Update handler.py

handler.py

@@ -43,13 +43,20 @@ class EndpointHandler:
         # --- image embedding ---------------------------------
         img = Image.open(io.BytesIO(base64.b64decode(img_b64))).convert("RGB")
         img_in = self.processor(images=img, return_tensors="pt").to(self.device)
+       
         with torch.no_grad(), torch.cuda.amp.autocast():
             img_feat = self.model.get_image_features(**img_in)
+        
         img_feat = img_feat / img_feat.norm(dim=-1, keepdim=True)
-
-        # --- similarity & softmax (identical to local) -------
+        txt_feat = txt_feat / txt_feat.norm(dim=-1, keepdim=True)
+        
+        img_feat = img_feat.float()   #  ← add these two lines
+        txt_feat = txt_feat.float()   #  ←
+        
         probs = (100 * img_feat @ txt_feat.T).softmax(dim=-1)[0].tolist()
 
+       
+
         return [
             {"label": p, "score": float(s)}
             for p, s in sorted(zip(prompts, probs), key=lambda x: x[1], reverse=True)