MotherDuck
Batch process all your records to store structured outputs in a MotherDuck account.
The requirements are as follows.
-
A MotherDuck access token for the account.
-
A database in the account.
You can run commands to manage MotherDuck databases, schemas, tables, and more in the MotherDuck UI or for example by connecting to MotherDuck with the DuckDB CLI.
-
A schema in the target database.
-
You can list available schemas and their parent catalogs by running the following command in the MotherDuck UI or the DuckDB CLI:
The MotherDuck connector uses the default schema name of
main
if not otherwise specified. -
A table in the target schema.
-
You can list available tables in a schema by running the following commands in the MotherDuck UI or the DuckDB CLI, replacing the target catalog and schema names:
The MotherDuck connector uses the default table name of
elements
if not otherwise specified.For maximum compatibility, Unstructured recommends the following table schema:
You can list the schema of a table by running the following commands in the MotherDuck UI or the DuckDB CLI, replacing the target catalog, schema, and table names:
The MotherDuck connector dependencies:
You might also need to install additional dependencies, depending on your needs. Learn more.
The following environment variables:
MOTHERDUCK_MD_TOKEN
- The access token for the target MotherDuck account, represented by--md-token
(CLI) ormd_token
(Python).MOTHERDUCK_DATABASE
- The name of the target database in the account, represented by--database
(CLI) ordatabase
(Python).MOTHERDUCK_DB_SCHEMA
- The name of the target schema in the database, represented by--db-schema
(CLI) ordb_schema
(Python).MOTHERDUCK_TABLE
- The name of the target table in the schema, represented by--table
(CLI) ortable
(Python).
Now call the Unstructured CLI or Python. The source connector can be any of the ones supported. This example uses the local source connector.
This example sends files 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) orpartition_by_api
(Python), or explicitly specifypartition_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) orapi_key=os.getenv("UNSTRUCTURED_API_KEY")
(Python)--partition-endpoint $UNSTRUCTURED_API_URL
(CLI) orpartition_endpoint=os.getenv("UNSTRUCTURED_API_URL")
(Python)- The environment variables
UNSTRUCTURED_API_KEY
andUNSTRUCTURED_API_URL
-
To send files to Unstructured API services for processing, specify
--partition-by-api
(CLI) orpartition_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) orapi_key=os.getenv("UNSTRUCTURED_API_KEY")
(Python)--partition-endpoint $UNSTRUCTURED_API_URL
(CLI) orpartition_endpoint=os.getenv("UNSTRUCTURED_API_URL")
(Python)- The environment variables
UNSTRUCTURED_API_KEY
andUNSTRUCTURED_API_URL
, representing your API key and API URL, respectively.