I’m developing a Glide app where sales reps answer questions about meetings via voice notes rather than data entries. GPT3.5 then transcribes these notes. The challenge is associating these notes with Deals and People in our Pipedrive CRM.
Due to the volume of data, syncing all deal titles/person names with their IDs isn’t feasible. I’m considering using the fetch JSON column for searching instead.
Two issues I need guidance with:
The implementation of this solution using an API Key.
Ensuring fast search operations, so surfacing deals/customers is as seamless as the CRM
There’s a “generic API” call in alpha now that allows you to add headers, but the headers are not safe as of now. It returns results pretty quick, though. I don’t know when it will reach beta, but I feel it’s promising, going hand in hand with the new query JSON column.
I’m also wondering which no-code tool would be a good bridge so that I could for instance use make.com to fetch the data from the Pipedrive API or Firestore and use the fetchJSON to display the queried results.
@Darren_Murphy seems to have implemented the solution you’re suggesting, correct?
I wonder how many rows it could handle without delay
enabled in previews! thanks!
I wonder the JSONata column is any quicker than the Transform JSON (which is essentially jq), which is already publicly released. I wonder what the the difference is in general.
You mean pull a different index for each row in the Query parameter? You could just build a template column that builds the query, along with the row’s index, and use the template column in the query parameter.
Yes, but the issue with that is-
I have multiple columns/fields which I would like to display.
I will need 2 columns for each field I would like to display, the ‘Template’ and ‘Query JSONata’ columns.