Update model.py

model.py

@@ -24,9 +24,23 @@ class SuicidalIntentModel:
         self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
         self.model = AutoModelForSequenceClassification.from_pretrained(self.model_name)
 
-    def predict(self, text):
+    def _score_text(self, text):
         inputs = self.tokenizer(text, return_tensors="pt", truncation=True, padding=True)
         with torch.no_grad():
             logits = self.model(**inputs).logits
         probs = torch.nn.functional.softmax(logits, dim=1)
         return float(probs[0][1])  # Probability of suicidal intent
+
+    def predict(self, text, window_size=20, stride=10):
+        tokens = self.tokenizer.tokenize(text)
+        if len(tokens) <= window_size:
+            return self._score_text(text)
+
+        scores = []
+        for i in range(0, len(tokens) - window_size + 1, stride):
+            window_tokens = tokens[i:i + window_size]
+            window_text = self.tokenizer.convert_tokens_to_string(window_tokens)
+            score = self._score_text(window_text)
+            scores.append(score)
+
+        return max(scores, default=0.0)