Syllabus for tonight:
Explore GPT-3 API example apps
Setup Bubble's API Connector and register API call
manually at first
then cheating using cURL import shortcut
free tool to visualize JSON objects: JSONvisual
Build the mini app in Bubble
parse response object to populate repeating group
parameterize the API call to make it dynamic from inputs
commit the results to a db table
chaining API calls together... 🤯
Troubleshooting tools to emulate sends/receives so you can inspect payloads:
Show SheetAI Gsheets ext for invoking GPT-3 from within Google Sheets.
"Prompt Engineering" guide of guides massive Gsheet
When to use APIs vs. Zapier/Make connectors:
When Zapier or Make don't have a connector
When # of calls will be cost preclusive to use ^^
When fast response times are paramount
Downsides of calling APIs directly vs. using connectors:
no replay protection if endpoint is down
more coding and error-handling required
requires centralized application logic vs. "pushing logic to the edges" when interacting with multiple services.
Final thoughts
JSON as the "rail spike" for parallelizing app dev in teams
value of JSON for serializing complex data in personal app dev (choke points)
Amazon's mandate for externalizing all services (exposing their own internal service-oriented architecture for public consumption)
great tutorial that I'm building upon for this demo
https://us02web.zoom.us/j/89404986017?pwd=MjdmVGlJTUFiSHVVQlNMRlN5OFZOZz09
zoom link ^^
For SheetAI discount: