Then with the block features, we can enable app like functionality to the tables. In this case, we have a block(right hand side of the 👆 screenshot) to capture the input and run a simple javascript function behind the scene to manage the API calls to OpenAI api for predictions, then fetch movie/tv metadata from IMDB, at the end parse the metadata to create records in the table for viewing.
With the above workflow, we have a basic low code, no ML set up to built our end to end movie recommendation app with GPT3 and Airtable in less than one day. Thinking about how much efforts are needed in the conventional ways.
No-code/low-code movement is happening, Automated ML/AI is booming, managed cloud services like AWS and GCP made these even more accessible and easy to build applications and solutions. OpenAI API and GPT3 as a service give us a new horizon to rethink what is possible.
Hope this blog can inspire you on exploring, leveraging, prototyping, and integrating the powerful GPT3 API into your applications. Feel free to ping me if you have any questions or want to know more about this project.
For more GPT3, check out my previous blogs:
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