You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
endpoint: string, Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` (required)
2456
+
body: object, The request body.
2457
+
The object takes the form of:
2458
+
2459
+
{ # Request message for PredictionService.StreamRawPredict.
2460
+
"httpBody": { # Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged. # The prediction input. Supports HTTP headers and arbitrary data payload.
2461
+
"contentType": "A String", # The HTTP Content-Type header value specifying the content type of the body.
2462
+
"data": "A String", # The HTTP request/response body as raw binary.
2463
+
"extensions": [ # Application specific response metadata. Must be set in the first response for streaming APIs.
2464
+
{
2465
+
"a_key": "", # Properties of the object. Contains field @type with type URL.
2466
+
},
2467
+
],
2468
+
},
2469
+
}
2470
+
2471
+
x__xgafv: string, V1 error format.
2472
+
Allowed values
2473
+
1 - v1 error format
2474
+
2 - v2 error format
2475
+
2476
+
Returns:
2477
+
An object of the form:
2478
+
2479
+
{ # Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged.
2480
+
"contentType": "A String", # The HTTP Content-Type header value specifying the content type of the body.
2481
+
"data": "A String", # The HTTP request/response body as raw binary.
2482
+
"extensions": [ # Application specific response metadata. Must be set in the first response for streaming APIs.
2483
+
{
2484
+
"a_key": "", # Properties of the object. Contains field @type with type URL.
Copy file name to clipboardexpand all lines: docs/dyn/aiplatform_v1.projects.locations.featureOnlineStores.html
+1-1
Original file line number
Diff line number
Diff line change
@@ -116,7 +116,7 @@ <h3>Method Details</h3>
116
116
<pre>Creates a new FeatureOnlineStore in a given project and location.
117
117
118
118
Args:
119
-
parent: string, Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}'` (required)
119
+
parent: string, Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}` (required)
Copy file name to clipboardexpand all lines: docs/dyn/aiplatform_v1.projects.locations.models.html
+7-7
Original file line number
Diff line number
Diff line change
@@ -497,7 +497,7 @@ <h3>Method Details</h3>
497
497
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
498
498
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
499
499
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
500
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
500
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
501
501
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
502
502
"sourceType": "A String", # Type of the model source.
503
503
},
@@ -745,7 +745,7 @@ <h3>Method Details</h3>
745
745
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
746
746
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
747
747
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
748
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
748
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
749
749
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
750
750
"sourceType": "A String", # Type of the model source.
751
751
},
@@ -996,7 +996,7 @@ <h3>Method Details</h3>
996
996
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
997
997
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
998
998
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
999
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
999
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
1000
1000
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
1001
1001
"sourceType": "A String", # Type of the model source.
1002
1002
},
@@ -1277,7 +1277,7 @@ <h3>Method Details</h3>
1277
1277
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
1278
1278
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
1279
1279
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
1280
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
1280
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
1281
1281
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
1282
1282
"sourceType": "A String", # Type of the model source.
1283
1283
},
@@ -1513,7 +1513,7 @@ <h3>Method Details</h3>
1513
1513
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
1514
1514
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
1515
1515
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
1516
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
1516
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
1517
1517
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
1518
1518
"sourceType": "A String", # Type of the model source.
1519
1519
},
@@ -1748,7 +1748,7 @@ <h3>Method Details</h3>
1748
1748
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
1749
1749
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
1750
1750
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
1751
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
1751
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
1752
1752
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
1753
1753
"sourceType": "A String", # Type of the model source.
1754
1754
},
@@ -2042,7 +2042,7 @@ <h3>Method Details</h3>
2042
2042
"metadata": "", # Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
2043
2043
"metadataArtifact": "A String", # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
2044
2044
"metadataSchemaUri": "A String", # Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
2045
-
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
2045
+
"modelSourceInfo": { # Detail description of the source information of the model. # Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.
2046
2046
"copy": True or False, # If this Model is copy of another Model. If true then source_type pertains to the original.
2047
2047
"sourceType": "A String", # Type of the model source.
0 commit comments