content: #  Copyright (c) ZenML GmbH 2024. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
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  """Implementation of the ZenML HyperAI orchestrator."""
  
  from typing import TYPE_CHECKING, Dict, Optional, Type
  
  from pydantic import Field
  
  from zenml.config.base_settings import BaseSettings
  from zenml.integrations.hyperai import HYPERAI_RESOURCE_TYPE
  from zenml.logger import get_logger
  from zenml.models import ServiceConnectorRequirements
  from zenml.orchestrators import (
      BaseOrchestratorConfig,
      BaseOrchestratorFlavor,
  )
  
  if TYPE_CHECKING:
      from zenml.integrations.hyperai.orchestrators import HyperAIOrchestrator
  
  logger = get_logger(__name__)
  
  
  class HyperAIOrchestratorSettings(BaseSettings):
      """HyperAI orchestrator settings."""
  
      mounts_from_to: Dict[str, str] = Field(
          default_factory=dict,
          description="A dictionary mapping from paths on the HyperAI instance "
          "to paths within the Docker container. This allows users to mount "
          "directories from the HyperAI instance into the Docker container.",
      )
  
  
  class HyperAIOrchestratorConfig(
      BaseOrchestratorConfig, HyperAIOrchestratorSettings
  ):
      """Configuration for the HyperAI orchestrator."""
  
      container_registry_autologin: bool = Field(
          False,
          description="If True, the orchestrator will attempt to automatically "
          "log in to the container registry specified in the stack configuration "
          "on the HyperAI instance.",
      )
      automatic_cleanup_pipeline_files: bool = Field(
          True,
          description="If True, the orchestrator will automatically clean up old "
          "pipeline files that are on the HyperAI instance. Pipeline files will "
          "be cleaned up if they are 7 days old or older.",
      )
      gpu_enabled_in_container: bool = Field(
          True,
          description="If True, the orchestrator will enable GPU support in the "
          "Docker container that runs on the HyperAI instance.",
      )
  
      @property
      def is_remote(self) -> bool:
          """Checks if this stack component is running remotely.
  
          This designation is used to determine if the stack component can be
          used with a local ZenML database or if it requires a remote ZenML
          server.
  
          Returns:
              True if this config is for a remote component, False otherwise.
          """
          return True
  
      @property
      def is_schedulable(self) -> bool:
          """Whether the orchestrator is schedulable or not.
  
          Returns:
              Whether the orchestrator is schedulable or not.
          """
          return True
  
  
  class HyperAIOrchestratorFlavor(BaseOrchestratorFlavor):
      """Flavor for the HyperAI orchestrator."""
  
      @property
      def name(self) -> str:
          """Name of the orchestrator flavor.
  
          Returns:
              Name of the orchestrator flavor.
          """
          return "hyperai"
  
      @property
      def service_connector_requirements(
          self,
      ) -> Optional[ServiceConnectorRequirements]:
          """Service connector resource requirements for service connectors.
  
          Specifies resource requirements that are used to filter the available
          service connector types that are compatible with this flavor.
  
          Returns:
              Requirements for compatible service connectors, if a service
              connector is required for this flavor.
          """
          return ServiceConnectorRequirements(
              resource_type=HYPERAI_RESOURCE_TYPE
          )
  
      @property
      def docs_url(self) -> Optional[str]:
          """A url to point at docs explaining this flavor.
  
          Returns:
              A flavor docs url.
          """
          return self.generate_default_docs_url()
  
      @property
      def sdk_docs_url(self) -> Optional[str]:
          """A url to point at SDK docs explaining this flavor.
  
          Returns:
              A flavor SDK docs url.
          """
          return self.generate_default_sdk_docs_url()
  
      @property
      def logo_url(self) -> str:
          """A url to represent the flavor in the dashboard.
  
          Returns:
              The flavor logo.
          """
          return "https://public-flavor-logos.s3.eu-central-1.amazonaws.com/connectors/hyperai/hyperai.png"
  
      @property
      def config_class(self) -> Type[BaseOrchestratorConfig]:
          """Config class for the base orchestrator flavor.
  
          Returns:
              The config class.
          """
          return HyperAIOrchestratorConfig
  
      @property
      def implementation_class(self) -> Type["HyperAIOrchestrator"]:
          """Implementation class for this flavor.
  
          Returns:
              Implementation class for this flavor.
          """
          from zenml.integrations.hyperai.orchestrators import (
              HyperAIOrchestrator,
          )
  
          return HyperAIOrchestrator
  