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