Skip to main content

Библиотека для использования Omni Antispam API (https://moderator.omni-devel.ru)

Project description

RuModeratorAI

Библиотека для использования Omni Antispam API (https://moderator.omni-devel.ru), в прошлом - RuModeratorAI API.

Установка

pip install rumoderatorai

Пример использования

from rumoderatorai import Client, Context, ChatContext

import asyncio

from PIL import Image

import os


async def main():
    async with Client(
        api_key=os.getenv("RUMODERATORAI_API_KEY")
    ) as client:
        context = Context(
            chat_context=ChatContext(
                title="Test group",
                topic_title="Test topic"
            ),
            allowed_rules=[
                "mutual subscriptions",
                "job offers",
                "cars selling"
            ]
        )

        text_response = await client.get_text_class("Hello, world!", context=context)
        print(text_response)

        profile_response = await client.get_profile_class(
            username="test",
            first_name="test",
            last_name="test",
            description="test",
            is_premium=False,
        )
        print(profile_response)

        image = Image.open("tests/image.png")
        image_response = await client.get_image_class(image)
        print(image_response)

        ocr_response = await client.get_ocr(image)
        print(ocr_response)

        multimodal_text_response = await client.get_multimodal_text_class(
            text="Всем привет!",
            images=[
                "tests/image_spam.png", "tests/image_not_spam.png", "tests/image_spam_2.png"
            ],
            context=context
        )
        print(multimodal_text_response)

        stats_response = await client.get_stats()
        print(stats_response)

        key_info_response = await client.get_key_info()
        print(key_info_response)

        prediction_response = await client.get_prediction(unique_id=text_response.unique_id)
        print(prediction_response)

        ips_response = await client.get_ips()
        print(ips_response)

        prices_response = await client.get_prices()
        print(prices_response)


asyncio.run(main())

Или можно использовать без async with:

from rumoderatorai import Client, Context, ChatContext

import asyncio

from PIL import Image

import os


async def main():
    client = Client(
        api_key=os.getenv("RUMODERATORAI_API_KEY"),
    )
    await client.init()

    context = Context(
        chat_context=ChatContext(
            title="Test group",
            topic_title="Test topic"
        ),
        allowed_rules=[
            "job offers",
            "cars selling"
        ]
    )

    text_response = await client.get_text_class("Hello, world!", context=context)
    print(text_response)

    profile_response = await client.get_profile_class(
        username="test",
        first_name="test",
        last_name="test",
        description="test",
        is_premium=False,
    )
    print(profile_response)

    image = Image.open("tests/image.png")
    image_response = await client.get_image_class(image)
    print(image_response)

    ocr_response = await client.get_ocr(image)
    print(ocr_response)

    multimodal_text_response = await client.get_multimodal_text_class(
        text="Всем привет!",
        images=[
            "tests/image_spam.png", "tests/image_not_spam.png", "tests/image_spam_2.png"
        ],
        context=context
    )
    print(multimodal_text_response)

    stats_response = await client.get_stats()
    print(stats_response)

    key_info_response = await client.get_key_info()
    print(key_info_response)

    prediction_response = await client.get_prediction(unique_id=text_response.unique_id)
    print(prediction_response)

    ips_response = await client.get_ips()
    print(ips_response)

    prices_response = await client.get_prices()
    print(prices_response)

    await client.close()


asyncio.run(main())

Примечание: Не забудьте установить переменную окружения RUMODERATORAI_API_KEY перед запуском кода.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rumoderatorai-1.4.1.tar.gz (9.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

rumoderatorai-1.4.1-py3-none-any.whl (9.0 kB view details)

Uploaded Python 3

File details

Details for the file rumoderatorai-1.4.1.tar.gz.

File metadata

  • Download URL: rumoderatorai-1.4.1.tar.gz
  • Upload date:
  • Size: 9.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.2

File hashes

Hashes for rumoderatorai-1.4.1.tar.gz
Algorithm Hash digest
SHA256 132f155a25513b3783da69b5c7acdeafe97f0e01ec6ffba7d7972ca48ef3a5b6
MD5 799fd00c613adfcbf8bf076636ecffcc
BLAKE2b-256 8ca049bfe1fedf6f88c1f827fec4ceae175dc509aee5b5510fc2e31ad8a3e556

See more details on using hashes here.

File details

Details for the file rumoderatorai-1.4.1-py3-none-any.whl.

File metadata

  • Download URL: rumoderatorai-1.4.1-py3-none-any.whl
  • Upload date:
  • Size: 9.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.2

File hashes

Hashes for rumoderatorai-1.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6b90e430ccc3438724221a1f1cb51be9743a7b71e47b4f38d552831d07324767
MD5 299e67b3d615c39cae47f99cc6479afd
BLAKE2b-256 f2b555f17150362bbe3cdb09dfa68b3a3ac0d6615188ef4d0a64a9f0ffd40142

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page