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Hardware-Specific Adapter Setup
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#. We will be copying some code from your specific hardware's webpage. Find it in the list in :doc:`supported_adapters` and leave it open in a browser tab.
#. Open your adapter's git repository in Visual Studio Code. Make sure you open it in the container.
#. Open the file :file:`Pipfile`.
#. In the packages section, add the lines listed on your specific hardware's page in the :file:`Pipfile` section.
#. Run ``pipenv lock`` in the terminal window. Wait until the command has completed - this will take a few minutes and it will update the :file:`Pipfile.lock` for you.
#. Rebuild your container. In Visual Studio Code, press ``Ctrl-Shift-P`` to open the command palette. Type ``Rebuild Container Without Cache`` and select that command to run it.
#. In your adapter repository, within the :file:`configs` folder, you will find one or more subfolders--each corresponding to a different :ref:`configuration context<Configuration Contexts>`. Create a new folder in the :file:`configs` folder named :file:`tutorial`. 
#. Inside that folder, make sure to place the :file:`secrets.yaml` you created in the guide for :doc:`local_dev_container`.
#. Also inside that folder, copy the :file:`config.yaml` exactly as listed on your specific hardware's page and follow any instructions given for that specific hardware's :file:`config.yaml` customization.
#. For the :file:`config.yaml`, you also need to customize:
    #. The entire ``artificial`` section needs to be set to the correct instance. You can get the entire deployment config from your Artificial's settings page by following these steps: 
        #. Go to your instance in Artificial. 
        #. Click on the Settings icon. 
        #. Select the correct lab under the Labs section. 
        #. Scroll down to the Deployment Config section and copy the entire ``artificial`` section there into your yaml file in place of the existing ``artificial`` section.
    #. In the ``asset_sync`` section, update the rid guid to the one matching your device. The rid can be obtained by: 
        #. logging into your instance and selecting the correct Lab.
        #. Click on the equipment to select it and click on the ``Edit asset details`` icon on the far right. 
        #. In the right pane, under ``Debug`` copy the instance ID (this is the rid) and copy it into the adapter's :file:`config.yaml` file.
    #. For more advanced use cases, consult :doc:`adapter_configuration`.
#. Next, replace the entire contents of the :file:`adapter/main/plugin.py` file with those listed on your specific hardware's page.
#. Set this as the active context by replacing the :file:`configs/context.yaml` file with the one below.
    .. code-block:: yaml
      :caption: :file:`configs/context.yaml`

      activeContext: tutorial
#. This should successfully set up the driver-specific portions of the adapter. You should continue following the guide that sent you here.