OpenSearch

Connect OpenSearch 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.

The requirements are as follows.

• An OpenSearch instance, such as an AWS OpenSearch instance…

  …or a local instance.

  In all cases, the OpenSearch version must be compatible with the client version of the opensearch-py package on PyPI.

• The instance’s hostname and port number. To learn how, see:

  • Creating and managing Amazon OpenSearch Service domains for AWS OpenSearch instances.
  • Communicate with OpenSearch for local OpenSearch instances.

• The name of the search index on the instance. Create an index.

  The OpenSearch 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": "knn_vector",
                  "dimension": 384
              },
              "metadata": {
                  "type": "object",
                  "properties": {
                      "parent_id": {
                          "type": "text"
                      },
                      "page_number": {
                          "type": "integer"
                      },
                      "is_continuation": {
                         "type": "boolean"
                      },
                      "orig_elements": {
                         "type": "text"
                      }
                  }
              }
          }
      }
  }
  

  See also:

  • Mappings and field types
  • Explicit mapping
  • Dynamic mapping
  • Unstructured document elements and metadata

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

• If you’re using certificates for authentication instead:

  • The path to the Certificate Authority (CA) bundle, if you use intermediate CAs with your root CA.
  • The path to the combined private key and certificate file, or
  • The paths to the separate private key and certificate file.

  To learn more, see:

  • For AWS OpenSearch instances, see Tutorial: Configure a domain with the internal user database and HTTP basic authentication and Creating a custom endpoint for Amazon OpenSearch Service.
  • For local OpenSearch instances, see Authentication backends, HTTP basic authentication, and Client certificate authentication.

The OpenSearch connector dependencies:

pip install "unstructured-ingest[opensearch]"

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

The following environment variables:

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

If you’re using basic authentication to the instance:

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

If you’re using certificates for authentication instead:

• OPENSEARCH_CA_CERTS - The path to the Certificate Authority (CA) bundle, if you use intermediate CAs with your root CA. This is represented by --ca-certs (CLI) or ca_certs (Python).
• OPENSEARCH_CLIENT_CERT - The path to the combined private key and certificate file, or the path to just the certificate file. This is represented by --client-cert (CLI) or client_cert (Python).
• OPENSEARCH_CLIENT_KEY - The path to the private key file, if OPENSEARCH_CLIENT_CERT refers to just the certificate file. This is represented by --client-key (CLI) or client_key (Python).

Additional related settings include:

• --use-ssl (CLI) or use_ssl=True (Python) to use SSL for the connection.
• --verify-certs (CLI) or verify_certs=True (Python) to verify SSL certificates.
• --ssl-show-warn (CLI) or ssl_show_warn=True (Python) to show a warning when verifying SSL certificates is disabled.

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: