v1alpha1

type Flavor struct {
	// Name represents the flavor name, which will be used in model claim.
	Name FlavorName `json:"name"`
	// Requests defines the required accelerators to serve the model, like nvidia.com/gpu: 8.
	// When GPU number is greater than 8, like 32, then multi-host inference is enabled and
	// 32/8=4 hosts will be grouped as an unit, each host will have a resource request as
	// nvidia.com/gpu: 8. The may change in the future if the GPU number limit is broken.
	// Not recommended to set the cpu and memory usage here.
	// If using playground, you can define the cpu/mem usage at backendConfig.
	// If using service, you can define the cpu/mem at the container resources.
	// Note: if you define the same accelerator requests at playground/service as well,
	// the requests here will be covered.
	// +optional
	Requests v1.ResourceList `json:"requests,omitempty"`
	// NodeSelector defines the labels to filter specified nodes, like
	// cloud-provider.com/accelerator: nvidia-a100.
	// NodeSelector will be auto injected to the Pods as scheduling primitives.
	// +optional
	NodeSelector map[string]string `json:"nodeSelector,omitempty"`
	// Params stores other useful parameters and will be consumed by the autoscaling components
	// like cluster-autoscaler, Karpenter.
	// E.g. when scaling up nodes with 8x Nvidia A00, the parameter can be injected with
	// instance-type: p4d.24xlarge for AWS.
	// +optional
	Params map[string]string `json:"params,omitempty"`
}

type FlavorName string

type ModelClaim struct {
	// ModelName represents a list of models, there maybe multiple models here
	// to support state-of-the-art technologies like speculative decoding.
	ModelName ModelName `json:"modelName,omitempty"`
	// InferenceFlavors represents a list of flavors with fungibility supports
	// to serve the model. The flavor names should be a subset of the model
	// configured flavors. If not set, will use the model configured flavors.
	// +optional
	InferenceFlavors []FlavorName `json:"inferenceFlavors,omitempty"`
}

type ModelHub struct {
	// Name refers to the model registry, such as huggingface.
	// +kubebuilder:default=Huggingface
	// +kubebuilder:validation:Enum={Huggingface,ModelScope}
	// +optional
	Name *string `json:"name,omitempty"`
	// ModelID refers to the model identifier on model hub,
	// such as meta-llama/Meta-Llama-3-8B.
	ModelID string `json:"modelID,omitempty"`
	// Filename refers to a specified model file rather than the whole repo.
	// This is helpful to download a specified GGUF model rather than downloading
	// the whole repo which includes all kinds of quantized models.
	// TODO: this is only supported with Huggingface, add support for ModelScope
	// in the near future.
	Filename *string `json:"filename,omitempty"`
	// Revision refers to a Git revision id which can be a branch name, a tag, or a commit hash.
	// Most of the time, you don't need to specify it.
	// +optional
	Revision *string `json:"revision,omitempty"`
}

type ModelName string

type ModelSource struct {
	// ModelHub represents the model registry for model downloads.
	// +optional
	ModelHub *ModelHub `json:"modelHub,omitempty"`
	// URI represents a various kinds of model sources following the uri protocol, e.g.:
	// - OSS: oss://<bucket>.<endpoint>/<path-to-your-model>
	//
	// +optional
	URI *URIProtocol `json:"uri,omitempty"`
}

type ModelSpec struct {
	// FamilyName represents the model type, like llama2, which will be auto injected
	// to the labels with the key of `llmaz.io/model-family-name`.
	FamilyName ModelName `json:"familyName"`
	// Source represents the source of the model, there're several ways to load
	// the model such as loading from huggingface, OCI registry, s3, host path and so on.
	Source ModelSource `json:"source"`
	// InferenceFlavors represents the accelerator requirements to serve the model.
	// Flavors are fungible following the priority of slice order.
	// +optional
	InferenceFlavors []Flavor `json:"inferenceFlavors,omitempty"`
}

type ModelStatus struct {
	// Conditions represents the Inference condition.
	Conditions []metav1.Condition `json:"conditions,omitempty"`
}

type MultiModelsClaim struct {
	// ModelNames represents a list of models, there maybe multiple models here
	// to support state-of-the-art technologies like speculative decoding.
	// +kubebuilder:validation:MinItems=1
	ModelNames []ModelName `json:"modelNames,omitempty"`
	// InferenceFlavors represents a list of flavors with fungibility supported
	// to serve the model.
	// - If not set, always apply with the 0-index model by default.
	// - If set, will lookup the flavor names following the model orders.
	// +optional
	InferenceFlavors []FlavorName `json:"inferenceFlavors,omitempty"`
	// Rate works only when multiple claims declared, it represents the replicas rates of
	// the sub-workload, like when claim1.rate:claim2.rate = 1:2 and 3 replicas defined in
	// workload, then sub-workload1 will have 1 replica, and sub-workload2 will have 2 replicas.
	// This is mostly designed for state-of-the-art technology called splitwise, the prefill
	// and decode phase will be separated and requires different accelerators.
	// The sum of the rates should be divisible by replicas.
	Rate *int32 `json:"rate,omitempty"`
}

type OpenModel struct {
	metav1.TypeMeta   `json:",inline"`
	metav1.ObjectMeta `json:"metadata,omitempty"`

	Spec   ModelSpec   `json:"spec,omitempty"`
	Status ModelStatus `json:"status,omitempty"`
}

type OpenModelList struct {
	metav1.TypeMeta `json:",inline"`
	metav1.ListMeta `json:"metadata,omitempty"`
	Items           []OpenModel `json:"items"`
}

type URIProtocol string