Keshav13142

{
  "version": "3.0.5",
  "settings": {
    "applyvideofilters": false,
    "backdropcolor": "#000000",
    "backdropopacity": 100,
    "blackbars": false,
    "blockautoplay": true,
    "blockhfrformats": false,
    "blockwebmformats": false,

Keshav13142

" Have j and k navigate visual lines rather than logical ones
nmap j gj
nmap k gk

" Go to beginning/end of line
nmap gh ^
nmap gl $

" Cycle between tabs
exmap tabprev obcommand workspace:previous-tab

Keshav13142

{
  "settingsVersion": "1.67.7",
  "exclusionRules": [
    {
      "pattern": "https?://mail.google.com/*",
      "passKeys": ""
    },
    {
      "pattern": "https?://www.google.com/*",
      "passKeys": "/"

Keshav13142

Git basics

• Setup Git

  • Install git
  • Configure name, email for commits

     git config --global user.name "Your name"
     git config --global user.email [email protected]

Keshav13142

"source ~/.vimrc
" Find more examples here: https://jb.gg/share-ideavimrc

let mapleader=" "

" Don't use Ex mode, use Q for formatting.
map Q gq

set number relativenumber
set clipboard+=unnamed

Keshav13142

import os
import sqlite3

import requests
from datasets import DatasetDict, load_dataset
from dotenv import load_dotenv
from flask import Flask, jsonify, redirect, render_template, request
from transformers import (
    DataCollatorForLanguageModeling,
    GPT2LMHeadModel,

Keshav13142

Question

I want you to generate a prompt which I will use to query a LLM to generate care plan data in JSON format using certain parameters I will pass in the query such as weight, height, spo2, avg_heartrate, stepCount, calories_burnt, sleep_duration_in_minutes which is the the average a daily data collected over a week. The output json format should be as follows: { "name": "<careplan_name>", "careplanItems": [ { "title": "careplan_item_title1", "description": "careplan_item_description1"

Keshav13142

import os
import sqlite3

from datetime import datetime, timedelta
import requests
from datasets import DatasetDict, load_dataset
from dotenv import load_dotenv
from flask import Flask, jsonify, redirect, render_template, request
from transformers import (
    DataCollatorForLanguageModeling,

Keshav13142

app.py

import os
import pickle
import sqlite3

import google.generativeai as genai
import markdown
import numpy as np

Keshav13142

# Yaml is white-space sensitive (use 2 spaces to indent).

###
# Define a new window with an id of 'bar'. This window can then be opened
# via the Zebar cli by running 'zebar open bar --args <ARGS...>'.
#
# Docs regarding window: https://some-future-docs-link.com
window/bar:
  providers: ["self"]
  # Width of the window in physical pixels.