romiras

"""
This demo program outputs raw SQL query by analyzing table, which is run by agent executer, via SQL adapter.
"""

import os
import sqlite3
from langchain.agents import *
from langchain.sql_database import SQLDatabase
from langchain.chains import create_sql_query_chain
from langchain_community.llms import OpenAI

romiras

Я: 
расскажи про проблемы языков программирования C, C++, C# в стиле хайку
ИИ: 
Конечно, в стиле хайку:

C и C++: Память - дикая, Утечки, ошибки, страх. Указатели власть.

C#: Графика, сети, Управляй, безопасность. .NET, удобство.

romiras

version: "3"

services:
  opensearch:
    image: opensearchproject/opensearch:${OPENSEARCH_VERSION}
    restart: "${OPENSEARCH_RESTART:-unless-stopped}"
    environment:
      - cluster.name=opensearch-cluster
      - node.name=opensearch-node1
      - discovery.type=single-node

romiras

# using ripgrep on macos
for f in $(rg --files-with-matches -F '2.7.6/'); do sed -i '' 's/\/2\.7\.6\//\/2\.7\.7\//' $f; done

romiras

require_relative './logging'
require_relative './async_consumer'

def drain(data_store, queue_name, output_filename)
  json_store = File.open(output_filename, 'a')

  executor = lambda do |class_name, args|
    Logging.logger.info "class_name: #{class_name}, args: #{args}"

    json_store.write("#{ { class: class_name, args: args }.to_json }\n")

romiras

require 'concurrent'
require 'benchmark'
require 'logger'

module Logging # Credits: https://stackoverflow.com/a/6768164/10118318
  # This is the magical bit that gets mixed into your classes
  def logger
    Logging.logger
  end

romiras

# Concurrently classify items by type and batch them with multiple workers

require 'logger'

NUM_WORKERS = 10
NUM_ITEMS = 12
NUM_ITERATIONS = 5000

Item = Struct.new(:id, :type)

romiras

split --verbose -l1000 dataset-bulk-30k.ndjson bulk.

for f in bulk.??; do echo $f; curl -i -X POST localhost:9200/_bulk -H "Content-Type: application/x-ndjson" --data-binary @$f; done

romiras

# Reads .jsonl file and transforms it into file ready for bulk import to ES.

require 'json'

File.open(ARGV[1], 'wb') {|f|
  ARGF.each_line { |line|
    a = JSON.parse(line)
    out = {
      index: {
        "_id": a["_id"],

romiras

require 'concurrent'
require 'benchmark'

max = 20  # number of tasks to process
n_workers = 4  # number of concurrent workers
results = []  # 
lambda = -> (iter, i) { results << ('%04d' % i); d = rand(0.005)+0.001; puts("Iteration #{iter}. sleep %.3f" % d); sleep(d) }
workers = Array.new(n_workers, lambda)
iter = 0