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We actually used Streamlit in the past. Our gripe with it was how the backend event loop was managed. Basically, Streamlit re-runs your code at every user inter
by Alyx1337 3y ago
We actually used Streamlit in the past. Our gripe with it was how the backend event loop was managed. Basically, Streamlit re-runs your code at every user interaction to check what's changed (unless you cache specific variables which is hard to do well). When your app has significant data or a significant model to work with or multiple pages or users, this approach fails, and the app starts freezing constantly. We wanted a product that is the compromise between the easy learning curve of Streamlit while retaining production-ready capabilities: we use callbacks for user interactions to avoid unnecessary computations, front and back-end are running on separate threads. We also run on Jupyter notebooks if that helps.
- d4rkp4ttern 3y agoThe script re-run ( and the bandaid of caching via decorators) is exactly what I don’t like about streamlit. I’d love to see an example of how you use Taipy to build an LLM chat app, analogous to this SL example: https://docs.streamlit.io/knowledge-base/tutorials/build-conversational-apps https://docs.streamlit.io/knowledge-base/tutorials/build-con... Then I’ll give it a shot
- d4rkp4ttern 3y agoAnother interest one in this space — Reflex (formerly known as PyneCone). They have a ready to use LLM chat App, which makes it more likely I will check it out. https://github.com/reflex-dev/reflex https://github.com/reflex-dev/reflex