Import files from Google Cloud Storage or Google Drive into a RagCorpus.
Endpoint
post
https://{service-endpoint}/v1beta1/{parent}/ragFiles:import
Where {service-endpoint}
is one of the supported service endpoints.
Path parameters
parent
string
Required. The name of the RagCorpus resource into which to import files. Format: projects/{project}/locations/{location}/ragCorpora/{ragCorpus}
Request body
The request body contains data with the following structure:
Required. The config for the RagFiles to be synced and imported into the RagCorpus. VertexRagDataService.ImportRagFiles
.
Response body
If successful, the response body contains an instance of Operation
.
ImportRagFilesConfig
Config for importing RagFiles.
Specifies the size and overlap of chunks after importing RagFiles.
maxEmbeddingRequestsPerMin
integer
Optional. The max number of queries per minute that this job is allowed to make to the embedding model specified on the corpus. This value is specific to this job and not shared across other import jobs. Consult the Quotas page on the project to set an appropriate value here. If unspecified, a default value of 1,000 QPM would be used.
import_source
. The source of the import. import_source
can be only one of the following:Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - gs://bucketName/my_directory/objectName/my_file.txt
- gs://bucketName/my_directory
Google Drive location. Supports importing individual files as well as Google Drive folders.
Slack channels with their corresponding access tokens.
Jira queries with their corresponding authentication.
JSON representation |
---|
{ "ragFileChunkingConfig": { object ( |