Hi,
Thanks @dataprofessor for the shout out. @DcPublished the media explorer app can be configured to run its backend as a monolith embedded in the Streamlit app, or in client-server mode as a standalone Streamlit frontend and FastAPI backend server.
The media explorer app only serves as an example of a flexible client-server design that you can follow. If you want to run it locally, then your media collections can point to local folders, but in the cloud you need to use URLs. You could write a small program that uploaded images to an S3 bucket and built the links list used in the media-service.toml file. Alternatively, you can change the appropriate media list generators in media_service.py. I have another version of this app which uses a sqlite database, for example.
Deploying on Heroku is easy. There are many posts in this forum showing what to do. Since you want to use PostgreSQL I’d suggest you start with a pure Streamlit application and squeeze as much perf from it using data caching and the new partial run decorators. You’ll be able to upload data to Heroku PostgreSQL using the Herkou desktop client, or the tools available in the build pack (I haven’t used it, so just guessing). Why not use Snowflake? There is a data connector that makes it really easy.
Have a look at @C_Quang’s app too: Public-facing, enterprise-grade deployment of Streamlit