harmonizing with template on huggingface to solve errors

handler.py

@@ -1,4 +1,4 @@
-from typing import  Dict
+from typing import Dict, List, Any
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
@@ -8,8 +8,8 @@ class EndpointHandler():
         self.model = AutoModelForCausalLM.from_pretrained("chuckfinca/arithmephi", torch_dtype="auto", trust_remote_code=True)
         self.tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
 
-    def __call__(self, data: Dict[str, str]) -> str:
-        input = data.get("input", data)
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        input = data.get("inputs", data)
         inputs = self.tokenizer(input, return_tensors="pt", return_attention_mask=False)
         outputs = self.model.generate(**inputs, max_length=len(inputs[0]) + 8, pad_token_id=self.tokenizer.eos_token_id)
         text = self.tokenizer.batch_decode(outputs)[0]