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Н Новости

Максимизируем продуктивность: Создание ИИ-секретаря с Whisper и ChatGPT

Процесс записи хода созвона (фото в цвете)
Процесс записи хода созвона (фото в цвете)

Приветствую! Меня зовут Григорий, и я главный по спецпроектам в команде AllSee. В современном мире искусственный интеллект стал незаменимым помощником в различных сферах нашей жизни. Однако, я верю, что всегда нужно стремиться к большему, автоматизируя все процессы, которые возможно. В этой статье я поделюсь опытом использования Whisper и ChatGPT для создания ИИ‑секретаря, способного оптимизировать хранение и обработку корпоративных созвонов.

Мотивация

Не только очевидно, но и научно доказано, что использование ИИ в рабочем процессе повышает продуктивность: для белых воротничков до 37%!

Источник: https://joshbersin.com/2023/03/new-mit-research-shows-spectacular-increase-in-white-collar-productivity-from-chatgpt/
Источник: https://joshbersin.com/2023/03/new-mit-research-shows-spectacular-increase-in-white-collar-productivity-from-chatgpt/

Давайте и мы попробуем «выбить» наши проценты продуктивности, автоматизировав рутинную задачу просмотра записей созвонов.

Какие вводные?

Есть достаточно большая база созвонов, которые иногда приходится пересматривать, расходуя по 30–40 минут на одну запись, а для некоторых видео, особенно для интервью или сбора требований, обработка может занимать даже больше времени, чем сама встреча.

Я хочу повысить эффективность данного процесса, извлекая транскрипции встреч с выделением участников для быстрого просмотра текста, а также уточняя конкретные вопросы у ИИ‑ассистента. Для взаимодействия с нашей системой я буду использовать Telegram‑бота.

Решение

Техническая структура решения включает в себя:

Техническая структура решения
Техническая структура решения

Я опущу многие детали, связанные с UX бота, но постараюсь затронуть важные моменты, с которыми вам точно придётся иметь дело при разработке и интеграции подобного проекта.

Sqiud Proxy

Для работы с ChatGPT API из России нам потребуется настроить proxy‑сервер. Я буду использовать Squid — кэширующий прокси‑сервер для протоколов HTTP, HTTPS, FTP и Gopher.

Инструкция по настройке Squid Proxy

Описывается установка на сервер с OS Ubuntu, но и для других дистрибутивов Linux инструкция будет похожей, отличаясь только используемым менеджером пакетов.

Установка squid

sudo apt update
sudo apt-get -y install squid

Преднастройка сети

sudo ufw allow squid
sudo iptables -P INPUT ACCEPT

Активация сервиса squid

sudo systemctl enable squid

Настройка squid

Создаём бекап конфигурации squid и удаляем из оригинального файла всё 8000 строк комментариев.

sudo cp /etc/squid/squid.conf /etc/squid/squid_back.conf
sudo  grep -v '^ *#\|^ *$' /etc/squid/squid.conf > /etc/squid/squid.conf

Открываем файл конфигурации squid.

sudo apt-get -y install nano
sudo nano /etc/squid/squid.conf

Файл squid.conf необходимо изменить следующим образом:

...
http_access allow localhost
acl whitelist src 111.111.111.111   # Добавляем IP адрес нашего основного сервера (нужно указать реальный IP) в список доступа
http_access allow whitelist         # Разрешаем основному серверу использовать наш прокси
http_access deny all
...

Перезапуск cервиса squid

Для применения наших настроек достаточно просто перезапустить squid.

sudo systemctl restart squid

WhisperX

Для решения поставленной задачи недостаточно просто транскрибировать текст, требуется также решать задачу диаризации: выделять из аудиопотока отдельных дикторов. Задача осложняется тем, что в переговорах и созвонах могут участвовать несколько собеседников, а многие алгоритмы ограничены 2-мя участниками разговора.

На помощь нам приходит WhisperX — «обёртка» над стандартной моделью Whisper для транскрибации, выделения временных меток отдельных слов, а также диаризации до 100 собеседников.

Для интеграции WhisperX в наше решение я написал небольшой FastAPI‑сервер, обрабатывающий входящие аудиофайлы.

Реализация и запуск сервера
Импорты и настройки
import asyncio
import os
import uuid
from dataclasses import dataclass
from datetime import datetime
from queue import Queue
from threading import Thread
from typing import Any

from fastapi import HTTPException, BackgroundTasks, FastAPI, status, Request
from fastapi.middleware.cors import CORSMiddleware
from pydantic_settings import BaseSettings
from streaming_form_data import StreamingFormDataParser
from streaming_form_data.targets import FileTarget
from streaming_form_data.validators import MaxSizeValidator

import whisperx


@dataclass
class WhisperXModels:
    whisper_model: Any
    diarize_pipeline: Any
    align_model: Any
    align_model_metadata: Any


class TranscriptionAPISettings(BaseSettings):
    tmp_dir: str = 'tmp'
    cors_origins: str = '*'
    cors_allow_credentials: bool = True
    cors_allow_methods: str = '*'
    cors_allow_headers: str = '*'
    whisper_model: str = 'large-v2'
    device: str = 'cuda'
    compute_type: str = 'float16'
    batch_size: int = 16
    language_code: str = 'auto'
    hf_api_key: str = ''
    file_loading_chunk_size_mb: int = 1024
    task_cleanup_delay_min: int = 60
    max_file_size_mb: int = 4096
    max_request_body_size_mb: int = 5000

    class Config:
        env_file = 'env/.env.cuda'
        env_file_encoding = 'utf-8'


class MaxBodySizeException(Exception):
    def __init__(self, body_len: int):
        self.body_len = body_len


class MaxBodySizeValidator:
    def __init__(self, max_size: int):
        self.body_len = 0
        self.max_size = max_size

    def __call__(self, chunk: bytes):
        self.body_len += len(chunk)
        if self.body_len > self.max_size:
            raise MaxBodySizeException(self.body_len)


settings = TranscriptionAPISettings()

app = FastAPI()
# noinspection PyTypeChecker
app.add_middleware(
    CORSMiddleware,
    allow_origins=settings.cors_origins.split(','),
    allow_credentials=settings.cors_allow_credentials,
    allow_methods=settings.cors_allow_methods.split(','),
    allow_headers=settings.cors_allow_headers.split(','),
)
Логика транскрибации
trancription_tasks = {}
trancription_tasks_queue = Queue()

whisperx_models = WhisperXModels(
    whisper_model=None,
    diarize_pipeline=None,
    align_model=None,
    align_model_metadata=None
)


def load_whisperx_models() -> None:
    global whisperx_models

    whisperx_models.whisper_model = whisperx.load_model(
        whisper_arch=settings.whisper_model,
        device=settings.device,
        compute_type=settings.compute_type,
        language=settings.language_code if settings.language_code != "auto" else None
    )

    whisperx_models.diarize_pipeline = whisperx.DiarizationPipeline(
        use_auth_token=settings.hf_api_key,
        device=settings.device
    )

    if settings.language_code != "auto":
        (
            whisperx_models.align_model,
            whisperx_models.align_model_metadata
        ) = whisperx.load_align_model(
            language_code=settings.language_code,
            device=settings.device
        )


def transcribe_audio(audio_file_path: str) -> dict:
    global whisperx_models

    audio = whisperx.load_audio(audio_file_path)

    transcription_result = whisperx_models.whisper_model.transcribe(
        audio,
        batch_size=int(settings.batch_size),
    )

    if settings.language_code == "auto":
        language = transcription_result["language"]
        (
            whisperx_models.align_model,
            whisperx_models.align_model_metadata
        ) = whisperx.load_align_model(
            language_code=language,
            device=settings.device
        )

    aligned_result = whisperx.align(
        transcription_result["segments"],
        whisperx_models.align_model,
        whisperx_models.align_model_metadata,
        audio,
        settings.device,
        return_char_alignments=False
    )

    diarize_segments = whisperx_models.diarize_pipeline(audio)

    final_result = whisperx.assign_word_speakers(
        diarize_segments,
        aligned_result
    )

    return final_result


def transcription_worker() -> None:
    while True:
        task_id, tmp_path = trancription_tasks_queue.get()

        try:
            result = transcribe_audio(tmp_path)
            trancription_tasks[task_id].update({"status": "completed", "result": result})

        except Exception as e:
            trancription_tasks[task_id].update({"status": "failed", "result": str(e)})

        finally:
            trancription_tasks_queue.task_done()
            os.remove(tmp_path)
Логика FasAPI
@app.on_event("startup")
async def startup_event() -> None:
    os.makedirs(settings.tmp_dir, exist_ok=True)
    load_whisperx_models()
    Thread(target=transcription_worker, daemon=True).start()


async def cleanup_task(task_id: str) -> None:
    await asyncio.sleep(settings.task_cleanup_delay_min * 60)
    trancription_tasks.pop(task_id, None)


@app.post("/transcribe/")
async def create_upload_file(
        request: Request,
        background_tasks: BackgroundTasks
) -> dict:
    task_id = str(uuid.uuid4())
    tmp_path = f"{settings.tmp_dir}/{task_id}.audio"

    trancription_tasks[task_id] = {
        "status": "loading",
        "creation_time": datetime.utcnow(),
        "result": None
    }

    body_validator = MaxBodySizeValidator(settings.max_request_body_size_mb * 1024 * 1024)

    try:
        file_target = FileTarget(
            tmp_path,
            validator=MaxSizeValidator(settings.max_file_size_mb * 1024 * 1024)
        )
        parser = StreamingFormDataParser(headers=request.headers)
        parser.register('file', file_target)
        async for chunk in request.stream():
            body_validator(chunk)
            parser.data_received(chunk)

    except MaxBodySizeException as e:
        raise HTTPException(
            status_code=status.HTTP_413_REQUEST_ENTITY_TOO_LARGE,
            detail=f"Maximum request body size limit exceeded: {e.body_len} bytes"
        )

    except Exception as e:
        if os.path.exists(tmp_path):
            os.remove(tmp_path)
        raise HTTPException(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            detail=f"Error processing upload: {str(e)}"
        )

    if not file_target.multipart_filename:
        if os.path.exists(tmp_path):
            os.remove(tmp_path)
        raise HTTPException(
            status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
            detail='No file was uploaded'
        )

    trancription_tasks[task_id].update({"status": "processing"})
    trancription_tasks_queue.put((task_id, tmp_path))

    background_tasks.add_task(cleanup_task, task_id)

    return {
        "task_id": task_id,
        "creation_time": trancription_tasks[task_id]["creation_time"].isoformat(),
        "status": trancription_tasks[task_id]["status"]
    }


@app.get("/transcribe/status/{task_id}")
async def get_task_status(task_id: str) -> dict:
    task = trancription_tasks.get(task_id)

    if not task:
        raise HTTPException(status_code=404, detail="Task not found")

    return {
        "task_id": task_id,
        "creation_time": task["creation_time"],
        "status": task["status"]
    }


@app.get("/transcribe/result/{task_id}")
async def get_task_result(task_id: str) -> dict:
    task = trancription_tasks.get(task_id)

    if not task:
        raise HTTPException(status_code=404, detail="Task not found")

    if task["status"] == "pending":
        raise HTTPException(status_code=404, detail="Task not completed")

    return {
            "task_id": task_id,
            "creation_time": task["creation_time"],
            "status": task["status"],
            "result": task["result"]
    }
Dockerfile
FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu20.04

RUN apt-get update && apt-get install -y software-properties-common
RUN add-apt-repository ppa:deadsnakes/ppa
RUN apt-get update && apt-get install -y python3.10 python3.10-venv python3-pip ffmpeg

WORKDIR /whisperx-fastapi
COPY . .

RUN python3.10 -m venv venv
RUN /bin/bash -c "source venv/bin/activate && pip install --upgrade pip"
RUN /bin/bash -c "source venv/bin/activate && pip install -e ."
RUN /bin/bash -c "source venv/bin/activate && pip install -r fastapi/requirements-fastapi-cuda.txt"

WORKDIR /whisperx-fastapi/fastapi

EXPOSE 8000

CMD ["../venv/bin/uvicorn", "api.app:app", "--host", "0.0.0.0", "--port", "8000"]
Запуск сервера

Для развёртывания сервера достаточно скопировать репозиторий, указать в ./fastapi/env/.env.cudaтокен доступа HuggingFace, собрать и запустить контейнер Docker.

sudo docker build -f fastapi/dockerization/dockerfile.fastapi.cuda -t whisperx-fastapi-cuda .
sudo docker run -p 8000:8000 --env-file ./fastapi/env/.env.cuda  --gpus all --name whisperx-fastapi-cuda-container whisperx-fastapi-cuda

Telegram Bot API

Большой проблемой стало ограничение для Telegram‑ботов на обработку файлов более 50мб, что в контексте обработки голосовых и видеозаписей часовых созвонов — смешные цифры.

Данную проблему можно решить достаточно просто: развернуть свой локальный API для Telegram‑бота с помощью telegram‑bot‑api, что позволит нам обрабатывать файлы уже до 2000мб. При этом вся информация бота будет храниться прямо на нашей машине, что позволит быстрее работать с файлами, не дожидаясь получения multipart c сервера.

Как это можно сделать?

На самом деле, очень просто:

apt-get install -y --no-install-recommends \
    build-essential \
    libssl-dev \
    zlib1g-dev \
    git \
    cmake \
    gperf \
    g++

git clone --recursive https://github.com/tdlib/telegram-bot-api.git && \
    cd telegram-bot-api && \
    mkdir build && \
    cd build && \
    cmake .. && \
    cmake --build . --target install

cd telegram-bot-api/build 
./telegram-bot-api --api-id=${TELEGRAM_API_ID} --api-hash=${TELEGRAM_API_HASH} --local

Python Telegram Bot

Ну и, наконец, для обработки запросов от пользователей я использовал python‑telegram‑bot.

Ничего особенного в логике работы я не выделю, поэтому остановимся лишь на интеграции уже готового Telegram‑бота в наше решение.

Развёртывание Telegram-бота

Загрузка репозитория

git clone https://github.com/allseeteam/ai-secretary.git

Сборка контейнера

docker build --build-arg HTTP_PROXY=${HTTP_PROXY} --build-arg HTTPS_PROXY=${HTTPS_PROXY} --build-arg NO_PROXY=${NO_PROXY} -t ai-secretary .
  • HTTP_PROXY — Адрес прокси-сервера для обхода географических ограничений

  • HTTPS_PROXY — См. HTTP_PROXY

  • NO_PROXY — Адреса, запросы на которые мы будем отправлять без прокси

Создание docker volume для sqlite базы данных

docker volume create ai_secretary_sqlite_db

Запуск контейнера

docker run -d --network host --volume ai_secretary_sqlite_db:/ai-secretary/database --env-file env/.env --name ai-secretary-container ai-secretary
  • TELEGRAM_API_ID — ID приложения Telegram

  • TELEGRAM_API_HASH — Hash приложения Telegram

  • TELEGRAM_BOT_TOKEN — Токен бота Telegram

  • TELEGRAM_BOT_API_BASE_URL — Базовый адрес сервера вашего бота (для локального сервера: http://localhost:8081/bot)

  • OPENAI_API_KEY — Токен OpenAI

  • SQLITE_DB_PATH — Путь по которому мы хотим хранить нашу SQLite базу данных (стандартный адрес: bot/database/ai-secretary.db)

  • TRANSCRIPTION_API_BASE_URL — Базовый адрес сервера для транскрибации (развернуть сервер можно по инструкциям из репозитория, для локального сервера адрес (для данного кейса обязательно при запуске образа указываем --network host): http://127.0.0.1:8000)

Результат

Пример работы с ботом
Пример работы с ботом

Как видно, наш ИИ‑секретарь без проблем обрабатывает входящие видеофайлы, а также обсуждает их содержимое с пользователем, учитывая содержание записи и контекст прошлых вопросов.

Заключение

С помощью ChatGPT, Whisper и капли «прогерской магии» нам удалось повысить продуктивность работы с корпоративной базой данных и избавиться от необходимости просматривать часовые видео созвонов, чтобы освежить память перед работой.

А ещё крутая новость для всех любителей «потыкать»: в течение следующей недели бот будет доступен всем желающим для ознакомления и работы. Если у вас возникнут проблемы или предложения по функционалу бота — свободно пишите по контактам в описании.

Всю кодовую базу вы можете найти в репозитории проекта. Если кто‑то вдохновиться проектом и решит модифицировать наши наработки — буду рад принять ваш pull request.

А какие моменты конкретно вашей работы просят автоматизации? Делитесь идеями и мыслями в комментариях — с нетерпением обсужу их вместе с вами. Будьте хорошими людьми, а всё остальное оставьте машинам. Удачи и будем на связи✌️

Источник

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  • 14.10.25 08:46 robertalfred175

    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: 📧 Email: [email protected] 📱 Telegram: @Capitalcryptorecover Contact: [email protected] 📞 Call/Text: +1 (336) 390-6684 🌐 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 14.10.25 08:46 robertalfred175

    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: 📧 Email: [email protected] 📱 Telegram: @Capitalcryptorecover Contact: [email protected] 📞 Call/Text: +1 (336) 390-6684 🌐 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 14.10.25 08:46 robertalfred175

    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: 📧 Email: [email protected] 📱 Telegram: @Capitalcryptorecover Contact: [email protected] 📞 Call/Text: +1 (336) 390-6684 🌐 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

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