Documentation
¶
Overview ¶
Create a Watsonx inference endpoint.
Create an inference endpoint to perform an inference task with the `watsonxai` service. You need an IBM Cloud Databases for Elasticsearch deployment to use the `watsonxai` inference service. You can provision one through the IBM catalog, the Cloud Databases CLI plug-in, the Cloud Databases API, or Terraform.
When you create an inference endpoint, the associated machine learning model is automatically deployed if it is not already running. After creating the endpoint, wait for the model deployment to complete before using it. To verify the deployment status, use the get trained model statistics API. Look for `"state": "fully_allocated"` in the response and ensure that the `"allocation_count"` matches the `"target_allocation_count"`. Avoid creating multiple endpoints for the same model unless required, as each endpoint consumes significant resources.
Index ¶
- Variables
- type NewPutWatsonx
- type PutWatsonx
- func (r PutWatsonx) Do(providedCtx context.Context) (*Response, error)
- func (r *PutWatsonx) ErrorTrace(errortrace bool) *PutWatsonx
- func (r *PutWatsonx) FilterPath(filterpaths ...string) *PutWatsonx
- func (r *PutWatsonx) Header(key, value string) *PutWatsonx
- func (r *PutWatsonx) HttpRequest(ctx context.Context) (*http.Request, error)
- func (r *PutWatsonx) Human(human bool) *PutWatsonx
- func (r PutWatsonx) Perform(providedCtx context.Context) (*http.Response, error)
- func (r *PutWatsonx) Pretty(pretty bool) *PutWatsonx
- func (r *PutWatsonx) Raw(raw io.Reader) *PutWatsonx
- func (r *PutWatsonx) Request(req *Request) *PutWatsonx
- func (r *PutWatsonx) Service(service watsonxservicetype.WatsonxServiceType) *PutWatsonx
- func (r *PutWatsonx) ServiceSettings(servicesettings types.WatsonxServiceSettingsVariant) *PutWatsonx
- type Request
- type Response
Constants ¶
This section is empty.
Variables ¶
var ErrBuildPath = errors.New("cannot build path, check for missing path parameters")
ErrBuildPath is returned in case of missing parameters within the build of the request.
Functions ¶
This section is empty.
Types ¶
type NewPutWatsonx ¶
type NewPutWatsonx func(tasktype, watsonxinferenceid string) *PutWatsonx
NewPutWatsonx type alias for index.
func NewPutWatsonxFunc ¶
func NewPutWatsonxFunc(tp elastictransport.Interface) NewPutWatsonx
NewPutWatsonxFunc returns a new instance of PutWatsonx with the provided transport. Used in the index of the library this allows to retrieve every apis in once place.
type PutWatsonx ¶
type PutWatsonx struct {
// contains filtered or unexported fields
}
func New ¶
func New(tp elastictransport.Interface) *PutWatsonx
Create a Watsonx inference endpoint.
Create an inference endpoint to perform an inference task with the `watsonxai` service. You need an IBM Cloud Databases for Elasticsearch deployment to use the `watsonxai` inference service. You can provision one through the IBM catalog, the Cloud Databases CLI plug-in, the Cloud Databases API, or Terraform.
When you create an inference endpoint, the associated machine learning model is automatically deployed if it is not already running. After creating the endpoint, wait for the model deployment to complete before using it. To verify the deployment status, use the get trained model statistics API. Look for `"state": "fully_allocated"` in the response and ensure that the `"allocation_count"` matches the `"target_allocation_count"`. Avoid creating multiple endpoints for the same model unless required, as each endpoint consumes significant resources.
https://www.elastic.co/guide/en/elasticsearch/reference/current/infer-service-watsonx-ai.html
func (PutWatsonx) Do ¶
func (r PutWatsonx) Do(providedCtx context.Context) (*Response, error)
Do runs the request through the transport, handle the response and returns a putwatsonx.Response
func (*PutWatsonx) ErrorTrace ¶
func (r *PutWatsonx) ErrorTrace(errortrace bool) *PutWatsonx
ErrorTrace When set to `true` Elasticsearch will include the full stack trace of errors when they occur. API name: error_trace
func (*PutWatsonx) FilterPath ¶
func (r *PutWatsonx) FilterPath(filterpaths ...string) *PutWatsonx
FilterPath Comma-separated list of filters in dot notation which reduce the response returned by Elasticsearch. API name: filter_path
func (*PutWatsonx) Header ¶
func (r *PutWatsonx) Header(key, value string) *PutWatsonx
Header set a key, value pair in the PutWatsonx headers map.
func (*PutWatsonx) HttpRequest ¶
HttpRequest returns the http.Request object built from the given parameters.
func (*PutWatsonx) Human ¶
func (r *PutWatsonx) Human(human bool) *PutWatsonx
Human When set to `true` will return statistics in a format suitable for humans. For example `"exists_time": "1h"` for humans and `"eixsts_time_in_millis": 3600000` for computers. When disabled the human readable values will be omitted. This makes sense for responses being consumed only by machines. API name: human
func (PutWatsonx) Perform ¶
Perform runs the http.Request through the provided transport and returns an http.Response.
func (*PutWatsonx) Pretty ¶
func (r *PutWatsonx) Pretty(pretty bool) *PutWatsonx
Pretty If set to `true` the returned JSON will be "pretty-formatted". Only use this option for debugging only. API name: pretty
func (*PutWatsonx) Raw ¶
func (r *PutWatsonx) Raw(raw io.Reader) *PutWatsonx
Raw takes a json payload as input which is then passed to the http.Request If specified Raw takes precedence on Request method.
func (*PutWatsonx) Request ¶
func (r *PutWatsonx) Request(req *Request) *PutWatsonx
Request allows to set the request property with the appropriate payload.
func (*PutWatsonx) Service ¶
func (r *PutWatsonx) Service(service watsonxservicetype.WatsonxServiceType) *PutWatsonx
The type of service supported for the specified task type. In this case, `watsonxai`. API name: service
func (*PutWatsonx) ServiceSettings ¶
func (r *PutWatsonx) ServiceSettings(servicesettings types.WatsonxServiceSettingsVariant) *PutWatsonx
Settings used to install the inference model. These settings are specific to the `watsonxai` service. API name: service_settings
type Request ¶
type Request struct { // Service The type of service supported for the specified task type. In this case, // `watsonxai`. Service watsonxservicetype.WatsonxServiceType `json:"service"` // ServiceSettings Settings used to install the inference model. These settings are specific to // the `watsonxai` service. ServiceSettings types.WatsonxServiceSettings `json:"service_settings"` }
Request holds the request body struct for the package putwatsonx
type Response ¶
type Response struct { // ChunkingSettings Chunking configuration object ChunkingSettings *types.InferenceChunkingSettings `json:"chunking_settings,omitempty"` // InferenceId The inference Id InferenceId string `json:"inference_id"` // Service The service type Service string `json:"service"` // ServiceSettings Settings specific to the service ServiceSettings json.RawMessage `json:"service_settings"` // TaskSettings Task settings specific to the service and task type TaskSettings json.RawMessage `json:"task_settings,omitempty"` // TaskType The task type TaskType tasktype.TaskType `json:"task_type"` }
Response holds the response body struct for the package putwatsonx