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Connect Elasticsearch to your preprocessing pipeline, and use the Unstructured Ingest CLI or the Unstructured Ingest Python library to batch process all your documents and store structured outputs locally on your filesystem.

You will need:

The Elasticsearch prerequisites:

  • An Elasticsearch instance, such as an Elastic Cloud service instance…

    …or a self-managed Elasticsearch instance.

  • 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": {
                "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"
                        }
                    }
                }
            }
        }
    }
    

    See also:

  • If you’re connecting to an Elastic Cloud instance, the Cloud ID and API key. To get these, see your Elasticsearch Service web console.

  • If you’re connecting to a self-managed instance, the instance’s hostname and port number. See Networking.

  • If you’re using basic authentication to the instance, the user’s name and password.

  • If you’re using token-based authentication to the instance, the bearer token or API key for the instance. See Token-based authentication services and Create API key.

  • If you’re using certificate, 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?.

The Elasticsearch connector dependencies:

CLI, Python
pip install "unstructured-ingest[elasticsearch]"

You might also need to install additional dependencies, depending on your needs. Learn more.

The following environment variables:

  • ELASTICSEARCH_HOST - The hostname and port number, defined as <hostname>:<port-number> and represented by --hosts (CLI) or hosts (Python).
  • ELASTICSEARCH_INDEX_NAME - The name of the search index, represented by --index-name (CLI) or index_name (Python).

If you’re using Elastic Cloud to connect to ElasticSearch:

  • ELASTIC_CLOUD_ID - The instance’s Cloud ID, represented by --cloud-id (CLI) or cloud_id (Python).
  • ELASTIC_CLOUD_API_KEY - The corresponding Cloud API key value, represented by --api-key-id (CLI) or api_key_id (Python).

If you’re using basic authentication to the instance:

  • ELASTICSEARCH_USERNAME - The user’s name, represented by --username (CLI) or username (Python).
  • ELASTICSEARCH_PASSWORD - The user’s password, represented by --password (CLI) or password (Python).

If you’re using token-based authentication to the instance instead:

  • ELASTICSEARCH_BEARER_TOKEN - The bearer token’s value, represented by --bearer-auth (CLI) or bearer_auth (Python).
  • ELASTIC_CLOUD_API_KEY_ID - The API key’s value, represented by --api-key (CLI) or api_key (Python).

If you’re using certificates:

  • ELASTICSEARCH_CA_CERTS - The path to the Certificate Authority (CA) file, represented by --ca-certs (CLI) or ca_certs (Python).
  • ELASTICSEARCH_SSL_ASSERT_FINGERPRINT - The certificate’s fingerprint, represented by --ssl-assert-fingerprint or ssl_assert_fingerprint (Python).

These environment variables:

  • UNSTRUCTURED_API_KEY - Your Unstructured API key value.
  • UNSTRUCTURED_API_URL - Your Unstructured API URL.

Now call the Unstructured CLI or Python SDK. The destination connector can be any of the ones supported. This example uses the local destination connector: