Omnipresent

Mind sharing some metrics (time it took you ...tokens etc) and the approach you took? Did you break it up by module? Share some prompts?

Which LLM can generate that timeline event graphic from text?

Why did they decide to build a custom front end vs leverage Grafana that’s already as the front layer?

are you able to share the link to your prompts / conversation?

it'd be cool to see the prompts used and the edits required to get to the end product here.

Thank you. Look forward to it! How is the data model visuzalization built? Does Duckdb provide that out of the box?

Is this on GitHub to take a look at the code?

What are some good datasets to combine with weather data based on a geolocation?

Are there such immersive math courses geared more towards middle / high schoolers?

Is Superset extensible enough to click on the charts -- for example, click on part of the pie-chart and have it show the list that makes up the data for that part of the pie chart?

This is pretty neat. Wonder if they're using some data catalog under the covers for the search screen or is it all custom built.

What library is used to make the frontend globe rendering? Its pretty fast and not laggy on my chrome browser.

This is great. I am very curious about the architectural decisions you've taken here. Is there a blog post / article about them? 80 yrs of historical data -- are you storing that somewhere in PG and the APIs are just fetching it? If so, what indices have you set up to make APIs fetch faster etc. I just fetched 1960 to 2022 in about 12 secs.

This is great but doesn't work for applications that don't have the luxury of the internet. What are some decent map alternatives for air-gapped (no internet access) applications.