jalotra

{
    "data": {
        "about": "Backend Engineer with expertise in writing scalable distributed systems.\nI have implemented\n1. stateless REST layers that scale upwards of 30K QPS.\n2. spark jobs that handle ~1 billion events in a BBD day\n3. wrote a prompt as a service on top of llama2 models and mixtral to get metrics on different prompting patterns, made the service self serve.\n4. worked on NFRs of our rest layers and spark jobs, did mem, cpu profiling.",
        "certifications": [],
        "city": "Bengaluru",
        "company": "Stealth Mode",
        "company_description": "Currently working on something new and very exciting",
        "company_domain": "",
        "company_employee_range": "1001-5000",
        "company_industry": "Software Development",

jalotra

{
  "2741835855": {
    "labels": {
      "spinal_canal_stenosis_l1_l2": "Normal/Mild",
      "spinal_canal_stenosis_l2_l3": "Normal/Mild",
      "spinal_canal_stenosis_l3_l4": "Normal/Mild",
      "spinal_canal_stenosis_l4_l5": "Normal/Mild",
      "spinal_canal_stenosis_l5_s1": "Normal/Mild",
      "left_neural_foraminal_narrowing_l1_l2": "Normal/Mild",
      "left_neural_foraminal_narrowing_l2_l3": "Normal/Mild",

jalotra

import requests
import json 


addresses = [{
        "street_name": "Sarjapur Road",
        "address_detail": "Silver Spring",
        "postal_code": "560035",
        "city": "Bengaluru",
        "region": "KA",

jalotra

from typing import List
from pathlib import Path
import pathlib
import os
import random

DATA_FOLDER = "../data"


def strip_line(line: List[str]):

jalotra

{"2690161683": {"labels": {"spinal_canal_stenosis_l1_l2": "Normal/Mild", "spinal_canal_stenosis_l2_l3": "Normal/Mild", "spinal_canal_stenosis_l3_l4": "Normal/Mild", "spinal_canal_stenosis_l4_l5": "Normal/Mild", "spinal_canal_stenosis_l5_s1": "Normal/Mild", "left_neural_foraminal_narrowing_l1_l2": "Normal/Mild", "left_neural_foraminal_narrowing_l2_l3": "Normal/Mild", "left_neural_foraminal_narrowing_l3_l4": "Normal/Mild", "left_neural_foraminal_narrowing_l4_l5": "Normal/Mild", "left_neural_foraminal_narrowing_l5_s1": "Normal/Mild", "right_neural_foraminal_narrowing_l1_l2": "Normal/Mild", "right_neural_foraminal_narrowing_l2_l3": "Normal/Mild", "right_neural_foraminal_narrowing_l3_l4": "Normal/Mild", "right_neural_foraminal_narrowing_l4_l5": "Normal/Mild", "right_neural_foraminal_narrowing_l5_s1": "Normal/Mild", "left_subarticular_stenosis_l1_l2": "Normal/Mild", "left_subarticular_stenosis_l2_l3": "Moderate", "left_subarticular_stenosis_l3_l4": "Severe", "left_subarticular_stenosis_l4_l5": "Severe", "left_subar

jalotra

{
  "status": "success",
  "data": {
    "conversation": {
      "uuid": "CONV-b0e2bcf4-f909-4bfa-a361-d1ffeac2a604",
      "workspaceId": 13262382,
      "createdAt": "2024-05-22T13:13:43.379Z",
      "projectId": 38877338,
      "context": {}
    },

jalotra

{
  "company_data": {
    "company": {
      "business_challenges": "Here are the top three business challenges discussed in the OKTA earnings call:\n\n1. **Security Incident and Its Aftermath**:\n   - The company experienced a security incident in October, which required significant effort to manage and mitigate. Although the incident is now behind them, it had some unquantifiable impact on Q4 results. The company is using the learnings from this incident to reassess and strengthen its security infrastructure and customer policies through initiatives like the Okta Secure Identity Commitment and Project Bedrock.\n\n2. **Reigniting Growth**:\n   - OKTA is focused on reigniting growth, which has decelerated. This involves improving go-to-market operational excellence, increasing competitiveness in core markets, and enhancing growth vectors in key industries and newly introduced products. Specific strategies include shifting the direct sales team to a hunter-farmer model to drive new customer acquisition and ups

jalotra

from .tree_structures import Tree, Node
from igraph import Graph, EdgeSeq
import plotly.graph_objects as go
import pickle
from ..routes.DocumentRoutes import read_redis_document
from ..routes.DocumentRoutes import get_redis_db

# Formats data so that plotly can plot it better, 
# each line should have less than 80 characters and 

jalotra

CREATE TABLE Org
(
  id INT NOT NULL AUTO_INCREMENT,
  marketplace VARCHAR NOT NULL,
  created_at DATE NOT NULL,
  updated_at DATE NOT NULL,
  PRIMARY KEY (id)
);

CREATE TABLE Surveyor

jalotra

*{
    margin: 0;
    padding: 0;
    box-sizing: border-box;
    font-family: 'Poppins', sans-serif;
}
body{
    min-height: 100vh;
    display: flex;
    align-items: center;