Merge remote-tracking branch 'migration/main' into nodejs-document-ai…

…-migration

document-ai/.eslintrc.yml

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+---
+rules:
+  no-console: off
+  node/no-unsupported-features/node-builtins: off

document-ai/batch-process-document.js

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+/**
+ * Copyright 2020 Google LLC
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+'use strict';
+
+const uuid = require('uuid');
+
+async function main(
+  projectId = 'YOUR_PROJECT_ID',
+  location = 'YOUR_PROJECT_LOCATION',
+  processorId = 'YOUR_PROCESSOR_ID', // Create this in the Cloud Console
+  gcsInputUri = 'gs://cloud-samples-data/documentai/invoice.pdf',
+  gcsOutputUri = 'output-bucket',
+  gcsOutputUriPrefix = uuid.v4()
+) {
+  // [START documentai_batch_process_document]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'YOUR_PROJECT_ID';
+  // const location = 'YOUR_PROJECT_LOCATION'; // Format is 'us' or 'eu'
+  // const processorId = 'YOUR_PROCESSOR_ID';
+  // const gcsInputUri = 'YOUR_SOURCE_PDF';
+  // const gcsOutputUri = 'YOUR_STORAGE_BUCKET';
+  // const gcsOutputUriPrefix = 'YOUR_STORAGE_PREFIX';
+
+  // Imports the Google Cloud client library
+  const {DocumentProcessorServiceClient} =
+    require('@google-cloud/documentai').v1;
+  const {Storage} = require('@google-cloud/storage');
+
+  // Instantiates Document AI, Storage clients
+  const client = new DocumentProcessorServiceClient();
+  const storage = new Storage();
+
+  const {default: PQueue} = require('p-queue');
+
+  async function batchProcessDocument() {
+    const name = `projects/${projectId}/locations/${location}/processors/${processorId}`;
+
+    // Configure the batch process request.
+    const request = {
+      name,
+      inputDocuments: {
+        gcsDocuments: {
+          documents: [
+            {
+              gcsUri: gcsInputUri,
+              mimeType: 'application/pdf',
+            },
+          ],
+        },
+      },
+      documentOutputConfig: {
+        gcsOutputConfig: {
+          gcsUri: `${gcsOutputUri}/${gcsOutputUriPrefix}/`,
+        },
+      },
+    };
+
+    // Batch process document using a long-running operation.
+    // You can wait for now, or get results later.
+    // Note: first request to the service takes longer than subsequent
+    // requests.
+    const [operation] = await client.batchProcessDocuments(request);
+
+    // Wait for operation to complete.
+    await operation.promise();
+    console.log('Document processing complete.');
+
+    // Query Storage bucket for the results file(s).
+    const query = {
+      prefix: gcsOutputUriPrefix,
+    };
+
+    console.log('Fetching results ...');
+
+    // List all of the files in the Storage bucket
+    const [files] = await storage.bucket(gcsOutputUri).getFiles(query);
+
+    // Add all asynchronous downloads to queue for execution.
+    const queue = new PQueue({concurrency: 15});
+    const tasks = files.map((fileInfo, index) => async () => {
+      // Get the file as a buffer
+      const [file] = await fileInfo.download();
+
+      console.log(`Fetched file #${index + 1}:`);
+
+      // The results stored in the output Storage location
+      // are formatted as a document object.
+      const document = JSON.parse(file.toString());
+      const {text} = document;
+
+      // Extract shards from the text field
+      const getText = textAnchor => {
+        if (!textAnchor.textSegments || textAnchor.textSegments.length === 0) {
+          return '';
+        }
+
+        // First shard in document doesn't have startIndex property
+        const startIndex = textAnchor.textSegments[0].startIndex || 0;
+        const endIndex = textAnchor.textSegments[0].endIndex;
+
+        return text.substring(startIndex, endIndex);
+      };
+
+      // Read the text recognition output from the processor
+      console.log('The document contains the following paragraphs:');
+
+      const [page1] = document.pages;
+      const {paragraphs} = page1;
+      for (const paragraph of paragraphs) {
+        const paragraphText = getText(paragraph.layout.textAnchor);
+        console.log(`Paragraph text:\n${paragraphText}`);
+      }
+
+      // Form parsing provides additional output about
+      // form-formatted PDFs. You  must create a form
+      // processor in the Cloud Console to see full field details.
+      console.log('\nThe following form key/value pairs were detected:');
+
+      const {formFields} = page1;
+      for (const field of formFields) {
+        const fieldName = getText(field.fieldName.textAnchor);
+        const fieldValue = getText(field.fieldValue.textAnchor);
+
+        console.log('Extracted key value pair:');
+        console.log(`\t(${fieldName}, ${fieldValue})`);
+      }
+    });
+    await queue.addAll(tasks);
+  }
+  // [END documentai_batch_process_document]
+
+  batchProcessDocument();
+}
+main(...process.argv.slice(2));

document-ai/package.json

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+{
+  "name": "nodejs-document-ai-samples",
+  "private": true,
+  "license": "Apache-2.0",
+  "author": "Google LLC",
+  "engines": {
+    "node": ">=12.0.0"
+  },
+  "files": [
+    "*.js"
+  ],
+  "scripts": {
+    "test": "mocha test/*.js --timeout 600000"
+  },
+  "dependencies": {
+    "@google-cloud/documentai": "^6.1.0",
+    "@google-cloud/storage": "^6.0.0",
+    "p-queue": "^6.6.2",
+    "uuid": "^9.0.0"
+  },
+  "devDependencies": {
+    "chai": "^4.2.0",
+    "mocha": "^8.0.0"
+  }
+}

document-ai/process-document-form.js

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+/**
+ * Copyright 2021, Google, Inc.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+'use strict';
+
+async function main(projectId, location, processorId, filePath) {
+  // [START documentai_process_form_document]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.
+   */
+  // const projectId = 'YOUR_PROJECT_ID';
+  // const location = 'YOUR_PROJECT_LOCATION'; // Format is 'us' or 'eu'
+  // const processorId = 'YOUR_PROCESSOR_ID'; // Create processor in Cloud Console
+  // const filePath = '/path/to/local/pdf';
+
+  const {DocumentProcessorServiceClient} =
+    require('@google-cloud/documentai').v1beta3;
+
+  // Instantiates a client
+  const client = new DocumentProcessorServiceClient();
+
+  async function processDocument() {
+    // The full resource name of the processor, e.g.:
+    // projects/project-id/locations/location/processor/processor-id
+    // You must create new processors in the Cloud Console first
+    const name = `projects/${projectId}/locations/${location}/processors/${processorId}`;
+
+    // Read the file into memory.
+    const fs = require('fs').promises;
+    const imageFile = await fs.readFile(filePath);
+
+    // Convert the image data to a Buffer and base64 encode it.
+    const encodedImage = Buffer.from(imageFile).toString('base64');
+
+    const request = {
+      name,
+      rawDocument: {
+        content: encodedImage,
+        mimeType: 'application/pdf',
+      },
+    };
+
+    // Recognizes text entities in the PDF document
+    const [result] = await client.processDocument(request);
+
+    console.log('Document processing complete.');
+
+    // Read the table and form fields output from the processor
+    // The form processor also contains OCR data. For more information
+    // on how to parse OCR data please see the OCR sample.
+    // For a full list of Document object attributes,
+    // please reference this page: https://googleapis.dev/nodejs/documentai/latest/index.html
+    const {document} = result;
+    const {text} = document;
+    console.log(`Full document text: ${JSON.stringify(text)}`);
+    console.log(`There are ${document.pages.length} page(s) in this document.`);
+
+    for (const page of document.pages) {
+      console.log(`\n\n**** Page ${page.pageNumber} ****`);
+
+      console.log(`Found ${page.tables.length} table(s):`);
+      for (const table of page.tables) {
+        const numCollumns = table.headerRows[0].cells.length;
+        const numRows = table.bodyRows.length;
+        console.log(`Table with ${numCollumns} columns and ${numRows} rows:`);
+        printTableInfo(table, text);
+      }
+      console.log(`Found ${page.formFields.length} form field(s):`);
+      for (const field of page.formFields) {
+        const fieldName = getText(field.fieldName.textAnchor, text);
+        const fieldValue = getText(field.fieldValue.textAnchor, text);
+        console.log(
+          `\t* ${JSON.stringify(fieldName)}: ${JSON.stringify(fieldValue)}`
+        );
+      }
+    }
+  }
+
+  const printTableInfo = (table, text) => {
+    // Print header row
+    let headerRowText = '';
+    for (const headerCell of table.headerRows[0].cells) {
+      const headerCellText = getText(headerCell.layout.textAnchor, text);
+      headerRowText += `${JSON.stringify(headerCellText.trim())} | `;
+    }
+    console.log(
+      `Collumns: ${headerRowText.substring(0, headerRowText.length - 3)}`
+    );
+    // Print first body row
+    let bodyRowText = '';
+    for (const bodyCell of table.bodyRows[0].cells) {
+      const bodyCellText = getText(bodyCell.layout.textAnchor, text);
+      bodyRowText += `${JSON.stringify(bodyCellText.trim())} | `;
+    }
+    console.log(
+      `First row data: ${bodyRowText.substring(0, bodyRowText.length - 3)}`
+    );
+  };
+
+  // Extract shards from the text field
+  const getText = (textAnchor, text) => {
+    if (!textAnchor.textSegments || textAnchor.textSegments.length === 0) {
+      return '';
+    }
+
+    // First shard in document doesn't have startIndex property
+    const startIndex = textAnchor.textSegments[0].startIndex || 0;
+    const endIndex = textAnchor.textSegments[0].endIndex;
+
+    return text.substring(startIndex, endIndex);
+  };
+
+  // [END documentai_process_form_document]
+  await processDocument();
+}
+
+main(...process.argv.slice(2)).catch(err => {
+  console.error(err);
+  process.exitCode = 1;
+});