1][0].item()
 
-def detect_ai_text(text):
-    global loaded, diveye, biscope, model
-    if not loaded:
-        return "❗ Model not loaded. We require a GPU to run DivEye.", 0.0, pd.DataFrame({
-            "Source": ["AI Generated", "Human Written"],
-            "Probability (%)": [0, 0]
-        })
-    
-    text = text.strip()
-    if not text or len(text.split()) < 15:
-        return (
-            "❗ Please enter some text with at least 15 words.",
-            0.0,
-            pd.DataFrame({
-                "Source": ["AI Generated", "Human Written"],
-                "Probability (%)": [0, 0]
-            })
-        )
-
-    # Call software
-    ai_prob = evaluate(text)
+    # ===========================================================
     human_prob = 1 - ai_prob
 
     if ai_prob > 0.7: