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handler.py

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+from typing import Dict, List, Any
+from transformers import MarianMTModel, MarianTokenizer
+
+
+class EndpointHandler:
+    def __init__(self, path: str = ""):
+        self.tokenizer = MarianTokenizer.from_pretrained(path)
+        self.model = MarianMTModel.from_pretrained(path)
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, str]]:
+        inputs = data.get("inputs", "")
+        
+        if isinstance(inputs, str):
+            inputs = [inputs]
+        
+        encoded = self.tokenizer(inputs, return_tensors="pt", padding=True, truncation=True)
+        translated = self.model.generate(**encoded)
+        decoded = self.tokenizer.batch_decode(translated, skip_special_tokens=True)
+        
+        return [{"translation_text": text} for text in decoded]