MongoDB

Batch process all your records to store structured outputs in MongoDB.

You will need:

The MongoDB prerequisites for a MongoDB Atlas deployment:

• A MongoDB Atlas account. Create an account.

• A MongoDB Atlas cluster. Create a cluster.

• The cluster must be reachable from your application environment. Learn how.

• The cluster must be configured to use your IP address. Learn how.

• The cluster must have at least one database. Create a database.

• The database must have at least one user, and that user must have sufficient access to the database. Create a database user. Give the user database access.

• The database must have at least one collection. Create a collection.

• The URI for the cluster. This URI must include the protocol, username, password, and host. Learn how to get this value.

The MongoDB connector dependencies:

pip install "unstructured-ingest[mongodb]"

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

For a MongoDB Atlas deployment, the following environment variables:

• MONGODB_DATABASE - The name of the database, represented by --database (CLI) or database (Python).

• MONGODB_COLLECTION - The name of the collection in the database, represented by --collection (CLI) or collection (Python).

• MONGODB_URI - The URI for the cluster, represented by --uri (CLI) or uri (Python).

For a local MongoDB server, the following environment variables:

• MONGODB_HOST - The host for the local MongoDB server, represented by --host (CLI) or host (Python).

• MONGODB_PORT - The port for the local MongoDB server, represented by --port (CLI) or port (Python).

Now call the Unstructured Ingest CLI or Unstructured Ingest 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) 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.