mirror of
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263 lines
9.9 KiB
Python
263 lines
9.9 KiB
Python
from typing import Optional
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from flask import Flask
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from pydantic import BaseModel
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from configs import dify_config
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from core.entities import DEFAULT_PLUGIN_ID
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from core.entities.provider_entities import ProviderQuotaType, QuotaUnit, RestrictModel
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from core.model_runtime.entities.model_entities import ModelType
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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: Optional[HostedModerationConfig] = None
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def init_app(self, app: Flask) -> None:
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if dify_config.EDITION != "CLOUD":
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return
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self.provider_map[f"{DEFAULT_PLUGIN_ID}/azure_openai/azure_openai"] = self.init_azure_openai()
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self.provider_map[f"{DEFAULT_PLUGIN_ID}/openai/openai"] = self.init_openai()
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self.provider_map[f"{DEFAULT_PLUGIN_ID}/anthropic/anthropic"] = self.init_anthropic()
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self.provider_map[f"{DEFAULT_PLUGIN_ID}/minimax/minimax"] = self.init_minimax()
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self.provider_map[f"{DEFAULT_PLUGIN_ID}/spark/spark"] = self.init_spark()
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self.provider_map[f"{DEFAULT_PLUGIN_ID}/zhipuai/zhipuai"] = self.init_zhipuai()
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self.moderation_config = self.init_moderation_config()
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@staticmethod
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def init_azure_openai() -> HostingProvider:
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quota_unit = QuotaUnit.TIMES
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if dify_config.HOSTED_AZURE_OPENAI_ENABLED:
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credentials = {
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"openai_api_key": dify_config.HOSTED_AZURE_OPENAI_API_KEY,
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"openai_api_base": dify_config.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 = dify_config.HOSTED_AZURE_OPENAI_QUOTA_LIMIT
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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-4o", base_model_name="gpt-4o", model_type=ModelType.LLM),
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RestrictModel(model="gpt-4o-mini", base_model_name="gpt-4o-mini", 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(
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model="gpt-4-1106-preview", base_model_name="gpt-4-1106-preview", model_type=ModelType.LLM
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),
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RestrictModel(
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model="gpt-4-vision-preview", base_model_name="gpt-4-vision-preview", model_type=ModelType.LLM
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),
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RestrictModel(model="gpt-35-turbo", base_model_name="gpt-35-turbo", model_type=ModelType.LLM),
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RestrictModel(
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model="gpt-35-turbo-1106", base_model_name="gpt-35-turbo-1106", model_type=ModelType.LLM
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),
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RestrictModel(
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model="gpt-35-turbo-instruct", base_model_name="gpt-35-turbo-instruct", model_type=ModelType.LLM
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),
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RestrictModel(
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model="gpt-35-turbo-16k", base_model_name="gpt-35-turbo-16k", model_type=ModelType.LLM
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),
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RestrictModel(
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model="text-davinci-003", base_model_name="text-davinci-003", model_type=ModelType.LLM
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),
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RestrictModel(
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model="text-embedding-ada-002",
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base_model_name="text-embedding-ada-002",
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model_type=ModelType.TEXT_EMBEDDING,
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),
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RestrictModel(
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model="text-embedding-3-small",
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base_model_name="text-embedding-3-small",
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model_type=ModelType.TEXT_EMBEDDING,
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),
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RestrictModel(
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model="text-embedding-3-large",
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base_model_name="text-embedding-3-large",
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model_type=ModelType.TEXT_EMBEDDING,
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),
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],
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)
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quotas.append(trial_quota)
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return HostingProvider(enabled=True, credentials=credentials, quota_unit=quota_unit, quotas=quotas)
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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) -> HostingProvider:
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quota_unit = QuotaUnit.CREDITS
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quotas = []
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if dify_config.HOSTED_OPENAI_TRIAL_ENABLED:
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hosted_quota_limit = dify_config.HOSTED_OPENAI_QUOTA_LIMIT
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trial_models = self.parse_restrict_models_from_env("HOSTED_OPENAI_TRIAL_MODELS")
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trial_quota = TrialHostingQuota(quota_limit=hosted_quota_limit, restrict_models=trial_models)
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quotas.append(trial_quota)
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if dify_config.HOSTED_OPENAI_PAID_ENABLED:
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paid_models = self.parse_restrict_models_from_env("HOSTED_OPENAI_PAID_MODELS")
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paid_quota = PaidHostingQuota(restrict_models=paid_models)
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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": dify_config.HOSTED_OPENAI_API_KEY,
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}
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if dify_config.HOSTED_OPENAI_API_BASE:
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credentials["openai_api_base"] = dify_config.HOSTED_OPENAI_API_BASE
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if dify_config.HOSTED_OPENAI_API_ORGANIZATION:
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credentials["openai_organization"] = dify_config.HOSTED_OPENAI_API_ORGANIZATION
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return HostingProvider(enabled=True, credentials=credentials, quota_unit=quota_unit, quotas=quotas)
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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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@staticmethod
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def init_anthropic() -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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quotas = []
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if dify_config.HOSTED_ANTHROPIC_TRIAL_ENABLED:
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hosted_quota_limit = dify_config.HOSTED_ANTHROPIC_QUOTA_LIMIT
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trial_quota = TrialHostingQuota(quota_limit=hosted_quota_limit)
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quotas.append(trial_quota)
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if dify_config.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": dify_config.HOSTED_ANTHROPIC_API_KEY,
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}
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if dify_config.HOSTED_ANTHROPIC_API_BASE:
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credentials["anthropic_api_url"] = dify_config.HOSTED_ANTHROPIC_API_BASE
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return HostingProvider(enabled=True, credentials=credentials, quota_unit=quota_unit, quotas=quotas)
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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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@staticmethod
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def init_minimax() -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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if dify_config.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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@staticmethod
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def init_spark() -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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if dify_config.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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@staticmethod
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def init_zhipuai() -> HostingProvider:
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quota_unit = QuotaUnit.TOKENS
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if dify_config.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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@staticmethod
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def init_moderation_config() -> HostedModerationConfig:
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if dify_config.HOSTED_MODERATION_ENABLED and dify_config.HOSTED_MODERATION_PROVIDERS:
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providers = dify_config.HOSTED_MODERATION_PROVIDERS.split(",")
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hosted_providers = []
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for provider in providers:
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if "/" not in provider:
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provider = f"{DEFAULT_PLUGIN_ID}/{provider}/{provider}"
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hosted_providers.append(provider)
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return HostedModerationConfig(enabled=True, providers=hosted_providers)
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return HostedModerationConfig(enabled=False)
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@staticmethod
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def parse_restrict_models_from_env(env_var: str) -> list[RestrictModel]:
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models_str = dify_config.model_dump().get(env_var)
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models_list = models_str.split(",") if models_str else []
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return [
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RestrictModel(model=model_name.strip(), model_type=ModelType.LLM)
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for model_name in models_list
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if model_name.strip()
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]
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