"use strict";

Object.defineProperty(exports, "__esModule", {
  value: true
});
exports.createIndexPipelineDefinitions = void 0;
var _ml_inference_pipeline_utils = require("../../utils/ml_inference_pipeline_utils");
/*
 * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
 * or more contributor license agreements. Licensed under the Elastic License
 * 2.0; you may not use this file except in compliance with the Elastic License
 * 2.0.
 */

/**
 * Used to create index-specific Ingest Pipelines to be used in conjunction with Enterprise Search
 * ingestion mechanisms. Three pipelines are created:
 * 1. `<indexName>@ml-inference` - empty by default. Any ML Inference processors that are enabled
 *   for this index are intended to be encapsulated in this pipeline.
 * 2. `<indexName>@custom` - empty by default. The customer is encouraged to edit this pipeline
 *   manually in order to meet their business needs.
 * 3. `<indexName>` - includes processors for binary content extraction, whitespace reduction, and nests
 *   the above pipelines in itself via pipeline processors.
 * @param indexName the index for which the pipelines should be created.
 * @param esClient the Elasticsearch Client with which to create the pipelines.
 */
const createIndexPipelineDefinitions = async (indexName, esClient) => {
  // TODO: add back descriptions (see: https://github.com/elastic/elasticsearch-specification/issues/1827)
  let result = {};
  try {
    const mlPipeline = {
      description: `Enterprise Search Machine Learning Inference pipeline for the '${indexName}' index`,
      id: (0, _ml_inference_pipeline_utils.getInferencePipelineNameFromIndexName)(indexName),
      processors: [],
      version: 1
    };
    await esClient.ingest.putPipeline(mlPipeline);
    result = {
      ...result,
      [mlPipeline.id]: mlPipeline
    };
    const customPipeline = {
      description: `Enterprise Search customizable ingest pipeline for the '${indexName}' index`,
      id: `${indexName}@custom`,
      processors: [],
      version: 1
    };
    await esClient.ingest.putPipeline(customPipeline);
    result = {
      ...result,
      [customPipeline.id]: customPipeline
    };
    const ingestPipeline = {
      _meta: {
        managed: true,
        managed_by: 'Enterprise Search'
      },
      description: `Enterprise Search ingest pipeline for the '${indexName}' index`,
      id: `${indexName}`,
      processors: [{
        attachment: {
          field: '_attachment',
          if: 'ctx?._extract_binary_content == true',
          ignore_missing: true,
          indexed_chars_field: '_attachment_indexed_chars',
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: [["Processor 'attachment' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]]
            }
          }],
          target_field: '_extracted_attachment'
        }
      }, {
        set: {
          field: 'body',
          if: 'ctx?._extract_binary_content == true',
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: [["Processor 'set' with tag 'set_body' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]]
            }
          }],
          tag: 'set_body',
          value: '{{{_extracted_attachment.content}}}'
        }
      }, {
        pipeline: {
          if: 'ctx?._run_ml_inference == true',
          name: (0, _ml_inference_pipeline_utils.getInferencePipelineNameFromIndexName)(indexName),
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: ["Processor 'pipeline' with tag 'index_ml_inference_pipeline' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]
            }
          }],
          tag: 'index_ml_inference_pipeline'
        }
      }, {
        pipeline: {
          name: `${indexName}@custom`,
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: ["Processor 'pipeline' with tag 'index_custom_pipeline' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]
            }
          }],
          tag: 'index_custom_pipeline'
        }
      }, {
        gsub: {
          field: 'body',
          if: 'ctx?._extract_binary_content == true',
          ignore_missing: true,
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: ["Processor 'gsub' with tag 'remove_replacement_chars' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]
            }
          }],
          pattern: '�',
          replacement: '',
          tag: 'remove_replacement_chars'
        }
      }, {
        gsub: {
          field: 'body',
          if: 'ctx?._reduce_whitespace == true',
          ignore_missing: true,
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: ["Processor 'gsub' with tag 'remove_extra_whitespace' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]
            }
          }],
          pattern: '\\s+',
          replacement: ' ',
          tag: 'remove_extra_whitespace'
        }
      }, {
        trim: {
          field: 'body',
          if: 'ctx?._reduce_whitespace == true',
          ignore_missing: true,
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: ["Processor 'trim' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]
            }
          }]
        }
      }, {
        remove: {
          field: ['_attachment', '_attachment_indexed_chars', '_extracted_attachment', '_extract_binary_content', '_reduce_whitespace', '_run_ml_inference'],
          ignore_missing: true,
          on_failure: [{
            append: {
              field: '_ingestion_errors',
              value: ["Processor 'remove' with tag 'remove_meta_fields' in pipeline '{{ _ingest.on_failure_pipeline }}' failed with message '{{ _ingest.on_failure_message }}'"]
            }
          }],
          tag: 'remove_meta_fields'
        }
      }],
      version: 1
    };
    await esClient.ingest.putPipeline(ingestPipeline);
    result = {
      ...result,
      [ingestPipeline.id]: ingestPipeline
    };
    return result;
  } catch (error) {
    // clean up pipelines if one failed to create
    for (const id of Object.keys(result)) {
      await esClient.ingest.deletePipeline({
        id
      });
    }
    throw error;
  }
};
exports.createIndexPipelineDefinitions = createIndexPipelineDefinitions;