Documentation
¶
Overview ¶
Create an OpenAI inference endpoint.
Create an inference endpoint to perform an inference task with the `openai` service or `openai` compatible APIs.
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 NewPutOpenai
- type PutOpenai
- func (r *PutOpenai) ChunkingSettings(chunkingsettings types.InferenceChunkingSettingsVariant) *PutOpenai
- func (r PutOpenai) Do(providedCtx context.Context) (*Response, error)
- func (r *PutOpenai) ErrorTrace(errortrace bool) *PutOpenai
- func (r *PutOpenai) FilterPath(filterpaths ...string) *PutOpenai
- func (r *PutOpenai) Header(key, value string) *PutOpenai
- func (r *PutOpenai) HttpRequest(ctx context.Context) (*http.Request, error)
- func (r *PutOpenai) Human(human bool) *PutOpenai
- func (r PutOpenai) Perform(providedCtx context.Context) (*http.Response, error)
- func (r *PutOpenai) Pretty(pretty bool) *PutOpenai
- func (r *PutOpenai) Raw(raw io.Reader) *PutOpenai
- func (r *PutOpenai) Request(req *Request) *PutOpenai
- func (r *PutOpenai) Service(service openaiservicetype.OpenAIServiceType) *PutOpenai
- func (r *PutOpenai) ServiceSettings(servicesettings types.OpenAIServiceSettingsVariant) *PutOpenai
- func (r *PutOpenai) TaskSettings(tasksettings types.OpenAITaskSettingsVariant) *PutOpenai
- 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 NewPutOpenai ¶
NewPutOpenai type alias for index.
func NewPutOpenaiFunc ¶
func NewPutOpenaiFunc(tp elastictransport.Interface) NewPutOpenai
NewPutOpenaiFunc returns a new instance of PutOpenai with the provided transport. Used in the index of the library this allows to retrieve every apis in once place.
type PutOpenai ¶
type PutOpenai struct {
// contains filtered or unexported fields
}
func New ¶
func New(tp elastictransport.Interface) *PutOpenai
Create an OpenAI inference endpoint.
Create an inference endpoint to perform an inference task with the `openai` service or `openai` compatible APIs.
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-openai.html
func (*PutOpenai) ChunkingSettings ¶
func (r *PutOpenai) ChunkingSettings(chunkingsettings types.InferenceChunkingSettingsVariant) *PutOpenai
The chunking configuration object. API name: chunking_settings
func (PutOpenai) Do ¶
Do runs the request through the transport, handle the response and returns a putopenai.Response
func (*PutOpenai) ErrorTrace ¶
ErrorTrace When set to `true` Elasticsearch will include the full stack trace of errors when they occur. API name: error_trace
func (*PutOpenai) FilterPath ¶
FilterPath Comma-separated list of filters in dot notation which reduce the response returned by Elasticsearch. API name: filter_path
func (*PutOpenai) HttpRequest ¶
HttpRequest returns the http.Request object built from the given parameters.
func (*PutOpenai) Human ¶
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 (PutOpenai) Perform ¶
Perform runs the http.Request through the provided transport and returns an http.Response.
func (*PutOpenai) Pretty ¶
Pretty If set to `true` the returned JSON will be "pretty-formatted". Only use this option for debugging only. API name: pretty
func (*PutOpenai) Raw ¶
Raw takes a json payload as input which is then passed to the http.Request If specified Raw takes precedence on Request method.
func (*PutOpenai) Request ¶
Request allows to set the request property with the appropriate payload.
func (*PutOpenai) Service ¶
func (r *PutOpenai) Service(service openaiservicetype.OpenAIServiceType) *PutOpenai
The type of service supported for the specified task type. In this case, `openai`. API name: service
func (*PutOpenai) ServiceSettings ¶
func (r *PutOpenai) ServiceSettings(servicesettings types.OpenAIServiceSettingsVariant) *PutOpenai
Settings used to install the inference model. These settings are specific to the `openai` service. API name: service_settings
func (*PutOpenai) TaskSettings ¶
func (r *PutOpenai) TaskSettings(tasksettings types.OpenAITaskSettingsVariant) *PutOpenai
Settings to configure the inference task. These settings are specific to the task type you specified. API name: task_settings
type Request ¶
type Request struct { // ChunkingSettings The chunking configuration object. ChunkingSettings *types.InferenceChunkingSettings `json:"chunking_settings,omitempty"` // Service The type of service supported for the specified task type. In this case, // `openai`. Service openaiservicetype.OpenAIServiceType `json:"service"` // ServiceSettings Settings used to install the inference model. These settings are specific to // the `openai` service. ServiceSettings types.OpenAIServiceSettings `json:"service_settings"` // TaskSettings Settings to configure the inference task. // These settings are specific to the task type you specified. TaskSettings *types.OpenAITaskSettings `json:"task_settings,omitempty"` }
Request holds the request body struct for the package putopenai
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 putopenai