- HTTP request
- Path parameters
- Request body
- Response body
- Authorization scopes
- CustomTuningModel
- ModelState
Gets a list of all the custom models.
HTTP request
GET https://discoveryengine.googleapis.com/v1/{dataStore=projects/*/locations/*/collections/*/dataStores/*}/customModels
The URL uses gRPC Transcoding syntax.
Path parameters
Parameters | |
---|---|
data |
Required. The resource name of the parent Data Store, such as |
Request body
The request body must be empty.
Response body
Response message for SearchTuningService.ListCustomModels
method.
If successful, the response body contains data with the following structure:
JSON representation |
---|
{
"models": [
{
object ( |
Fields | |
---|---|
models[] |
List of custom tuning models. |
Authorization scopes
Requires the following OAuth scope:
https://www.googleapis.com/auth/cloud-platform
For more information, see the Authentication Overview.
CustomTuningModel
Metadata that describes a custom tuned model.
JSON representation |
---|
{
"name": string,
"displayName": string,
"modelVersion": string,
"modelState": enum ( |
Fields | |
---|---|
name |
Required. The fully qualified resource name of the model. Format: Model must be an alpha-numerical string with limit of 40 characters. |
display |
The display name of the model. |
model |
The version of the model. |
model |
The state that the model is in (e.g. |
createTime |
Deprecated: Timestamp the Model was created at. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
training |
Timestamp the model training was initiated. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
metrics |
The metrics of the trained model. |
error |
Currently this is only populated if the model state is |
ModelState
The state of the model.
Enums | |
---|---|
MODEL_STATE_UNSPECIFIED |
Default value. |
TRAINING_PAUSED |
The model is in a paused training state. |
TRAINING |
The model is currently training. |
TRAINING_COMPLETE |
The model has successfully completed training. |
READY_FOR_SERVING |
The model is ready for serving. |
TRAINING_FAILED |
The model training failed. |
NO_IMPROVEMENT |
The model training finished successfully but metrics did not improve. |
INPUT_VALIDATION_FAILED |
Input data validation failed. Model training didn't start. |