At Trubrics we are building tools to help you enhance your ML workflows with human feedback.
We’ve released a new component with Streamlit that allows you to collect qualitative and quantitative feedback from your users and save it along with all your model and dataset metadata:
Install it with:
pip install "trubrics[streamlit]"
and start collecting feedback in your app with:
from trubrics.integrations.streamlit import FeedbackCollector
collector = FeedbackCollector()
Source code: GitHub - trubrics/trubrics-sdk: Enhance your ML workflows with human feedback
Thanks & please let us know what you think !
The component is so good. But this works on an older version of Streamlit.
Thanks for pointing this out, we’ve fixed it in the new release! Have you given it a try? Please don’t hesitate if you have any feedback !
Sorry if I’m pointing out too many version compatibilities😅 but the component installs scikit-learn 1.0.2 but the current scikit version is 1.2.2.
True, I’ll sort this out in the next release.
For the moment don’t worry about the scikit-learn version required, as it only concerns another part of the package. Just run a
pip install --upgrade scikit-learn and all should work just fine
Used trubrics feedback component. I need to connect it to the database to store the feedback (cosmosDB) and need to do some UI changes. Here’s the Link: Termsbrief
st.form() to wrap your custom feedback in a form