Elasticsearch

If you’re new to Unstructured, read this note first.

Before you can create a destination connector, you must first sign up for Unstructured and get your Unstructured API key. After you sign up, the Unstructured user interface (UI) appears, which you use to get the key. To learn how, watch this 40-second how-to video.

After you create the destination connector, add it along with a source connector to a workflow. Then run the worklow as a job. To learn how, try out the hands-on Workflow Endpoint quickstart, go directly to the quickstart notebook, or watch the two 4-minute video tutorials for the Unstructured Python SDK.

You can also create destination connectors with the Unstructured user interface (UI). Learn how.

If you need help, reach out to the community on Slack, or contact us directly.

You are now ready to start creating a destination connector! Keep reading to learn how.

Send processed data from Unstructured to Elasticsearch.

The requirements are as follows.

• For the Unstructured UI or the Unstructured API, only Elastic Cloud instances are supported.

• For Unstructured Ingest, Elastic Cloud instances and self-manged Elasticsearch instances are supported.

• For Elastic Cloud, you will need an Elastic Cloud service instance.

• For self-managed Elasticsearch, you will need a self-managed Elasticsearch instance.

• You will need the name of the index on the instance. See Create index and Get index.

  The Elasticsearch index that you use must have a schema that is compatible with the schema of the documents that Unstructured produces for you. Unstructured cannot provide a schema that is guaranteed to work in all circumstances. This is because these schemas will vary based on your source files’ types; how you want Unstructured to partition, chunk, and generate embeddings; any custom post-processing code that you run; and other factors.

  You can adapt the following index schema example for your own needs:

  {
      "settings": {
          "index": {
              "knn": true,
              "knn.algo_param.ef_search": 100
          }
      },
      "mappings": {
          "properties": {
              "record_id": {
                  "type": "text"
              },
              "element_id": {
                  "type": "keyword"
              },
              "text": {
                  "type": "text"
              },
              "embeddings": {
                  "type": "dense_vector",
                  "dims": 384,
                  "index": true,
                  "similarity": "cosine"
              },
              "metadata": {
                  "type": "object",
                  "properties": {
                      "parent_id": {
                          "type": "text"
                      },
                      "page_number": {
                          "type": "integer"
                      },
                      "is_continuation": {
                          "type": "boolean"
                      },
                      "orig_elements": {
                          "type": "text"
                      },
                      "partitioner_type": {
                          "type": "text"
                      }
                  }
              }
          }
      }
  }
  

  See also:

  • An Introduction to Elasticsearch Mapping
  • Explicit mapping
  • Dynamic field mapping
  • Unstructured document elements and metadata

• For Elastic Cloud, you will need the Elastic Cloud service instance’s API key. If you are using Unstructured Ingest, you will also need the instance’s Cloud ID. To get these, see your Elasticsearch Service web console.

• For self-managed Elasticsearch, you will need:

  • The self-managed instance’s hostname and port number. See Networking.
  • If you’re using basic authentication to the self-managed instance, the user’s name and password.
  • If you’re using token-based authentication to the self-managed instance, the bearer token or API key for the instance. See Token-based authentication services and Create API key.
  • If you’re using certificate authentication to the self-managed instance, the path to the Certificate Authority (CA) file on the instance, and the certificate fingerprint. See SSL certificate API and Where can I see my Certificate Fingerprint?.

To create an Elasticsearch destination connector, see the following examples.

Python SDK

import os

from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateDestinationRequest
from unstructured_client.models.shared import (
    CreateDestinationConnector,
    DestinationConnectorType,
    ElasticsearchConnectorConfigInput
)

with UnstructuredClient(api_key_auth=os.getenv("UNSTRUCTURED_API_KEY")) as client:
    response = client.destinations.create_destination(
        request=CreateDestinationRequest(
            create_destination_connector=CreateDestinationConnector(
                name="<name>",
                type=DestinationConnectorType.ELASTICSEARCH,
                config=ElasticsearchConnectorConfigInput(
                    hosts=["<host-url>"],
                    es_api_key="<es-api-key>",
                    index_name="<index-name>"
                )
            )
        )
    )

    print(response.destination_connector_information)

Replace the preceding placeholders as follows:

• <name> (required) - A unique name for this connector.
• hosts is a required array, with <host-url> specifying the URL of the Elastic Cloud instance to access, for example: ["https://<random-number>.<region>.<cloud-provider>.cloud.es.io"].
• <es-api-key> (required) - The Elastic Cloud API key for the target cluster.
• <index-name> (required) - The name of the target index in the cluster.