刷新健康数据

使用集合让一切井井有条 根据您的偏好保存内容并对其进行分类。

REST

1. 执行增量导入。

   curl -X POST \
   -H "Authorization: Bearer $(gcloud auth print-access-token)" \
   -H "Content-Type: application/json; charset=utf-8" \
   -H "X-Goog-User-Project: PROJECT_ID" \
   "https://us-discoveryengine.googleapis.com/v1alpha/projects/PROJECT_ID/locations/us/dataStores/DATA_STORE_ID/branches/0/documents:import" \
   -d '{
      "reconciliation_mode": "INCREMENTAL",
      "fhir_store_source": {"fhir_store": "projects/PROJECT_ID/locations/CLOUD_HEALTHCARE_DATASET_LOCATION/datasets/CLOUD_HEALTHCARE_DATASET_ID/fhirStores/FHIR_STORE_ID"}
   }'
   

   替换以下内容：

   • PROJECT_ID：您的 Google Cloud 项目的 ID。
   • DATA_STORE_ID：Vertex AI Search 数据存储区的 ID。
   • CLOUD_HEALTHCARE_DATASET_ID：包含源 FHIR 存储区的 Cloud Healthcare API 数据集的 ID。
   • CLOUD_HEALTHCARE_DATASET_LOCATION：包含源 FHIR 存储区的 Cloud Healthcare API 数据集的位置。
   • FHIR_STORE_ID：Cloud Healthcare API FHIR R4 存储区的 ID。

   响应

   您应该收到类似以下内容的 JSON 响应。响应包含长时间运行的操作的标识符。当方法调用可能需要大量时间才能完成时，会返回长时间运行的操作。记下 IMPORT_OPERATION_ID 的值。您需要此值来验证导入的状态。

     {
       "name": "projects/PROJECT_ID/locations/us/collections/default_collection/dataStores/DATA_STORE_ID/branches/0/operations/IMPORT_OPERATION_ID",
       "metadata": {
         "@type": "type.googleapis.com/google.cloud.discoveryengine.v1alpha.ImportDocumentsMetadata"
       }
     }
   

2. 验证 FHIR 数据导入操作是否已完成。

   curl -X GET \
   -H "Authorization: Bearer $(gcloud auth print-access-token)" \
   "https://us-discoveryengine.googleapis.com/v1alpha/projects/PROJECT_ID/locations/us/collections/default_collection/dataStores/DATA_STORE_ID/branches/0/operations/IMPORT_OPERATION_ID"
   

   替换以下内容：

   • PROJECT_ID：您的 Google Cloud 项目的 ID。
   • DATA_STORE_ID：Vertex AI Search 数据存储区的 ID。
   • IMPORT_OPERATION_ID：调用 import 方法时返回的长时间运行的操作的操作 ID。

   响应

   您应该收到类似以下内容的 JSON 响应。导入操作是一项长时间运行的操作。操作运行期间，响应包含以下字段：

   • successCount：表示到目前为止成功导入的 FHIR 资源的数量。
   • failureCount：表示到目前为止未能导入的 FHIR 资源的数量。只有在有任何 FHIR 资源导入失败时，才会显示此字段。

   操作完成后，响应将包含以下字段：

   • successCount：表示成功导入的 FHIR 资源的数量。
   • failureCount：表示无法导入的 FHIR 资源的数量。只有在有任何 FHIR 资源导入失败时，才会显示此字段。
   • totalCount：表示源 FHIR 存储区中存在的 FHIR 资源数量。只有在有任何 FHIR 资源导入失败时，才会显示此字段。
   • done：值为 true，表示导入操作已完成
   • errorSamples：提供有关未能导入的资源的信息。只有在有任何 FHIR 资源导入失败时，才会显示此字段。
   • errorConfig：提供包含错误摘要日志文件的 Cloud Storage 位置的路径。

   {
    "name": "projects/PROJECT_ID/locations/us/collections/default_collection/dataStores/DATA_STORE_ID/branches/0/operations/IMPORT_OPERATION_ID",
    "metadata": {
      "@type": "type.googleapis.com/google.cloud.discoveryengine.v1alpha.ImportDocumentsMetadata",
      "createTime": "START_TIMESTAMP",
      "updateTime": "END_TIMESTAMP",
      "successCount": "SUCCESS_COUNT",
      "failureCount": "FAILURE_COUNT",
      "totalCount": "TOTAL_COUNT",
    },
    "done": true,
    "response": {
      "@type": "type.googleapis.com/google.cloud.discoveryengine.v1alpha.ImportDocumentsResponse",
     "errorSamples": [ERROR_SAMPLE],
     "errorConfig": {
        "gcsPrefix": "LOG_FILE_LOCATION"
      }
    }
   }
   

Python

如需了解详情，请参阅 Vertex AI Agent Builder Python API 参考文档。

如需向 Vertex AI Agent Builder 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

from google.api_core.client_options import ClientOptions
from google.cloud import discoveryengine

# TODO(developer): Uncomment these variables before running the sample.
# project_id = "YOUR_PROJECT_ID"
# location = "YOUR_LOCATION" # Values: "us"
# data_store_id = "YOUR_DATA_STORE_ID"
# healthcare_project_id = "YOUR_HEALTHCARE_PROJECT_ID"
# healthcare_location = "YOUR_HEALTHCARE_LOCATION"
# healthcare_dataset_id = "YOUR_HEALTHCARE_DATASET_ID"
# healthcare_fihr_store_id = "YOUR_HEALTHCARE_FHIR_STORE_ID"

#  For more information, refer to:
# https://cloud.google.com/generative-ai-app-builder/docs/locations#specify_a_multi-region_for_your_data_store
client_options = (
    ClientOptions(api_endpoint=f"{location}-discoveryengine.googleapis.com")
    if location != "global"
    else None
)

# Create a client
client = discoveryengine.DocumentServiceClient(client_options=client_options)

# The full resource name of the search engine branch.
# e.g. projects/{project}/locations/{location}/dataStores/{data_store_id}/branches/{branch}
parent = client.branch_path(
    project=project_id,
    location=location,
    data_store=data_store_id,
    branch="default_branch",
)

request = discoveryengine.ImportDocumentsRequest(
    parent=parent,
    fhir_store_source=discoveryengine.FhirStoreSource(
        fhir_store=client.fhir_store_path(
            healthcare_project_id,
            healthcare_location,
            healthcare_dataset_id,
            healthcare_fihr_store_id,
        ),
    ),
    # Options: `FULL`, `INCREMENTAL`
    reconciliation_mode=discoveryengine.ImportDocumentsRequest.ReconciliationMode.INCREMENTAL,
)

# Make the request
operation = client.import_documents(request=request)

print(f"Waiting for operation to complete: {operation.operation.name}")
response = operation.result()

# After the operation is complete,
# get information from operation metadata
metadata = discoveryengine.ImportDocumentsMetadata(operation.metadata)

# Handle the response
print(response)
print(metadata)