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from typing import Dict, List, Any
from transformers import pipeline
import holidays
import sys
import os
class EndpointHandler:
def __init__(self, path=""):
self.pipeline = pipeline("text-classification", model=path)
self.holidays = holidays.US()
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
inputs (:obj: `str`)
date (:obj: `str`)
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
os.system('echo $PWD')
os.system('python --version')
os.system('python3 --version')
os.system('ls')
os.system('ls huggingface_inference_toolkit')
os.system('ps -ef')
os.system('uname -a')
os.system('cat webservice_starlette.py')
# get inputs
inputs = data.pop("inputs", data)
# get additional date field
date = data.pop("date", None)
# check if date exists and if it is a holiday
if date is not None and date in self.holidays:
return [{"label": "happy", "score": 1}]
# run normal prediction
prediction = self.pipeline(inputs)
return prediction
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