## Update a custom model `models.update(strmodel_id, ModelUpdateParams**kwargs) -> InferenceModel` **patch** `/v5/models/{model_id}` Update a custom model record; vendor-configuration changes are applied asynchronously by redeploying the model. This supports three kinds of update: changing model metadata only, renaming the model, and changing the vendor configuration. A vendor-configuration change is asynchronous — it puts the model back into a deploying status, records an update job, and starts a Temporal workflow to redeploy, so the new configuration is not live when this returns; metadata-only and rename changes take effect immediately. The vendor configuration supplied must match the model's own vendor (`launch` or `llmengine`), and only those two vendors are supported. A model that is currently deploying cannot be modified and the request fails until deployment finishes. When renaming with `on_conflict` set to `swap`, the name is exchanged with an existing model of the same name and vendor instead of failing on the uniqueness constraint. ### Parameters - `model_id: str` - `model: Model` - `class ModelDefaultModelPatchRequest: …` - `model_metadata: Optional[Dict[str, object]]` - `class ModelModelConfigurationPatchRequest: …` - `vendor_configuration: ModelModelConfigurationPatchRequestVendorConfiguration` - `class ModelModelConfigurationPatchRequestVendorConfigurationPartialLaunchVendorConfiguration: …` - `model_image: Optional[ModelModelConfigurationPatchRequestVendorConfigurationPartialLaunchVendorConfigurationModelImage]` - `command: Optional[Sequence[str]]` - `env_vars: Optional[Dict[str, object]]` - `healthcheck_route: Optional[str]` - `predict_route: Optional[str]` - `readiness_delay: Optional[int]` - `registry: Optional[str]` - `repository: Optional[str]` - `request_schema: Optional[Dict[str, object]]` - `response_schema: Optional[Dict[str, object]]` - `streaming_command: Optional[Sequence[str]]` - `streaming_predict_route: Optional[str]` - `tag: Optional[str]` - `model_infra: Optional[ModelModelConfigurationPatchRequestVendorConfigurationPartialLaunchVendorConfigurationModelInfra]` - `cpus: Optional[Union[str, int]]` - `str` - `int` - `endpoint_type: Optional[Literal["async", "sync", "streaming"]]` - `"async"` - `"sync"` - `"streaming"` - `gpu_type: Optional[Literal["nvidia-tesla-t4", "nvidia-ampere-a10", "nvidia-ampere-a100", 4 more]]` - `"nvidia-tesla-t4"` - `"nvidia-ampere-a10"` - `"nvidia-ampere-a100"` - `"nvidia-ampere-a100e"` - `"nvidia-hopper-h100"` - `"nvidia-hopper-h100-1g20gb"` - `"nvidia-hopper-h100-3g40gb"` - `gpus: Optional[int]` - `high_priority: Optional[bool]` - `labels: Optional[Dict[str, str]]` - `max_workers: Optional[int]` - `memory: Optional[str]` - `min_workers: Optional[int]` - `per_worker: Optional[int]` - `public_inference: Optional[bool]` - `storage: Optional[str]` - `class ModelModelConfigurationPatchRequestVendorConfigurationPartialLlmEngineVendorConfiguration: …` - `chat_template_override: Optional[str]` - `checkpoint_path: Optional[str]` - `cpus: Optional[int]` - `default_callback_url: Optional[str]` - `endpoint_type: Optional[str]` - `gpu_type: Optional[str]` - `gpus: Optional[int]` - `high_priority: Optional[bool]` - `inference_framework: Optional[str]` - `inference_framework_image_tag: Optional[str]` - `labels: Optional[Dict[str, str]]` - `max_workers: Optional[int]` - `memory: Optional[str]` - `min_workers: Optional[int]` - `model: Optional[str]` - `nodes_per_worker: Optional[int]` - `num_shards: Optional[int]` - `per_worker: Optional[int]` - `post_inference_hooks: Optional[Sequence[str]]` - `public_inference: Optional[bool]` - `quantize: Optional[str]` - `source: Optional[str]` - `storage: Optional[str]` - `model_metadata: Optional[Dict[str, object]]` - `class ModelSwapNamesModelPatchRequest: …` - `name: str` - `on_conflict: Optional[Literal["error", "swap"]]` - `"error"` - `"swap"` ### Returns - `class InferenceModel: …` - `id: str` The unique identifier of the entity. - `created_at: datetime` The date and time when the entity was created in ISO format. - `created_by_identity_type: Literal["user", "service_account"]` The type of identity that created the entity. - `"user"` - `"service_account"` - `created_by_user_id: str` The user who originally created the entity. - `model_type: InferenceModelType` - `"generic"` - `"completion"` - `"chat_completion"` - `model_vendor: InferenceModelVendor` - `"openai"` - `"cohere"` - `"vertex_ai"` - `"anthropic"` - `"azure"` - `"gemini"` - `"launch"` - `"llmengine"` - `"model_zoo"` - `"bedrock"` - `"xai"` - `"fireworks_ai"` - `name: str` - `status: Literal["failed", "ready", "deploying", "deployment_timeout"]` - `"failed"` - `"ready"` - `"deploying"` - `"deployment_timeout"` - `model_availability: Optional[InferenceModelAvailability]` - `"unknown"` - `"available"` - `"unavailable"` - `model_metadata: Optional[Dict[str, object]]` - `object: Optional[Literal["model"]]` - `"model"` - `status_reason: Optional[str]` - `vendor_configuration: Optional[VendorConfiguration]` - `class LaunchVendorConfiguration: …` - `model_image: ModelImage` - `command: List[str]` - `registry: str` - `repository: str` - `tag: str` - `env_vars: Optional[Dict[str, object]]` - `healthcheck_route: Optional[str]` - `predict_route: Optional[str]` - `readiness_delay: Optional[int]` - `request_schema: Optional[Dict[str, object]]` - `response_schema: Optional[Dict[str, object]]` - `streaming_command: Optional[List[str]]` - `streaming_predict_route: Optional[str]` - `model_infra: ModelInfra` - `cpus: Optional[Union[str, int, null]]` - `str` - `int` - `endpoint_type: Optional[Literal["async", "sync", "streaming"]]` - `"async"` - `"sync"` - `"streaming"` - `gpu_type: Optional[Literal["nvidia-tesla-t4", "nvidia-ampere-a10", "nvidia-ampere-a100", 4 more]]` - `"nvidia-tesla-t4"` - `"nvidia-ampere-a10"` - `"nvidia-ampere-a100"` - `"nvidia-ampere-a100e"` - `"nvidia-hopper-h100"` - `"nvidia-hopper-h100-1g20gb"` - `"nvidia-hopper-h100-3g40gb"` - `gpus: Optional[int]` - `high_priority: Optional[bool]` - `labels: Optional[Dict[str, str]]` - `max_workers: Optional[int]` - `memory: Optional[str]` - `min_workers: Optional[int]` - `per_worker: Optional[int]` - `public_inference: Optional[bool]` - `storage: Optional[str]` - `class LlmEngineVendorConfiguration: …` - `model: str` - `chat_template_override: Optional[str]` - `checkpoint_path: Optional[str]` - `cpus: Optional[int]` - `default_callback_url: Optional[str]` - `endpoint_type: Optional[str]` - `gpu_type: Optional[str]` - `gpus: Optional[int]` - `high_priority: Optional[bool]` - `inference_framework: Optional[str]` - `inference_framework_image_tag: Optional[str]` - `labels: Optional[Dict[str, str]]` - `max_workers: Optional[int]` - `memory: Optional[str]` - `min_workers: Optional[int]` - `nodes_per_worker: Optional[int]` - `num_shards: Optional[int]` - `per_worker: Optional[int]` - `post_inference_hooks: Optional[List[str]]` - `public_inference: Optional[bool]` - `quantize: Optional[str]` - `source: Optional[str]` - `storage: Optional[str]` ### Example ```python import os from scale_gp_beta import SGPClient client = SGPClient( api_key=os.environ.get("SGP_API_KEY"), # This is the default and can be omitted ) inference_model = client.models.update( model_id="model_id", model={}, ) print(inference_model.id) ``` #### Response ```json { "id": "id", "created_at": "2019-12-27T18:11:19.117Z", "created_by_identity_type": "user", "created_by_user_id": "created_by_user_id", "model_type": "generic", "model_vendor": "openai", "name": "name", "status": "failed", "model_availability": "unknown", "model_metadata": { "foo": "bar" }, "object": "model", "status_reason": "status_reason", "vendor_configuration": { "model_image": { "command": [ "string" ], "registry": "registry", "repository": "repository", "tag": "tag", "env_vars": { "foo": "bar" }, "healthcheck_route": "healthcheck_route", "predict_route": "predict_route", "readiness_delay": 0, "request_schema": { "foo": "bar" }, "response_schema": { "foo": "bar" }, "streaming_command": [ "string" ], "streaming_predict_route": "streaming_predict_route" }, "model_infra": { "cpus": "string", "endpoint_type": "async", "gpu_type": "nvidia-tesla-t4", "gpus": 0, "high_priority": true, "labels": { "foo": "string" }, "max_workers": 0, "memory": "memory", "min_workers": 0, "per_worker": 0, "public_inference": true, "storage": "storage" } } } ```