GoogleCloudContentwarehouseV1GcsIngestWithDocAiProcessorsPipeline
Content Warehouse V1InfrastructureGoogleApi.ContentWarehouse.V1.Model.GoogleCloudContentwarehouseV1GcsIngestWithDocAiProcessorsPipeline
SEO Analysis
AI GeneratedBackend infrastructure with indirect SEO impact. This model (Google Cloud Contentwarehouse V1 Gcs Ingest With Doc Ai Processors Pipeline) contains 6 attributes that define its data structure. Key functionality includes: The extract processors information. One matched extract processor will be used to process documents based on the classify processor result. If no clas...
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Attributes
6extractProcessorInfosGoogleCloudContentwarehouseV1ProcessorInfo →nilFull type: list(GoogleApi.ContentWarehouse.V1.Model.GoogleCloudContentwarehouseV1ProcessorInfo.tThe extract processors information. One matched extract processor will be used to process documents based on the classify processor result. If no classify processor is specified, the first extract processor will be used.
inputPathstringnilFull type: String.tThe input Cloud Storage folder. All files under this folder will be imported to Document Warehouse. Format: gs:///.
pipelineConfigGoogleCloudContentwarehouseV1IngestPipelineConfig →nilFull type: GoogleApi.ContentWarehouse.V1.Model.GoogleCloudContentwarehouseV1IngestPipelineConfig.tOptional. The config for the Cloud Storage Ingestion with DocAI Processors pipeline. It provides additional customization options to run the pipeline and can be skipped if it is not applicable.
processorResultsFolderPathstringnilFull type: String.tThe Cloud Storage folder path used to store the raw results from processors. Format: gs:///.
skipIngestedDocumentsboolean(nilThe flag whether to skip ingested documents. If it is set to true, documents in Cloud Storage contains key "status" with value "status=ingested" in custom metadata will be skipped to ingest.
splitClassifyProcessorInfoGoogleCloudContentwarehouseV1ProcessorInfo →nilFull type: GoogleApi.ContentWarehouse.V1.Model.GoogleCloudContentwarehouseV1ProcessorInfo.tThe split and classify processor information. The split and classify result will be used to find a matched extract processor.