LukaFontanilla
commented
6 months ago Mark,
A new version of the codebase was deployed to address a few doc notes from this FR, namely:
- BQ dataset & connection id variable name changes in the deployment steps
- Explicit callout as to where to run the port forwarding command if a requirement
- Removal of the Cloud Function step in the BQ deployment (this is not needed)
- "Open in Colab" button to run the training notebook
Outstanding and what we are looking into:
- Removal of some unneeded dependencies and instructions on Node Version req
- New Column for "Suggested Prompts" to add to explore assistant examples table in BQ
To note on the last bullet point here ^, The examples in the current documentation are used for training the LLM. They are separate from the suggested prompts that show up in the UI of the Explore Assistant. For a while those have been hardcoded in the Frontend UI to serve as an example based on the ecomm use case. To change them to date, you would need to update the Frontend code and rebuild the frontend javascript (see the code sample below). For the BQ deployment however, we are working on an automated approach for that which is represented in the last bullet point.
const categorizedPrompts = [
{
category: 'Cohorting',
prompt: 'Count of Users by first purchase date',
color: 'blue',
},
{
category: 'Audience Building',
prompt:
'Users who have purchased more than 100 dollars worth of Calvin Klein products and have purchased in the last 30 days',
color: 'green',
},
{
category: 'Period Comparison',
prompt:
'Total revenue by category this year compared to last year in a line chart with year pivoted',
color: 'red',
},
]
markrittman
I followed the BigQuery Deployment instructions and managed to get through the LLM deployment steps, working around the following issues:
1) The instruction to use the notebook to create the stringified examples doesn't include any instructions on how to run the notebook - how do you run it?
2) The step that tells you to:
references a dataset name that we've not previously created (
explore_assistant_demo_logs) and so I created that dataset and then inserted into theexplore_assistant_examplestable the following values, and repeated this for a table of the same name in theexplore_assistantdataset that we had been working with up until this point.Then I followed the instructions under "2. Looker Extension Framework Setup".
1) For step 2, you suggest running these steps from Cloud Shell, but every time I try to do this I run out of space, it seems that the files that
npm installdownloads and tries to unpack eventually exceed the 5GB limit we have when using Cloud Shell.2) Doing this from my Mac, I think, works? But when you say "You may need to update your Node version or use a Node version manager to change your Node version." it's not clear what version of Node we should install? I went with the default for the Mac but I don't really know if the rest of the steps worked ok or not, this bit of the instruction isn't very clear - this was the output from my attempt to run this install:
3) For Step 4 where you say "Start the development server IMPORTANT If you are running the extension from a VM or another remote machine, you will need to Port Forward to the machine where you are accessing the Looker Instance from. Here's a boilerplate example for port forwarding the remote port 8080 to the local port 8080: ssh username@host -L 8080:localhost:8080." - I understand the concept of port forwarding but where exactly do you run this command? On my Mac? On a VM if I'd have run these steps there? Somehow on the Looker server? I just ignored these steps in the end.
4) Then for Step 5 you say "IMPORTANT please paste in the deployed Cloud Function URL into the external_api_urls list. This will allowlist it in Looker for fetch requests." - what cloud function? I see you mention creating one in another set of steps that are an alternative deployment approach to the BigQuery deployment, but are you now saying we have to deploy that cloud function anyway?
5) I then went to the Deployment section and managed to put together the manifest file, I think correctly but I'm guessing at this stage:
Running the Explore Assistant extension brings-up this screen, which looked promising but I noted, didn't reference any of the example queries I inserted into the
explore_assistant_examplestable earlier:I then try entering a natural language query e.g. "total invoiced revenue by company" and whilst the explore assistant extension app just hangs, if I then check the Job History tab in the BigQuery Studio web app I can see that the app has sent the query to BigQuery DBML, as shown in the truncated SQL text below:
However the Explore Assistant app never returns any results.
In summary:
1) It's never really clear to me whether the
npm installpart worked and whether I still needed to switch Node version (to what version? 17?)Do we need to deploy the cloud function or not? If so then the steps to do so need to be added to the BigQuery Deployment set of steps
The bit about port forwarding and running this on your local machine (or a VM?) really aren't that clear and do we really need them, if the goal is to get this all running independently on your Looker instance?
Whilst despite all of the above, the extension app seems to be working at the end and sending requests to my BigQuery instance, the app never renders any results, or has my example queries listed for selection and running (and has a load of boilerplate text that wouldn't apply to a customer deployment i.e. the ecommerce data)
Hope this helps and looking-forward to getting a version running at some point! Cheers