工具箱 - 创建文档批次
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。
创建一批文档,以便使用 batch_process_documents()
进行处理。
深入探索
如需查看包含此代码示例的详细文档,请参阅以下内容:
代码示例
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[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],[],[[["\u003cp\u003eThe \u003ccode\u003ecreate_batches_sample()\u003c/code\u003e function creates batches of documents from a specified Google Cloud Storage (GCS) location for processing.\u003c/p\u003e\n"],["\u003cp\u003eBatches are created from documents located within a specified GCS bucket and prefix, with the size of each batch determined by the \u003ccode\u003ebatch_size\u003c/code\u003e parameter.\u003c/p\u003e\n"],["\u003cp\u003eThe code provides a method to generate batches that can be utilized as input for \u003ccode\u003ebatch_process_documents()\u003c/code\u003e, which is further explained in the provided link to send a batch processing request.\u003c/p\u003e\n"],["\u003cp\u003eTo use the code, you need to configure Application Default Credentials (ADC) for authentication with Document AI, as well as setting the GCS bucket name, GCS prefix, and the desired batch size.\u003c/p\u003e\n"]]],[],null,["# Toolbox - Create document batches\n\nCreate batches of documents for processing with `batch_process_documents()`.\n\nExplore further\n---------------\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [Document AI Toolbox client libraries](/document-ai/docs/toolbox)\n- [Handle processing response](/document-ai/docs/handle-response)\n- [Send a processing request](/document-ai/docs/send-request)\n\nCode sample\n-----------\n\n### Python\n\n\nFor more information, see the\n[Document AI Python API\nreference documentation](/python/docs/reference/documentai/latest).\n\n\nTo authenticate to Document AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n\n from google.cloud import documentai\n from google.cloud.documentai_toolbox import https://cloud.google.com/python/docs/reference/documentai-toolbox/latest/google.cloud.documentai_toolbox.utilities.gcs_utilities.html\n\n # TODO(developer): Uncomment these variables before running the sample.\n # Given unprocessed documents in path gs://bucket/path/to/folder\n # gcs_bucket_name = \"bucket\"\n # gcs_prefix = \"path/to/folder\"\n # batch_size = 50\n\n\n def create_batches_sample(\n gcs_bucket_name: str,\n gcs_prefix: str,\n batch_size: int = 50,\n ) -\u003e None:\n # Creating batches of documents for processing\n batches = https://cloud.google.com/python/docs/reference/documentai-toolbox/latest/google.cloud.documentai_toolbox.utilities.gcs_utilities.html.https://cloud.google.com/python/docs/reference/documentai-toolbox/latest/google.cloud.documentai_toolbox.utilities.gcs_utilities.html(\n gcs_bucket_name=gcs_bucket_name, gcs_prefix=gcs_prefix, batch_size=batch_size\n )\n\n print(f\"{len(batches)} batch(es) created.\")\n for batch in batches:\n print(f\"{len(batch.gcs_documents.documents)} files in batch.\")\n print(batch.gcs_documents.documents)\n\n # Use as input for batch_process_documents()\n # Refer to https://cloud.google.com/document-ai/docs/send-request\n # for how to send a batch processing request\n request = documentai.https://cloud.google.com/python/docs/reference/documentai/latest/google.cloud.documentai_v1.types.BatchProcessRequest.html(\n name=\"processor_name\", input_documents=batch\n )\n print(request)\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=documentai)."]]