thisisarjuns

import rapidfuzz


def get_confidence_lv(init_data_name: str, document_name: str) -> float:
    edit_distance = rapidfuzz.distance.Levenshtein.distance(init_data_name, document_name)
    similarity = 1 - (edit_distance / max(len(init_data_name), len(document_name)))
    return round(similarity, 2)

input = [
    ("Arjun", "Arjun" ), 

thisisarjuns

[
  [
    {
      "created_at": "2023-01-02T12:47:24.779041",
      "data": {
        "aws_response": {
          "FaceDetails": [
            {
              "AgeRange": {
                "High": 42,