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    Manage search config

    Restriction

    If there is a facet property in search config, its mapped fields should always match those in search criteria property. These fields should be the existing data schema with the same type, granularity, and search strategy.

    Create a search config

    REST

    To create a SearchConfig resource, send a POST request by using the projects.locations.corpora.searchConfigs.create method.

    Here is the example of how to create a search config with customized search criteria.

    Before using any of the request data, make the following replacements:

    • REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
    • PROJECT_NUMBER : Your Google Cloud project number .
    • LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
    • CORPUS_ID : The ID of your target corpus.
    • SEARCHCONFIG : The name of your target SearchConfig .
      • The SearchConfig in this example is person .

    HTTP method and URL:

    POST https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs ?search_config_id= 
 person

    Request JSON body:

    {
   "search_criteria_property": {
     "mapped_fields": "player" 
,
     "mapped_fields": "coach" 
,
     "mapped_fields": "cheerleader" 
,
  }
}

    To send your request, choose one of these options:

    curl

    Save the request body in a file named request.json , and execute the following command:

    curl -X POST \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    -H "Content-Type: application/json; charset=utf-8" \
    -d @request.json \
    "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs ?search_config_id= 
 person 
"

    PowerShell

    Save the request body in a file named request.json , and execute the following command:

    $cred = gcloud auth print-access-token
    $headers = @{ "Authorization" = "Bearer $cred" }

    Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs ?search_config_id= 
 person 
" | Select-Object -Expand Content

    You should receive a JSON response similar to the following:

    {
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/person",
  "searchCriteriaProperty":
    {
      "mappedFields": [ "player" 
, "coach" 
, "cheerleader" 
]
    }
}

    Update a search config

    REST

    To update a SearchConfig resource, send a POST request by using the projects.locations.corpora.searchConfigs.patch method.

    Here is the example of how to create a search config with customized search criteria.

    Before using any of the request data, make the following replacements:

    • REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
    • PROJECT : Your Google Cloud project ID or project number .
    • LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
    • CORPUS_ID : The ID of your target corpus.
    • SEARCHCONFIG_ID : The ID of your target SearchConfig .
    • "mappedFields" : One or more existing user-given annotation keys.

    HTTP method and URL:

    PATCH https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID

    Request JSON body:

    {
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID1 
",
  "searchCriteriaProperty": {
    "mappedFields": " dataschema2 
"
  }
}

    To send your request, choose one of these options:

    curl

    Save the request body in a file named request.json , and execute the following command:

    curl -X PATCH \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    -H "Content-Type: application/json; charset=utf-8" \
    -d @request.json \
    "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID 
"

    PowerShell

    Save the request body in a file named request.json , and execute the following command:

    $cred = gcloud auth print-access-token
    $headers = @{ "Authorization" = "Bearer $cred" }

    Invoke-WebRequest `
    -Method PATCH `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID 
" | Select-Object -Expand Content

    You should receive a JSON response similar to the following:

    {
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID1 
",
  "searchCriteriaProperty": {
    "mappedFields": [
      " dataschema2 
"
    ]
  }
}

    Get a search config

    The following example shows you how to retrieve an existing SearchConfig that makes it easier to search for people in warehouse-stored data.

    REST

    To get details about a SearchConfig , send a GET request by using the projects.locations.corpora.searchConfigs.get method.

    Before using any of the request data, make the following replacements:

    • REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
    • PROJECT_NUMBER : Your Google Cloud project number .
    • LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
    • CORPUS_ID : The ID of your target corpus.
    • SEARCHCONFIG : The name of your target SearchConfig .
      • The SearchConfig in this example is person .

    HTTP method and URL:

    GET https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG

    To send your request, choose one of these options:

    curl

    Execute the following command:

    curl -X GET \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG 
"

    PowerShell

    Execute the following command:

    $cred = gcloud auth print-access-token
    $headers = @{ "Authorization" = "Bearer $cred" }

    Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG 
" | Select-Object -Expand Content

    You should receive a JSON response similar to the following:

    {
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ person 
"
  "facet_property": {
    // Top-level facet group name.
    "display_name": "Person",
    // Each mapped_field will be displayed in the UI as a selectable value
    // under "Person".
    "mapped_fields": "player",
    // The maximum number of mapped_fields to be displayed.
    "result_size": 2,
    // The facet type is a singular value. In this case, type string.
    "bucket_type": FACET_BUCKET_TYPE_VALUE
  }
}

    List search configs

    The following example shows you how to list all previously created SearchConfig resources.

    You can specify the number of search configs listed by setting the page_size field in your request.

    REST

    To list all search configs, send a GET request by using the projects.locations.corpora.searchConfigs.list method.

    In this example, the page_size field is set to 2, limiting the response to two search configs. If the page size is not specified, the default value of 25 is used.

    Before using any of the request data, make the following replacements:

    • REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
    • PROJECT_NUMBER : Your Google Cloud project number .
    • LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
    • CORPUS_ID : The ID of your target corpus.
    • PAGE_SIZE : ( Optional ) The number of results to return.

    HTTP method and URL:

    GET https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs ?page_size=2

    To send your request, choose one of these options:

    curl

    Execute the following command:

    curl -X GET \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs ?page_size=2 
"

    PowerShell

    Execute the following command:

    $cred = gcloud auth print-access-token
    $headers = @{ "Authorization" = "Bearer $cred" }

    Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs ?page_size=2 
" | Select-Object -Expand Content

    You should receive a JSON response similar to the following:

    {
  "next_page_token": " xyz 
",
  "search_configs": {
    "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ person 
",
    "facet_property": {
      // Top-level facet group name.
      "display_name": "Person",
      // Each mapped_field will be displayed in the console as a selectable value
      // under "Person".
      "mapped_fields": "player",
      // The maximum number of mapped_fields to be displayed.
      "result_size": 2,
      // The facet type is a singular value. In this case, type string.
      "bucket_type": FACET_BUCKET_TYPE_VALUE
    }
  },
  "search_configs": {
    "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ location 
",
    "facet_property": {
      // Top-level facet group name.
      "display_name": "location",
      // Each mapped_field will be displayed in the console as a selectable value
      // under "location".
      "mapped_fields": "city",
      // The maximum number of mapped_fields to be displayed.
      "result_size": 2,
      // The facet type is a singular value. In this case, type string.
      "bucket_type": FACET_BUCKET_TYPE_VALUE
    }
  }
}

    The response only contains two SearchConfigs because in the request, the page_size=2 field is set. To view the next page of search configs, include the previous response's next_page_token setting in your next request:

    • https://warehouse-visionai.googleapis.com/v1alpha/ [...] /searchConfigs ?page_size= 2 &page_token=' xyz '

    Delete a search config

    REST & CMD LINE

    The following code sample uses the projects.locations.corpora.searchConfigs.delete method to delete a SearchConfig . The SearchConfig must exist for this request to succeed.

    Before using any of the request data, make the following replacements:

    • REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
    • PROJECT_NUMBER : Your Google Cloud project number .
    • LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
    • CORPUS_ID : The ID of your target corpus.
    • SEARCHCONFIG_ID : The ID of your target SearchConfig .

    HTTP method and URL:

    DELETE https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID

    To send your request, choose one of these options:

    curl

    Execute the following command:

    curl -X DELETE \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID 
"

    PowerShell

    Execute the following command:

    $cred = gcloud auth print-access-token
    $headers = @{ "Authorization" = "Bearer $cred" }

    Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/searchConfigs/ SEARCHCONFIG_ID 
" | Select-Object -Expand Content

    You should receive a JSON response similar to the following:

    {}
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