Couchbase

Connect Couchbase Database 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 Couchbase database prerequisites.

• For the Unstructured Platform, only Couchbase Capella clusters are supported.
• For Unstructured Ingest, Couchbase Capella clusters and local Couchbase server deployments are supported.

For Couchbase Capella, you will need:

• A Couchbase Capella account. Create an account.
• A Couchbase Capella cluster. Create a cluster.
• A bucket, scope, and collection.
• A cluster connection string. Learn how.
• Incoming IP address allowance. Learn how.
• A username and password. Learn how.

For a local Couchbase server, you will need:

• Installation of a local Couchbase server. Learn how.
• Connection details to the local Couchbase server. Learn how.

To learn more about how to set up a Couchbase cluster and play with data, refer to this tutorial.

The Couchbase DB connector dependencies:

pip install "unstructured-ingest[couchbase]"

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

These environment variables are required for the Couchbase Connector:

• CB_CONN_STR - The Connection String for the Couchbase server, represented by --connection-string (CLI) or connection_string (Python).
• CB_USERNAME - The username for the Couchbase server, represented by --username (CLI) or username (Python).
• CB_PASSWORD - The password for the Couchbase server, represented by --password (CLI) or password (Python).
• CB_BUCKET - The name of the bucket in the Couchbase server, represented by --bucket (CLI) or bucket (Python).
• CB_SCOPE - The name of the scope in the bucket, represented by --scope (CLI) or scope (Python).
• CB_COLLECTION - The name of the collection in the scope, represented by --collection (CLI) or collection (Python).

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

This example sends data to Unstructured API services for processing by default. To process files locally instead, see the instructions at the end of this page.

For the Unstructured Ingest CLI and the Unstructured Ingest Python library, you can use the --partition-by-api option (CLI) or partition_by_api (Python) parameter to specify where files are processed:

• To do local file processing, omit --partition-by-api (CLI) or partition_by_api (Python), or explicitly specify partition_by_api=False (Python).

  Local file processing does not use an Unstructured API key or API URL, so you can also omit the following, if they appear:

  • --api-key $UNSTRUCTURED_API_KEY (CLI) or api_key=os.getenv("UNSTRUCTURED_API_KEY") (Python)
  • --partition-endpoint $UNSTRUCTURED_API_URL (CLI) or partition_endpoint=os.getenv("UNSTRUCTURED_API_URL") (Python)
  • The environment variables UNSTRUCTURED_API_KEY and UNSTRUCTURED_API_URL

• To send files to Unstructured API services for processing, specify --partition-by-api (CLI) or partition_by_api=True (Python).

  Unstructured API services also requires an Unstructured API key and API URL, by adding the following:

  • --api-key $UNSTRUCTURED_API_KEY (CLI) or api_key=os.getenv("UNSTRUCTURED_API_KEY") (Python)
  • --partition-endpoint $UNSTRUCTURED_API_URL (CLI) or partition_endpoint=os.getenv("UNSTRUCTURED_API_URL") (Python)
  • The environment variables UNSTRUCTURED_API_KEY and UNSTRUCTURED_API_URL, representing your API key and API URL, respectively.

  Get an API key and API URL.