{% extends "base.html" %} {% block content %} {# ── Header ── #}
data/raw/ inside the project folder.pipeline.yaml and set paths to your file and target_col to the column you want to predict.aimodelground run — then refresh this page.aimodelground run in a terminal to resume execution.1. Add your data to data/raw/ and edit pipeline.yaml.
2. Run aimodelground run in a terminal to start the pipeline.
3. Come back here — nodes will update live as they complete.
{% elif awaiting_gates %}1. Scroll up to the highlighted gate node(s).
2. Review the gate message and any relevant output.
3. Click Approve if you're happy, or Skip to bypass.
4. Run aimodelground run in a terminal to resume execution.
Pipeline complete!
1. Go to the Results tab to review model performance.
2. Go to the Deploy tab to get your deployment guide.
{% else %}Pipeline is running. This page updates live.
If a node shows failed, click Retry after fixing the issue.
Check the Data tab to inspect your uploaded files and profile.
{% endif %}