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#
# LlamaIndex Starter Example with DBRX
#

# Based on the LlamaIndex Starter Example
# https://docs.llamaindex.ai/en/stable/getting_started/starter_example/
#
# Ensure you have installed both llama_index and Databricks integration
# e.g., pip install llama_index llama-index-llms-databricks
# 

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Chat GPT "DAN" (and other "Jailbreaks")

• https://chat.openai.com/
• Is ChatGPT "DAN" Real? Gonna find out [Part 1]
  (https://www.youtube.com/watch?v=-q8woRG9FrI)
• Part 2: I thought ChatGPT DAN was a hoax, but...
  (https://www.youtube.com/watch?v=rHZRrDu3A2U&lc=UgxfrxX8aK7gnCzkend4AaABAg)

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import openai
import asyncio
from typing import Any

async def dispatch_openai_requests(
    messages_list: list[list[dict[str,Any]]],
    model: str,
    temperature: float,
    max_tokens: int,
    top_p: float,

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/*
 
 File: Reachability.h
 Abstract: Basic demonstration of how to use the SystemConfiguration Reachablity APIs.
 
 Version: 2.2 - ARCified
 
 Disclaimer: IMPORTANT:  This Apple software is supplied to you by Apple Inc.
 ("Apple") in consideration of your agreement to the following terms, and your
 use, installation, modification or redistribution of this Apple software

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Klipper mesh on print area only install guide

What this macro do

• This macro will dymanic change the bed_mesh area based on the size of the printed part. The fw will only probe on the area that the part will be printed (plus mesh_area_offset value)

Setup guide

• (1) Add the following macrro to your printer config, this will replace the default BED_MESH_CALIBRATE command.

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/* 
    The original files are 960x319.
    
    Image sizes to save:
    
    * 800x266 - Retina for 480x320 resolution (400 logical pixel wide panel areas)
    * 740x246 - Desktop and iPad
    * 616x205 - Retina for 320x480 resolution (308 logical pixel wide panel areas)
    * 400x133 - 480x320 resolution
    * 308x102 - 320x480 resolution

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def knapsack_aux(x: (Int, Int), is: List[Int]): List[Int] = {
  for {
    w <- is.zip(is.take(x._1) ::: is.take(is.size - x._1).map(_ + x._2))
  } yield math.max(w._1, w._2)
}

def knapsack_rec(xs: List[(Int, Int)], is: List[Int]): List[List[Int]] = {
  xs match {
    case x :: xs => knapsack_aux(x, is) :: knapsack_rec(xs, knapsack_aux(x, is))
    case _ => Nil

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# coding=UTF-8
from __future__ import division
import nltk
import re
import requests

# Add your freebase key here
# If you don't have one, register at https://code.google.com/apis/console
FREEBASE_KEY = ""

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"""
An implementation of the `Local reparameterization trick`
from Kingma & Wellings and 
Bayesian RNN 
from Fortunato, Blundell & Vinyals
"""
import os
import time
import copy
from os.path import join as pjoin

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Elasticsearch CLI

Experimental CLI interface for the helpers in the python library.

Main purpose is to expose the bulk functionality to enable rapid loading of data into an elasticsearch cluster. Combined with the scan command it can also be used to reindex data from elasticsearch into a different index or cluster.