Slack

Connect Slack 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.

• A Slack app. Create a Slack app by following Step 1: Creating an app.

• The app must have the channels:history OAuth scope. Give the app this scope by following Step 2: Requesting scopes.

• The app must be installed and authorized for the target Slack workspace. Install and authorize the app by following Step 3: Installing and authorizing the app.

• The app’s access token. Get this token by following Step 3: Installing and authorizing the app.

• Add the app to the target channels in the Slack workspace. To do this from the channel, open the channel’s details page, click the Integrations tab, click Add apps, and follow the on-screen directions to install the app.

• The channel ID for each target channel. To get this ID, open the channel’s details page, and look for the Channel ID field on the About tab.

• The starting and ending date and time range for the channels to be processed. Supported formats include:

  • YYYY-MM-DD
  • YYYY-MM-DDTHH:MM:SS
  • YYYY-MM-DDTHH:MM:SSZ
  • YYYY-MM-DD+HH:MM:SS
  • YYYY-MM-DD-HH:MM:SS

The Slack connector dependencies:

pip install "unstructured-ingest[slack]"

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

These environment variables:

• SLACK_BOT_USER_OAUTH_TOKEN - The OAuth token for the Slack app, represented by --token (CLI) or token (Python).

To specify the starting and ending date and time range for the channels to be processed:

• For the CLI, use one of the following supported formats:

  • YYYY-MM-DD
  • YYYY-MM-DDTHH:MM:SS
  • YYYY-MM-DDTHH:MM:SSZ
  • YYYY-MM-DD+HH:MM:SS
  • YYYY-MM-DD-HH:MM:SS

• For Python, use the datetime.datetime function.

Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. 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 data 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.