dify/api/core/helper/moderation.py
takatost d069c668f8
Model Runtime (#1858)
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
Co-authored-by: Garfield Dai <dai.hai@foxmail.com>
Co-authored-by: chenhe <guchenhe@gmail.com>
Co-authored-by: jyong <jyong@dify.ai>
Co-authored-by: Joel <iamjoel007@gmail.com>
Co-authored-by: Yeuoly <admin@srmxy.cn>
2024-01-02 23:42:00 +08:00

49 lines
1.9 KiB
Python

import logging
import random
from core.entities.application_entities import ModelConfigEntity
from core.model_runtime.errors.invoke import InvokeBadRequestError
from core.model_runtime.model_providers.openai.moderation.moderation import OpenAIModerationModel
from extensions.ext_hosting_provider import hosting_configuration
from models.provider import ProviderType
logger = logging.getLogger(__name__)
def check_moderation(model_config: ModelConfigEntity, text: str) -> bool:
moderation_config = hosting_configuration.moderation_config
if (moderation_config and moderation_config.enabled is True
and 'openai' in hosting_configuration.provider_map
and hosting_configuration.provider_map['openai'].enabled is True
):
using_provider_type = model_config.provider_model_bundle.configuration.using_provider_type
provider_name = model_config.provider
if using_provider_type == ProviderType.SYSTEM \
and provider_name in moderation_config.providers:
hosting_openai_config = hosting_configuration.provider_map['openai']
# 2000 text per chunk
length = 2000
text_chunks = [text[i:i + length] for i in range(0, len(text), length)]
if len(text_chunks) == 0:
return True
text_chunk = random.choice(text_chunks)
try:
model_type_instance = OpenAIModerationModel()
moderation_result = model_type_instance.invoke(
model='text-moderation-stable',
credentials=hosting_openai_config.credentials,
text=text_chunk
)
if moderation_result is True:
return True
except Exception as ex:
logger.exception(ex)
raise InvokeBadRequestError('Rate limit exceeded, please try again later.')
return False