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251 lines
9.4 KiB
Python
251 lines
9.4 KiB
Python
from typing import Optional
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from flask import Config, Flask
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from pydantic import BaseModel
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from core.entities.provider_entities import QuotaUnit, RestrictModel
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from core.model_runtime.entities.model_entities import ModelType
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from models.provider import ProviderQuotaType
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class HostingQuota(BaseModel):
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quota_type: ProviderQuotaType
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restrict_models: list[RestrictModel] = []
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class TrialHostingQuota(HostingQuota):
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quota_type: ProviderQuotaType = ProviderQuotaType.TRIAL
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quota_limit: int = 0
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"""Quota limit for the hosting provider models. -1 means unlimited."""
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class PaidHostingQuota(HostingQuota):
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quota_type: ProviderQuotaType = ProviderQuotaType.PAID
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class FreeHostingQuota(HostingQuota):
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quota_type: ProviderQuotaType = ProviderQuotaType.FREE
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class HostingProvider(BaseModel):
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enabled: bool = False
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credentials: Optional[dict] = None
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quota_unit: Optional[QuotaUnit] = None
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quotas: list[HostingQuota] = []
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class HostedModerationConfig(BaseModel):
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enabled: bool = False
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providers: list[str] = []
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class HostingConfiguration:
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provider_map: dict[str, HostingProvider] = {}
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moderation_config: HostedModerationConfig = None
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def init_app(self, app: Flask) -> None:
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config = app.config
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if config.get('EDITION') != 'CLOUD':
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return
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self.provider_map["azure_openai"] = self.init_azure_openai(config)
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self.provider_map["openai"] = self.init_openai(config)
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self.provider_map["anthropic"] = self.init_anthropic(config)
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self.provider_map["minimax"] = self.init_minimax(config)
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self.provider_map["spark"] = self.init_spark(config)
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self.provider_map["zhipuai"] = self.init_zhipuai(config)
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self.moderation_config = self.init_moderation_config(config)
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def init_azure_openai(self, app_config: Config) -> HostingProvider:
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quota_unit = QuotaUnit.TIMES
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if app_config.get("HOSTED_AZURE_OPENAI_ENABLED"):
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credentials = {
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"openai_api_key": app_config.get("HOSTED_AZURE_OPENAI_API_KEY"),
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"openai_api_base": app_config.get("HOSTED_AZURE_OPENAI_API_BASE"),
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"base_model_name": "gpt-35-turbo"
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}
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quotas = []
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hosted_quota_limit = int(app_config.get("HOSTED_AZURE_OPENAI_QUOTA_LIMIT", "1000"))
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trial_quota = TrialHostingQuota(
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quota_limit=hosted_quota_limit,
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restrict_models=[
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RestrictModel(model="gpt-4", base_model_name="gpt-4", model_type=ModelType.LLM),
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RestrictModel(model="gpt-4-32k", base_model_name="gpt-4-32k", model_type=ModelType.LLM),
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RestrictModel(model="gpt-4-1106-preview", base_model_name="gpt-4-1106-preview", model_type=ModelType.LLM),
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RestrictModel(model="gpt-4-vision-preview", base_model_name="gpt-4-vision-preview", model_type=ModelType.LLM),
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RestrictModel(model="gpt-35-turbo", base_model_name="gpt-35-turbo", model_type=ModelType.LLM),
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RestrictModel(model="gpt-35-turbo-1106", base_model_name="gpt-35-turbo-1106", model_type=ModelType.LLM),
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RestrictModel(model="gpt-35-turbo-instruct", base_model_name="gpt-35-turbo-instruct", model_type=ModelType.LLM),
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RestrictModel(model="gpt-35-turbo-16k", base_model_name="gpt-35-turbo-16k", model_type=ModelType.LLM),
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RestrictModel(model="text-davinci-003", base_model_name="text-davinci-003", model_type=ModelType.LLM),
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RestrictModel(model="text-embedding-ada-002", base_model_name="text-embedding-ada-002", model_type=ModelType.TEXT_EMBEDDING),
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RestrictModel(model="text-embedding-3-small", base_model_name="text-embedding-3-small", model_type=ModelType.TEXT_EMBEDDING),
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RestrictModel(model="text-embedding-3-large", base_model_name="text-embedding-3-large", model_type=ModelType.TEXT_EMBEDDING),
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]
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)
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quotas.append(trial_quota)
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return HostingProvider(
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enabled=True,
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credentials=credentials,
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quota_unit=quota_unit,
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quotas=quotas
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)
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return HostingProvider(
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enabled=False,
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quota_unit=quota_unit,
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)
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def init_openai(self, app_config: Config) -> HostingProvider:
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quota_unit = QuotaUnit.CREDITS
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quotas = []
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if app_config.get("HOSTED_OPENAI_TRIAL_ENABLED"):
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hosted_quota_limit = int(app_config.get("HOSTED_OPENAI_QUOTA_LIMIT", "200"))
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trial_models = self.parse_restrict_models_from_env(app_config, "HOSTED_OPENAI_TRIAL_MODELS")
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trial_quota = TrialHostingQuota(
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quota_limit=hosted_quota_limit,
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restrict_models=trial_models
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)
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quotas.append(trial_quota)
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if app_config.get("HOSTED_OPENAI_PAID_ENABLED"):
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paid_models = self.parse_restrict_models_from_env(app_config, "HOSTED_OPENAI_PAID_MODELS")
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paid_quota = PaidHostingQuota(
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restrict_models=paid_models
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)
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quotas.append(paid_quota)
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if len(quotas) > 0:
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credentials = {
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"openai_api_key": app_config.get("HOSTED_OPENAI_API_KEY"),
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}
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if app_config.get("HOSTED_OPENAI_API_BASE"):
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credentials["openai_api_base"] = app_config.get("HOSTED_OPENAI_API_BASE")
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if app_config.get("HOSTED_OPENAI_API_ORGANIZATION"):
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credentials["openai_organization"] = app_config.get("HOSTED_OPENAI_API_ORGANIZATION")
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return HostingProvider(
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enabled=True,
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credentials=credentials,
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quota_unit=quota_unit,
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quotas=quotas
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)
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return HostingProvider(
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enabled=False,
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quota_unit=quota_unit,
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)
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def init_anthropic(self, app_config: Config) -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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quotas = []
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if app_config.get("HOSTED_ANTHROPIC_TRIAL_ENABLED"):
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hosted_quota_limit = int(app_config.get("HOSTED_ANTHROPIC_QUOTA_LIMIT", "0"))
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trial_quota = TrialHostingQuota(
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quota_limit=hosted_quota_limit
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)
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quotas.append(trial_quota)
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if app_config.get("HOSTED_ANTHROPIC_PAID_ENABLED"):
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paid_quota = PaidHostingQuota()
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quotas.append(paid_quota)
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if len(quotas) > 0:
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credentials = {
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"anthropic_api_key": app_config.get("HOSTED_ANTHROPIC_API_KEY"),
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}
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if app_config.get("HOSTED_ANTHROPIC_API_BASE"):
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credentials["anthropic_api_url"] = app_config.get("HOSTED_ANTHROPIC_API_BASE")
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return HostingProvider(
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enabled=True,
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credentials=credentials,
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quota_unit=quota_unit,
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quotas=quotas
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)
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return HostingProvider(
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enabled=False,
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quota_unit=quota_unit,
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)
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def init_minimax(self, app_config: Config) -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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if app_config.get("HOSTED_MINIMAX_ENABLED"):
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quotas = [FreeHostingQuota()]
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return HostingProvider(
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enabled=True,
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credentials=None, # use credentials from the provider
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quota_unit=quota_unit,
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quotas=quotas
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)
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return HostingProvider(
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enabled=False,
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quota_unit=quota_unit,
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)
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def init_spark(self, app_config: Config) -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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if app_config.get("HOSTED_SPARK_ENABLED"):
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quotas = [FreeHostingQuota()]
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return HostingProvider(
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enabled=True,
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credentials=None, # use credentials from the provider
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quota_unit=quota_unit,
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quotas=quotas
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)
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return HostingProvider(
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enabled=False,
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quota_unit=quota_unit,
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)
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def init_zhipuai(self, app_config: Config) -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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if app_config.get("HOSTED_ZHIPUAI_ENABLED"):
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quotas = [FreeHostingQuota()]
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return HostingProvider(
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enabled=True,
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credentials=None, # use credentials from the provider
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quota_unit=quota_unit,
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quotas=quotas
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)
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return HostingProvider(
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enabled=False,
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quota_unit=quota_unit,
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)
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def init_moderation_config(self, app_config: Config) -> HostedModerationConfig:
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if app_config.get("HOSTED_MODERATION_ENABLED") \
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and app_config.get("HOSTED_MODERATION_PROVIDERS"):
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return HostedModerationConfig(
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enabled=True,
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providers=app_config.get("HOSTED_MODERATION_PROVIDERS").split(',')
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)
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return HostedModerationConfig(
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enabled=False
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)
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@staticmethod
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def parse_restrict_models_from_env(app_config: Config, env_var: str) -> list[RestrictModel]:
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models_str = app_config.get(env_var)
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models_list = models_str.split(",") if models_str else []
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return [RestrictModel(model=model_name.strip(), model_type=ModelType.LLM) for model_name in models_list if
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model_name.strip()]
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