KDB.AI

Batch process all your records to store structured outputs in KDB.AI.

You will need:

The KDB.AI prerequisites:

• A KDB.AI Cloud or server instance. Sign Up for KDB.AI Cloud: Starter Edition. Set up KDB.AI Server.
• The instance’s endpoint URL. Get the KDB.AI Cloud endpoint URL. Get the KDB.AI Server endpoint URL.
• An API key. Create the API key.
• The name of the target table to access. Create the table.

The KDB.AI connector dependencies:

pip install "unstructured-ingest[kdbai]"

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

The following environment variables:

• KDBAI_ENDPOINT - The KDB.AI instance’s endpoint URL, represented by --endpoint (CLI) or endpoint (Python).
• KDBAI_API_KEY - The KDB.AI API key, represented by --api-key (CLI) or api_key (Python).
• KDBAI_TABLE - The name of the target table, represented by --table-name (CLI) or table_name (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 source connector can be any of the ones supported. This example uses the local source connector: