Update textPreprocess.py

textPreprocess.py

@@ -55,7 +55,8 @@ except Exception as e:
 @torch.inference_mode()
 def predict_text(text: str, max_length: int | None = None):
     if model is None or tokenizer is None:
-        return {"predicted_class": "Human", "confidence": 0.0}
+        print("Issue 1")
+        return {"predicted_class": "Human", "confidence": -100.0}
 
     if max_length is None:
         max_length = MAX_LEN
@@ -70,13 +71,14 @@ def predict_text(text: str, max_length: int | None = None):
         return {"predicted_class": label, "confidence": float(probs[pred_id])}
     except Exception as e:
         print(f"Error during text prediction: {e}")
-        return {"predicted_class": "Human", "confidence": 0.0}
+        return {"predicted_class": "Human", "confidence": -100.0}
 
 # ── 4) Batch (optional) ────────────────────────────────────────────────────────
 @torch.inference_mode()
 def predict_batch(texts, batch_size=16):
     if model is None or tokenizer is None:
-        return [{"predicted_class": "Human", "confidence": 0.0} for _ in texts]
+        print("Issue 2")
+        return [{"predicted_class": "Human", "confidence": -100.0} for _ in texts]
 
     results = []
     for i in range(0, len(texts), batch_size):