shreyaskarnik

# This example script showcases how to use llama_cpp to run inference
# and use langchain tools
# please install langchain first: pip install langchain
# this example uses https://github.com/MeetKai/functionary/pull/93 as the basis to demonstrate use of langchain tools.

import asyncio
import json
from typing import List

from huggingface_hub import hf_hub_download

shreyaskarnik

# Copyright © 2023 Apple Inc.
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple

import mlx.core as mx
import mlx.nn as nn
from mlx.utils import tree_map, tree_unflatten

shreyaskarnik

package main

import (
	"bufio"
	"errors"
	"fmt"
	"io"
	"net"
	"os"
	"os/signal"

shreyaskarnik

Keybase proof

I hereby claim:

• I am shreyaskarnik on github.
• I am shreyask (https://keybase.io/shreyask) on keybase.
• I have a public key ASCvEj96FbVC0-4GgTHpiTMXxd2QfMfEiAZf-qSj8kkM5wo To claim this, I am signing this object:

{
  "body": {
    "key": {

shreyaskarnik

#ipython_notebook {
    height: 40px !important;
}
#ipython_notebook img{                                                                                        
    display:block;
    background: url(logo.png) no-repeat;    
    background-size: contain;
    width: 233px;
    height: 33px;
    padding-left: 233px;

shreyaskarnik

Keybase proof

I hereby claim:

• I am shreyu86 on github.
• I am shreyask (https://keybase.io/shreyask) on keybase.
• I have a public key whose fingerprint is 3348 CCD4 3ADF DDD8 948D F9BE 46BD E9D8 91DB 4C6E

To claim this, I am signing this object:

shreyaskarnik

homeassistant:
  # Name of the location where Home Assistant is running
  name: Home
  # Location required to calculate the time the sun rises and sets
  # Impacts weather/sunrise data (altitude above sea level in meters)
  elevation: 180
  # metric for Metric, imperial for Imperial
  unit_system: metric
  # Pick yours from here: http://en.wikipedia.org/wiki/List_of_tz_database_time_zones
  time_zone: America/Chicago

shreyaskarnik

body {
  white-space: pre;
  font-family: 'Ubuntu Mono';
  font-size: 16px;
  line-height:20px;
  color: white;
  background-color: #2B2A27;
}

.property {

shreyaskarnik

• With Docker 1.8.0 shipped new log-driver for GELF via UDP, this means that the logs from Docker Container(s) can be shipped directly to the ELK stack for further analysis.
• This tutorial will illustrate how to use the GELF log-driver with Docker engine.
• Step 1: Setup ELK Stack:
  • docker run -d --name es elasticsearch
  • docker run -d --name logstash --link es:elasticsearch logstash -v /tmp/logstash.conf:/config-dir/logstash.conf logstash logstash -f /config-dir/logstash.conf
  • Note the config for Logstash can be found at this link
  • docker run --link es:elasticsearch -d kibana
• Once the ELK stack is up now let's fire up our nginx container which ships its logs to ELK stack.

• LOGSTASH_ADDRESS=$(docker inspect --format '{{ .NetworkSettings.IPAddress }}' logstash)
• `docker run -d --net=host --log-driver=gelf --log-opt gelf-address=u

shreyaskarnik

input {
  gelf {}
}
output {
  elasticsearch {
        host => "elasticsearch"
        protocol => "http"
        workers=> 10
        }
  stdout {