Revert BERT label to probs[0][0] (correct AI index), expose perplexity in response schema

api/schemas.py

@@ -76,6 +76,14 @@ class AnalyzeResponse(BaseModel):
     chunks_analyzed: int
     word_count: int
     character_count: int
+    perplexity: Optional[float] = Field(
+        default=None,
+        description="Raw GPT-2 perplexity score (lower = more AI-like)"
+    )
+    perplexity_score: Optional[float] = Field(
+        default=None,
+        description="Perplexity converted to 0-1 AI probability"
+    )
 
 
 class BatchAnalyzeResponse(BaseModel):

core/bert_scorer.py

@@ -155,8 +155,9 @@ class BertScorer:
 
         probs = torch.softmax(outputs.logits, dim=-1)
 
-        # LABEL_1 = AI probability
-        ai_prob = probs[0][1].item()
+        # LABEL_0 = AI probability for gouwsxander/slop-detector-bert
+        # (verified: probs[0][0] gives higher scores on known AI text)
+        ai_prob = probs[0][0].item()
         return ai_prob
 
     def score_text(self, text: str) -> dict: