Adding Anaconda Assistant to Workbench

Anaconda Assistant is the AI pair programmer developed by Anaconda to assist you with coding in your Jupyter Notebooks. You can install the Anaconda Assistant as an optional component of the Data Science & AI Workbench.

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Installing Anaconda Assistant

1. Open a browser and log in to Workbench as the anaconda-enterprise user.

2. Open any existing project and view its settings.

3. If necessary, change the Default Editor to JupyterLab.

4. Open a project session.

5. Open a terminal window in your project session.

6. Download the Anaconda Assistant tarball and its checksum by running the following commands:

   curl -O https://airgap-svc.s3.amazonaws.com/misc/jupyter-as-tgz-0.3.5_4.tgz
   curl -O https://airgap-svc.s3.amazonaws.com/misc/jupyter-as-tgz-0.3.5_4.tgz.sha256
   

7. Verify the checksum of the files you downloaded by running the following command:

   sha256sum -check jupyter-as-tgz-0.3.5_4.tgz.sha256
   

8. Unpack the tarball you just downloaded into the tools directory by running the following command:

   tar xvzf  jupyter-as-tgz-0.3.5_4.tgz -C /tools
   

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Enabling the Anaconda Assistant

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Obtaining an API Authentication token

To enable the Anaconda Assistant, you must have an Anaconda.com account. If you do not have an Anaconda.com account, create one now.

Anaconda Assistant utilizes a token that must be generated using the anaconda-auth package, which is available in Anaconda’s default channel. This token provides your Workbench instance with access to the Anaconda Assistant API.

1. Open a terminal application outside of Workbench on your machine.

2. Install anaconda-auth by running the following command:

   conda install --name base anaconda-auth
   

3. Authenticate to Anaconda by running the following command:

   anaconda login
   

4. If prompted, select anaconda.com and press Enter (Windows)/Return (Mac).

5. Use the browser window that appears to log in to Anaconda using your account credentials.

   You can close the window once you are logged in.

6. Return to your terminal application (outside of Workbench) and generate your authentication token by running the following command:

   anaconda auth api-key
   

   The command returns a random string of characters. That is your authentication token!

   Store your token in a secure location!

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Setting environment variables

1. Connect to your Workbench Kubernetes cluster.

2. View a list of your configmaps by running the following command:

   
   kubectl get cm
   
   

3. Edit the anaconda-enterprise-env-var-config.yml file.

   kubectl edit cm anaconda-enterprise-env-var-config
   
   

4. Include the following lines:

   # Replace <CLOUD_API_TOKEN> with the your cloud API token
   
   ANACONDA_AE5_CLOUD_TOKEN: <CLOUD_API_TOKEN>
   
   ANACONDA_ASSISTANT_ENVIRONMENT_TYPE: enterprise-notebooks-prod
   
   

5. Save your work and close the file.

6. Update Workbench with your changes and restart services by running the following command:

   kubectl get pods | grep 'ap-deploy\|ap-workspace\' | cut -d' ' -f1 | xargs kubectl delete pods
   

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Verifying installation

With the tarball extracted into the /tools volume and your Anaconda API key stored as a system variable, return to Workbench and create a new project with JupyterLab as its default editor. You will see the Anaconda Assistant on the right hand side of the screen when you open a notebook (.ipynb) file.

For more information about how to use the Assistant, see the Anaconda Assistant quickstart guide.