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Н Новости

Локальные LLM в разработке: а почему бы и да?

Меня зовут Антон Гращенков, и я занимаюсь развитием Java в Альфа-Банке. Программированием увлекаюсь ещё со школы: писал на множестве разных языков — от Pascal до TypeScript, мне это просто нравится. В статье я на примерах покажу, для каких задач я использую локальные модели. Да, существует много инструментов доступных в облаке, — тот же ChatGPT, Copilot или YandexGPT. Однако можно запустить такую модель и локально, и сделать это крайне просто.

Ведь если хочется, то почему бы и да?

Вступление

Развитие ИИ и, в частности, генеративных сетей — это примерно такой же сдвиг парадигмы, как изобретение электронных таблиц. Если помните эту историю, электронные таблицы позволили за минуты осуществлять сложные расчеты, которые раньше требовали недель кропотливого труда. И нейросети в этом плане предлагают нам такой же буст эффективности.

Поэтому так же, как сейчас сложно найти человека в ИТ, который не умел бы пользоваться электронным таблицами, так и в скором времени не будет тех, кто не умеет эффективно использовать ИИ.

И если в целом с ИИ все понятно, то почему именно локальные модели?

Плюсы локальной работы.

Офлайн. Все локальные модели работают в офлайне и вам не нужен интернет, чтобы ими пользоваться. В дороге, в самолёте, в поезде и на даче — везде, в любом месте, куда вы можете принести свой ноутбук, вы можете использовать ИИ.
Приватность. Если вы используете локальную модельку, то никакие ваши данные ни на какие серверы не отправляются. Для кого-то это важно.
Политика безопасности компании. Этот пункт напрямую вытекает из предыдущего. Для работы с кодом этот самый код часто нужно отправлять в контексте запроса, и ваша компания может напрямую это запрещать.
Это бесплатно. При использовании локальной модели, вам не нужно платить за токены при использовании API или оформлять платные подписки. Платим только за ноутбук и за электроэнергию, естественно.

Минусы локальной работы.

Естественно, локальные модели имеют ряд очень существенных ограничений.

Ресурсы. Чем умнее модель, тем больше ресурсов она потребляет. Я подчеркну — они МНОГО «кушают». И чем умнее модель, тем больше она, соответственно, потребляет. Так что может потребоваться обновить компьютер «для работы» (да и видеокарту тоже).
Скорость. Она не очень велика. Если вы у GPT что-то спросите, то ожидаете, что она вам ответит мгновенно. Ответа локальной модели придётся подождать какое-то время. Особенно на большом контексте и слабом железе.
Точность. Мало того, что придётся ждать, так и точность ответа может быть невысокой, поэтому нужно всегда тщательно проверять, что она нам говорит. Локал-модельки не очень точные и могут изрядно фантазировать, что случается с большими сетями всё реже.
Язык. Доступные модели, как правило, обучаются на англоязычных данных, так что общаться с ними лучше на английском. Можно использовать для запросов и русский язык, но точность может пострадать. Лучше, наверное, подучить английский язык.

Теперь к инструментарию.

Мы будем использовать Ollama. Она позволяет нам загружать различные модели и запускать их локально. Список самих моделек есть на их сайте, их много, и они постоянно обновляются. Следите за новостями и пробуйте что-то новое.

Если хотите какой-то красивый графический интерфейс и дополнительные возможности, например, подгружать документы в контекст или использовать векторные базы данных, можно поставить себе Anything.

И, конечно, нам, как разработчикам, важно, чтобы наш чатик работал в той IDE, которой мы пользуемся. Мне очень нравится Continue.dev: он доступен для IntelliJ IDEA и VS Code.

Давайте посмотрим как всё настроить и начать пользоваться.

Установка и настройка

Первое, что нам нужно сделать, — поставить Ollama. На Mac все достаточно просто:

brew install ollama

Для остальных операционных систем всё тоже весьма просто, например на Linux достаточно выполнить:

curl -fsSL https://ollama.com/install.sh | sh

После этого нужно будет загрузить модели. Моделей много, они доступны на официальном сайте — достаточно знать их названия.

Начать можно, например, с этих четырёх:

llama3 — модель общего назначения от Meta;
mistral — модель общего назначения от Mistral AI;
codellama — модель для работы с кодом от Meta;
codegemma — модель для работы с кодом от Google.

Модели отличаются по количеству параметров. Чем их больше, тем модель умнее, но для локального запуска оптимальны модели с 7–8 миллиардами параметров, то есть 7–8 b.

Ставятся модели очень просто — командой:

ollama pull llama3

Здесь llama3 — название модели с сайта.

Мы ставим сразу несколько моделей, потому что у разных моделей свои сильные стороны. Например, Mistral и llama3 хорошо работают просто с текстом (суммаризация, генерация текстов по заданному шаблону), а codellama или codegemma специализируются на работе с кодом.

Чтобы Ollama начала работать с нашими локальными клиентами, нужно запустить её в режиме сервера. Сделать это можно командой:

ollama serv

А можно запустить её в режиме сервиса, что ещё лучше. На Mac запуск сервера в режиме сервиса происходит командой:

brew services start ollama

Так Ollama всегда будет запущена и готова к работе.

Последняя из настроек — настройка continue.dev, это плагин для нашей IDE. Хранятся они в ~/.continue/config.json Достаточно лишь изменить секцию models вот так:

"models": [
  {
    "title": "Ollama",
    "provider": "ollama",
    "model": "AUTODETECT"
  }
]

Мы используем провайдер ollama и название модели. Можно перечислить все модельки, которые вы хотите использовать, или оставить автодетект, и тогда их можно будет выбирать из всех, что вы скачали и установили.

По настройкам всё — можно начинать пользоваться.

Как использовать

Использовать Ollama можно несколькими способами.

Запустить модель можно при помощи команды ollama run llama3. При этом мы перейдём в режим интерактивного чата: пишем свой вопрос и получаем ответ.
Можно задавать вопросы в неинтерактивном режиме. Для этого передаём вопрос в качестве параметра ollama run llama3 ‘what is java?’.
Также можно писать собственных агентов, общаясь с Ollama при помощи REST API.
И, конечно же, можно использовать плагин в вашей любимой IDE. Он предоставляет окно чата, в которое можно вводить запросы.

Теперь посмотрим в каких сценариях мы можем использовать Ollama?

№1. Работа с утилитами, формат запросов которых я плохо помню

Например, я плохо помню формат запросов jq, и когда приходится с ним работать, я всё время читаю документацию.

Допустим, я получил выгрузку с какими-то темами в JSON-файле и хочу отфильтровать темы, у которых лайков больше чем дизлайков.

[
  {
    "name": "Как установить LLM локально",
    "like": 2,
    "dislike": 1
  },
  {
    "name": "Пишем сортировку пузырьком 3 способами",
    "like": 1,
    "dislike": 5
  },
  {
    "name": "Как делегировать всю работу ИИ и зарабатывать миллион в час",
    "like": 9,
    "dislike": 2
  },
  {
    "name": "Можно ли программировать прямо в баше?",
    "like": 4,
    "dislike": 4
  },
  {
    "name": "Подключаем ChatGPT к vim",
    "like": 7,
    "dislike": 3
  },
  {
    "name": "Автоматичесоке преобразование JavaScript в Java",
    "like": 9,
    "dislike": 0
  }
]

Собственно, запускаем модель:

ollama run llama3

Формулируем запрос:

I have an array of elements like { “name”: “My Name”, “like”: 2, “dislike”: 1}. Write a jq query to filter elements which have likes more than dislikes, show only element’s name.

На одни и те же промпты разные модели отвечают по-разному. Иногда можно получить что-то странное, иногда что-то хорошее. Но llama3, в принципе, справляется неплохо. Работа с с языковыми моделями — это не тоже самое, что программирование: для одного и того же «кода» результат может быть разный.

В итоге я получил вот такой ответ.

You can use the following `jq` command:

```bash
jq '.[] | select(.like > .dislike) | .name' your_array.json
```

Here's how it works:

- `.[]` iterates over each object in the array.
- `select(.like > .dislike)` filters out objects where likes are not greater than
dislikes. The `.` refers to the current object being processed.
- `.name` extracts and prints only the "name" value from the filtered objects.

Replace `your_array.json` with the actual path to your JSON file or input string.

И это корректная команда, можете убедиться сами!

№2. Работа с утилитами, для которых я плохо помню формат конфигурационных файлов

Это могут быть, например Dockerfile, Makefile или docker-compose.yaml. И вместо того, чтобы каждый раз гуглить синтаксис, можно использовать Ollama.

ollama run codegemma 'Write a docker-compose file. It should contain mongodb and minio. Map their ports to local machine. Add volumes to store data. Do not provide an explanation, just code.' > docker-compose.yaml

Здесь есть пара интересных моментов.

Первый. Я запустил Ollama не в интерактивном режиме, а просто как команду. Это даёт нам возможность использовать Ollama для автоматизации рутины. Например, можно генерировать тестовые данные или какие-то каркасы классов.
Второй. Это директива Do not provide an explanation, just code. Я прошу модель, чтобы она не генерировала пояснения к тому, что сделала. Так я могу перенаправить ответ в файл и получить готовый результат. Правда, иногда она всё же добавляет кавычки, чтобы оформить ответ в виде блока кода в Markdown.

И вот что я получил в результате.

version: "3.8"

services:
  mongodb:
    image: mongo:latest
    restart: unless-stopped
    ports:
      - 27017:27017
    volumes:
      - mongodb_data:/data/db

  minio:
    image: minio/minio:latest
    restart: unless-stopped
    ports:
      - 9000:9000
      - 9001:9001
    volumes:
      - minio_data:/data

volumes:
  mongodb_data:
  minio_data:

А теперь давайте посмотрим что-нибудь ближе к коду.

№3. Чтение кода

Я, конечно, пишу бэкенд, но нет-нет да и приходится посмотреть, что там происходит на фронтэнде. Если вы не очень хорошо знаете JavaScript/TypeScript, то читать его может быть достаточно непросто. И наш ассистент может помочь с этой проблемой.

На этот раз воспользуемся Visual Studio Code. Выделяем весь код, жмём Cmd-L и просим объяснить как работает код:

explain this code

Сам код при этом добавится в контекст запроса, и, немного подумав, модель выдаст свои пояснения.

Модель достаточно точно описывает что это код для разграничения доступа на основе белых списков и что для хранения пользователей используется MongoDB с библиотекой Mongoose.

Она описывает достаточно много подробностей, которых нет в коде. То есть они есть, но завуалированы. Мы, программисты, знаем, что правильно названные переменные — половина смысла в нашей программе. И моделька понимает этот смысл. Понятное дело, что не так же хорошо, как мы, но примерно.

№4. Собственные ИИ агенты

Ну и, конечно, самое интересное — это использовать API для разработки собственных ИИ-агентов, которым можно поручить выполнение рутинных действий. С точки зрения программирования всё предельно просто: Ollama предоставляет REST API (по умолчанию на 11434 порту), в котором нам достаточно пары эндпоинтов. Давайте посмотрим, как это можно использовать.

Наверняка вы уже сталкивались с современными эмуляторами терминала, такими как Warp, у которых есть встроенный ИИ-помощник. Он преобразует запросы на естественном языке в команды, которые можно выполнить в терминале. Давайте сделаем так же, но для любого терминала и при помощи локальной LLM.

Для начала разберёмся с API. На GitHub есть подробная документация, так что разобраться не составит труда. Нам нужен метод api/generate, так как мы не собираемся общаться с моделью в режиме диалога, а хотим получить единственный ответ.

Сгенерировать основную часть кода можно при помощи Ollama. Это будет быстрее, а заодно продемонстрирует, как можно использовать модель для написания программ на языке, который мы не очень хорошо знаем. В качестве языка выберем Go, и, так как пишу я на нём не особо часто, Ollama придётся помогать. Промпт достаточно большой и подробный, но это позволит получить код, максимально близкий к тому, что хочется.

Write a program in go language. Generate only code, no explanations. Write a program to send http post request to local ollama server on port 11434. Endpoint is /api/generate. Payload is in json format and has fields model, prompt, system and stream. Get prompt from command line arguments, system and model from const. Set stream to false. Response is in json format and looks like

{ "model": "llama3", "created_at": "2023-08-04T19:22:45.499127Z", "response": "", "done": true, "context": [1, 2, 3], "total_duration": 10706818083, "load_duration": 6338219291, "prompt_eval_count": 26, "prompt_eval_duration": 130079000, "eval_count": 259, "eval_duration": 4232710000 }.

Create and use struct types for the payload and response. Unmarshall the response and print "response" field.

В результате получим заготовку для нашего агента. Она, конечно, не идеальна, но компилируется, работоспособна, решает проблему «чистого листа», и её можно доработать так, как нам хочется.

Вот что у меня получилось:

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"log"
	"net/http"
	"os"
	"time"
)

type Payload struct {
	Model  string `json:"model"`
	Prompt string `json:"prompt"`
	System string `json:"system"`
	Stream bool   `json:"stream"`
}

type Response struct {
	Model              string    `json:"model"`
	CreatedAt          time.Time `json:"created_at"`
	Response           string    `json:"response"`
	Done               bool      `json:"done"`
	Context            []int     `json:"context"`
	TotalDuration      int64     `json:"total_duration"`
	LoadDuration       int64     `json:"load_duration"`
	PromptEvalCount    int       `json:"prompt_eval_count"`
	PromptEvalDuration int64     `json:"prompt_eval_duration"`
	EvalCount          int       `json:"eval_count"`
	EvalDuration       int64     `json:"eval_duration"`
}

func main() {
	// Get prompt from command line arguments
	prompt := os.Args[1]

	// Set system and model from const
	system := "llama"
	model := "llama3"

	// Set stream to false
	stream := false

	// Create payload
	payload := Payload{
		Model:  model,
		Prompt: prompt,
		System: system,
		Stream: stream,
	}

	// Marshal payload to JSON
	jsonPayload, err := json.Marshal(payload)
	if err != nil {
		log.Fatal(err)
	}

	// Send HTTP POST request to local ollama server on port 11434
	resp, err := http.Post("http://localhost:11434/api/generate", "application/json", bytes.NewBuffer(jsonPayload))
	if err != nil {
		log.Fatal(err)
	}

	// Read response body
	body, err := io.ReadAll(resp.Body)
	println(string(body))
	if err != nil {
		log.Fatal(err)
	}

	// Unmarshal JSON response
	var response Response
	err = json.Unmarshal(body, &response)
	if err != nil {
		log.Fatal(err)
	}

	// Print "response" field
	fmt.Println(response.Response)
}

Приступим к доработкам.

Первое, что нужно сделать, — поменять system, то есть указания модели, как она должна себя вести. Наша модель должна знать, что мы хотим от неё получить и в каком виде. В нашем случае роль модели — системный администратор, который пишет команды для Bash, выполняющие то, что мне нужно.

И, конечно, нужны исключительно команды, без пояснений. Получается примерно так.

You are a system administrator. Write bash commands that do what I ask. Generate the commands and only the commands, no explanations or formatting. I want to copy your response directly to a terminal emulator and execute it.

Несмотря на просьбу не форматировать ответ, модель иногда возвращает ответы, окружённые кавычками, форматируя их в Markdown. Поэтому добавим небольшую обработку, которая удаляет эти кавычки из ответа.

Ну и, конечно, проведём небольшой рефакторинг, больше для собственного удовольствия. Я же говорил, что люблю писать код?

В итоге у меня получилось вот так:

package main

import (
	"bufio"
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"net/http"
	"os"
	"os/exec"
	"strings"
)

type Config struct {
	model  string
	system string
	url    string
}

func config() Config {
	return Config{
		model:  "codellama",
		system: "You are a system administrator. Write bash commands that do what I ask. Generate the commands and only the commands, no explanations or formatting. I want to copy your response direct to a terminal emulator and execute it.",
		url:    "http://localhost:11434/api/generate",
	}
}

type Response struct {
	Model              string `json:"model"`
	CreatedAt          string `json:"created_at"`
	Response           string `json:"response"`
	Done               bool   `json:"done"`
	Context            []int  `json:"context"`
	TotalDuration      int64  `json:"total_duration"`
	LoadDuration       int64  `json:"load_duration"`
	PromptEvalCount    int    `json:"prompt_eval_count"`
	PromptEvalDuration int64  `json:"prompt_eval_duration"`
	EvalCount          int    `json:"eval_count"`
	EvalDuration       int64  `json:"eval_duration"`
}

type Payload struct {
	Model  string `json:"model"`
	Prompt string `json:"prompt"`
	System string `json:"system"`
	Stream bool   `json:"stream"`
}

func main() {
	// Get the prompt from command line arguments
	prompt := os.Args[1]

	resp, err := sendAiRequest(prompt)
	if err != nil {
		fmt.Println("Can not generate prompt: ", err)
	}
	cmd := getCommand(resp.Response)
	fmt.Print(cmd)
}

func sendAiRequest(prompt string) (*Response, error) {
	cfg := config()

	payload := Payload{
		Model:  cfg.model,
		Prompt: prompt,
		System: cfg.system,
		Stream: false,
	}

	// Marshal the payload to JSON
	jsonPayload, err := json.Marshal(payload)
	if err != nil {
		fmt.Println("Error marshaling payload: ", err)
		return nil, err
	}

	// Send HTTP POST request to local ollama server on port 11434
	client := &http.Client{}
	req, err := http.NewRequest("POST", cfg.url, bytes.NewBuffer(jsonPayload))
	if err != nil {
		fmt.Println("Error creating request: ", err)
		return nil, err
	}
	req.Header.Add("Content-Type", "application/json")

	res, err := client.Do(req)
	if err != nil {
		fmt.Println("Error sending request: ", err)
		return nil, err
	}
	defer res.Body.Close()

	// Read response body
	body, err := io.ReadAll(res.Body)
	if err != nil {
		fmt.Println("Error reading response: ", err)
		return nil, err
	}

	// Unmarshal JSON response
	var response Response
	err = json.Unmarshal(body, &response)
	if err != nil {
		fmt.Println("Error unmarshaling response: ", err)
		return nil, err
	}

	return &response, nil
}

func getCommand(raw string) string {
	cmd := ""
	scanner := bufio.NewScanner(strings.NewReader(raw))
	for scanner.Scan() {
		line := scanner.Text()
		if strings.HasPrefix(line, "```") {
			continue // skip lines starting with ```
		}
		cmd += line + " "
	}
	cmd = strings.TrimSpace(cmd)
	if strings.HasPrefix(cmd, "`") && strings.HasSuffix(cmd, "`") {
		cmd = strings.TrimPrefix(cmd, "`")
		cmd = strings.TrimSuffix(cmd, "`")
	}
	return cmd
}

Скомпилируем получившееся при помощи go build и проверим, работает ли наш агент (я назвал его cli-ai).

Работает!

Осталось только настроить шелл. Я использую zsh, так что добавим функцию для вызова нашего агента и забиндю её на Ctrl-a, i добавив в ~/.zshrc следующий код.

function _ai() {
  prompt="'$BUFFER'"
  zle -R "Thinking about $prompt..."
  cmd=$(/Users/bidzo/develop/bidzo/go/ai-cli/cli-ai $prompt)
  BUFFER="$cmd"
  zle end-of-line
}
zle -N _ai
bindkey "^ai" _ai

Перезапускаем zsh и смотрим, как в шеле просыпается искусственный интеллект.

Как видите, написать своего простого агента не составляет труда, причем на любом языке, который вам нравится. Такой подход можно использовать для автоматизации любой рутины, главное — чётко представлять, какой результат вы хотите получить.

Итого

Как видите, на текущем уровне локальные сети пока слишком далеки от того, чтобы писать самостоятельно что-то приличное, без постоянной помощи разработчика. Код, получаемый на выходе, часто не только не работает, но даже не компилируется.

Однако они могут помочь быстро создать каркас приложения и нужных классов, а зачастую подкидывают интересные идеи, которые можно развивать. И это крайне полезно, особенно если у вас нет доступа к интернету ;). Не зря copilot называется copilot, а не автопилот. Эта штука помогает нам писать код, но пока не пишет за нас.

Всё равно программисту нужно:

Предельно точно и чётко сформулировать задачу. Без этого результата точно не будет. ИИ не человек, вместо того чтобы уточнить непонятный момент, он его додумает, и, скорее всего, не так, как нам хотелось бы.
Проверить результат.
Доработать полученный код напильником, чтобы он запускался. Потому что, сюрприз, сетка ничего не понимает в программировании — она знает, как составить слова, чтобы это было похоже на программу. Поэтому без программиста всё равно никак.

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10 июл. 2024 г.

07.09.23 16:24 CherryTeam

Cherry Team atlyginimų skaičiavimo programa yra labai naudingas įrankis įmonėms, kai reikia efektyviai valdyti ir skaičiuoti darbuotojų atlyginimus. Ši programinė įranga, turinti išsamias funkcijas ir patogią naudotojo sąsają, suteikia daug privalumų, kurie padeda supaprastinti darbo užmokesčio skaičiavimo procesus ir pagerinti finansų valdymą. Štai keletas pagrindinių priežasčių, kodėl Cherry Team atlyginimų skaičiavimo programa yra naudinga įmonėms: Automatizuoti ir tikslūs skaičiavimai: Atlyginimų skaičiavimai rankiniu būdu gali būti klaidingi ir reikalauti daug laiko. Programinė įranga Cherry Team automatizuoja visą atlyginimų skaičiavimo procesą, todėl nebereikia atlikti skaičiavimų rankiniu būdu ir sumažėja klaidų rizika. Tiksliai apskaičiuodama atlyginimus, įskaitant tokius veiksnius, kaip pagrindinis atlyginimas, viršvalandžiai, premijos, išskaitos ir mokesčiai, programa užtikrina tikslius ir be klaidų darbo užmokesčio skaičiavimo rezultatus. Sutaupoma laiko ir išlaidų: Darbo užmokesčio valdymas gali būti daug darbo jėgos reikalaujanti užduotis, reikalaujanti daug laiko ir išteklių. Programa Cherry Team supaprastina ir pagreitina darbo užmokesčio skaičiavimo procesą, nes automatizuoja skaičiavimus, generuoja darbo užmokesčio žiniaraščius ir tvarko išskaičiuojamus mokesčius. Šis automatizavimas padeda įmonėms sutaupyti daug laiko ir pastangų, todėl žmogiškųjų išteklių ir finansų komandos gali sutelkti dėmesį į strategiškai svarbesnę veiklą. Be to, racionalizuodamos darbo užmokesčio operacijas, įmonės gali sumažinti administracines išlaidas, susijusias su rankiniu darbo užmokesčio tvarkymu. Mokesčių ir darbo teisės aktų laikymasis: Įmonėms labai svarbu laikytis mokesčių ir darbo teisės aktų, kad išvengtų baudų ir teisinių problemų. Programinė įranga Cherry Team seka besikeičiančius mokesčių įstatymus ir darbo reglamentus, užtikrindama tikslius skaičiavimus ir teisinių reikalavimų laikymąsi. Programa gali dirbti su sudėtingais mokesčių scenarijais, pavyzdžiui, keliomis mokesčių grupėmis ir įvairių rūšių atskaitymais, todėl užtikrina atitiktį reikalavimams ir kartu sumažina klaidų riziką. Ataskaitų rengimas ir analizė: Programa Cherry Team siūlo patikimas ataskaitų teikimo ir analizės galimybes, suteikiančias įmonėms vertingų įžvalgų apie darbo užmokesčio duomenis. Ji gali generuoti ataskaitas apie įvairius aspektus, pavyzdžiui, darbo užmokesčio paskirstymą, išskaičiuojamus mokesčius ir darbo sąnaudas. Šios ataskaitos leidžia įmonėms analizuoti darbo užmokesčio tendencijas, nustatyti tobulintinas sritis ir priimti pagrįstus finansinius sprendimus. Pasinaudodamos duomenimis pagrįstomis įžvalgomis, įmonės gali optimizuoti savo darbo užmokesčio strategijas ir veiksmingai kontroliuoti išlaidas. Integracija su kitomis sistemomis: Cherry Team programinė įranga dažnai sklandžiai integruojama su kitomis personalo ir apskaitos sistemomis. Tokia integracija leidžia automatiškai perkelti atitinkamus duomenis, pavyzdžiui, informaciją apie darbuotojus ir finansinius įrašus, todėl nebereikia dubliuoti duomenų. Supaprastintas duomenų srautas tarp sistemų padidina bendrą efektyvumą ir sumažina duomenų klaidų ar neatitikimų riziką. Cherry Team atlyginimų apskaičiavimo programa įmonėms teikia didelę naudą - automatiniai ir tikslūs skaičiavimai, laiko ir sąnaudų taupymas, atitiktis mokesčių ir darbo teisės aktų reikalavimams, ataskaitų teikimo ir analizės galimybės bei integracija su kitomis sistemomis. Naudodamos šią programinę įrangą įmonės gali supaprastinti darbo užmokesčio skaičiavimo procesus, užtikrinti tikslumą ir atitiktį reikalavimams, padidinti darbuotojų pasitenkinimą ir gauti vertingų įžvalgų apie savo finansinius duomenis. Programa Cherry Team pasirodo esanti nepakeičiamas įrankis įmonėms, siekiančioms efektyviai ir veiksmingai valdyti darbo užmokestį. https://cherryteam.lt/lt/
08.10.23 01:30 davec8080

The "Shibarium for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH. The Plot Thickens. Someone posted the actual transactions!!!! https://bscscan.com/tx/0xa846ea0367c89c3f0bbfcc221cceea4c90d8f56ead2eb479d4cee41c75e02c97 It seems the article is true!!!! And it's also FUD. Let me explain. Check this link: https://bscscan.com/token/0x5a752c9fe3520522ea88f37a41c3ddd97c022c2f So there really is a "Shibarium" token. And somebody did a rug pull with it. CONFIRMED. But the "Shibarium" token for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH.
24.06.24 04:31 tashandiarisha

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26.06.24 18:46 Jacobethannn098

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26.06.24 18:46 Jacobethannn098

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04.07.24 04:49 ZionNaomi

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13.07.24 21:13 michaelharrell825

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17.07.24 02:26 thompsonrickey

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02.09.24 20:24 [email protected]

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06.09.24 01:35 Celinagarcia

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06.09.24 01:44 Celinagarcia

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16.09.24 00:10 marcusaustin

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16.09.24 00:11 marcusaustin

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23.09.24 18:56 matthewshimself

At first, I was admittedly skeptical about Worldcoin (ref: https://worldcoin.org/blog/worldcoin/this-is-worldcoin-video-explainer-series), particularly around the use of biometric data and the WLD token as a reward mechanism for it. However, after following the project closer, I’ve come to appreciate the broader vision and see the value in the underlying tech behind it. The concept of Proof of Personhood (ref: https://worldcoin.org/blog/worldcoin/proof-of-personhood-what-it-is-why-its-needed) has definitely caught my attention, and does seem like a crucial step towards tackling growing issues like bots, deepfakes, and identity fraud. Sam Altman’s vision is nothing short of ambitious, but I do think he & Alex Blania have the chops to realize it as mainstay in the global economy.
01.10.24 14:54 Sinewclaudia

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02.10.24 22:27 Emily Hunter

Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
18.10.24 09:34 freidatollerud

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31.10.24 00:13 ytre89

Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
02.11.24 14:44 diannamendoza732

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12.11.24 00:50 TERESA

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17.11.24 09:31 Vivianlocke223

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Being a parent is great until your toddler figures out how to use your devices. One afternoon, I left my phone unattended for just a few minutes rookie mistake of the century. I thought I’d take a quick break, but little did I know that my curious little genius was about to embark on a digital adventure. By the time I came back, I was greeted by two shocking revelations: my toddler had somehow managed to buy a $5 dinosaur toy online and, even more alarmingly, had locked me out of my cryptocurrency wallet holding a hefty $75,000. Yes, you heard that right a dinosaur toy was the least of my worries! At first, I laughed it off. I mean, what toddler doesn’t have a penchant for expensive toys? But then reality set in. I stared at my phone in disbelief, desperately trying to guess whatever random string of gibberish my toddler had typed as a new password. Was it “dinosaur”? Or perhaps “sippy cup”? I felt like I was in a bizarre game of Password Gone Wrong. Every attempt led to failure, and soon the laughter faded, replaced by sheer panic. I was in way over my head, and my heart raced as the countdown of time ticked away. That’s when I decided to take action and turned to Digital Tech Guard Recovery, hoping they could solve the mystery that was my toddler’s handiwork. I explained my predicament, half-expecting them to chuckle at my misfortune, but they were incredibly professional and empathetic. Their confidence put me at ease, and I knew I was in good hands. Contact With WhatsApp: +1 (443) 859 - 2886 Email digital tech guard . com Telegram: digital tech guard recovery . com website link :: https : // digital tech guard . com Their team took on the challenge like pros, employing their advanced techniques to unlock my wallet with a level of skill I can only describe as magical. As I paced around, anxiously waiting for updates, I imagined my toddler inadvertently locking away my life savings forever. But lo and behold, it didn’t take long for Digital Tech Guard Recovery to work their magic. Not only did they recover the $75,000, but they also gave me invaluable tips on securing my wallet better like not leaving it accessible to tiny fingers! Who knew parenting could lead to such dramatic situations? Crisis averted, and I learned my lesson: always keep my devices out of reach of little explorers. If you ever find yourself in a similar predicament whether it’s tech-savvy toddlers or other digital disasters don’t hesitate to reach out to Digital Tech Guard Recovery. They saved my funds and my sanity, proving that no challenge is too great, even when it involves a toddler’s mischievous fingers!
21.11.24 08:02 Emily Hunter

If I hadn't found a review online and filed a complaint via email to support@deftrecoup. com , the people behind this unregulated scheme would have gotten away with leaving me in financial ruins. It was truly the most difficult period of my life.
22.11.24 04:41 [email protected]

I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT
22.11.24 15:26 cliftonhandyman

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22.11.24 23:43 teresaborja

all thanks to Tech Cyber Force Recovery expert assistance. As a novice in cryptocurrency, I had been carefully accumulating a modest amount of Bitcoin, meticulously safeguarding my digital wallet and private keys. However, as the adage goes, the best-laid plans can often go awry, and that's precisely what happened to me. Due to a series of technical mishaps and human errors, I found myself locked out of my Bitcoin wallet, unable to access the fruits of my digital labors. Panic set in as I frantically searched for a solution, scouring the internet for any glimmer of hope. That's when I stumbled upon the Tech Cyber Force Recovery team, a group of seasoned cryptocurrency specialists who had built a reputation for their ability to recover lost or inaccessible digital assets. Skeptical at first, I reached out, desperate for a miracle. To my utter amazement, the Tech Cyber Force Recovery experts quickly assessed my situation and devised a meticulous plan of attack. Through their deep technical knowledge, unwavering determination, and a keen eye for detail, they were able to navigate the complex labyrinth of blockchain technology, ultimately recovering my entire Bitcoin portfolio. What had once seemed like a hopeless endeavor was now a reality, and I found myself once again in possession of my digital wealth, all thanks to the incredible efforts of the Tech Cyber Force Recovery team. This experience has not only restored my faith in the cryptocurrency ecosystem. Still, it has also instilled in me a profound appreciation for the critical role that expert recovery services can play in safeguarding one's digital assets. ENAIL < Tech cybers force recovery @ cyber services. com > WEBSITE < ht tps : // tech cyber force recovery. info > TEXT < +1. 561. 726. 3697 >
24.11.24 02:21 [email protected]

I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT
25.11.24 02:19 briankennedy

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25.11.24 02:20 briankennedy

After countless hours of research and desperate attempts to find a solution, I stumbled upon FASTFUND RECOVERY. It was like finding an oasis in the middle of a desert. Their website promised to help victims of scams reclaim what was rightfully theirs, and I instantly knew I had to give them a shot. Before diving headfirst into the recovery process, I wanted to make sure that FASTFUND RECOVERY was the real deal. So, I did my due diligence and looked into their expertise and reputation. To my relief, I found that they had an impeccable track record, successfully assisting countless individuals in recovering their lost funds. Their team consisted of experts in cybersecurity and financial fraud, armed with the knowledge and tools needed to tackle even the most intricate scams. With their reputation preceding them, I felt a renewed sense of hope. FASTFUND RECOVERY successfully came to my aid and got back the amount I lost to these scammers and for this, I am sending this article for clarification. The info of FASTFUND RECOVERY is email: Fastfundrecovery8 (@)Gmail (.) com. Web fastfundrecovery(.)com. (W/A 1 807/500/7554)
26.11.24 21:59 [email protected]

In a world brimming with enticing investment opportunities, it is crucial to tread carefully. The rise of digital currencies has attracted many eager investors, but along with this excitement lurk deceitful characters ready to exploit the unsuspecting. I learned this lesson the hard way, and I want to share my story in the hopes that it can save someone from making the same mistakes I did. It all began innocently enough when I came across an engaging individual on Facebook. Lured in by promises of high returns in the cryptocurrency market, I felt the electric thrill of potential wealth coursing through me. Initial investments returned some profits, and that exhilarating taste of success fueled my ambition. Encouraged by a meager withdrawal, I decided to commit even more funds. This was the moment I let my guard down, blinded by greed. As time went on, the red flags started to multiply. The moment I tried to withdraw my earnings, a cascade of unreasonable fees appeared like a thick mist, obscuring the truth. “Just a little more,” they said, “Just until the next phase.” I watched my hard-earned money slip through my fingers as I scraped together every last cent to pay those relentless fees. My trust had become my downfall. In the end, I lost not just a significant amount of cash, but my peace of mind about $1.1 million vanished into the abyss of false promises and hollow guarantees. But despair birthed hope. After a cascade of letdowns, I enlisted the help of KAY-NINE CYBER SERVICES, a team that specializes in reclaiming lost funds from scams. Amazingly, they worked tirelessly to piece together what had been ripped away, providing me with honest guidance when I felt utterly defeated. Their expertise in navigating the treacherous waters of crypto recovery was a lifeline I desperately needed. To anyone reading this, please let my story serve as a warning. High returns often come wrapped in the guise of deception. Protect your investments, scrutinize every opportunity, and trust your instincts. Remember, the allure of quick riches can lead you straight to heartbreak, but with cautious determination and support, it is possible to begin healing from such devastating loss. Stay informed, stay vigilant, and may you choose your investment paths wisely. Email: kaynine @ cyberservices . com
26.11.24 23:12 rickrobinson8

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26.11.24 23:12 rickrobinson8

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00:39 [email protected]

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09:10 Michal Novotny

The biggest issue with cryptocurrency is that it is unregulated, wh ich is why different people can come up with different fake stories all the time, and it is unfortunate that platforms like Facebook and others only care about the money they make from them through ads. I saw an ad on Facebook for Cointiger and fell into the scam, losing over $30,000. I reported it to Facebook, but they did nothing until I discovered deftrecoup . c o m from a crypto community; they retrieved approximately 95% of the total amount I lost.