▶️ EXECUTE
Introduction
Execute walks through the lifecycle required to ship and operate an AGILab
application. It generates ready-to-run snippets, streams logs back into the UI
and keeps app_settings.toml synchronised so that installs, distribution
checks and runs are reproducible.
Main Content Area
System settingsgroups the cluster configuration. Toggle support forpool,cythonandrapids, enable the Dask scheduler and provide IP definitions for workers. The calculated mode hint clarifies how the chosen combination will execute and the settings are written back toapp_settings.toml.Installrenders the install snippet that provisions the project’s virtual environments.INSTALLstreams stdout/stderr intoInstall logsso you know when the worker is ready. A successful install automatically enables theRunsection.Distributeis split into two parts:<module> args: edit the run arguments managed inapp_args.py. You can toggle between the generated form UI and the custom Streamlit snippet saved inapp_args_form.py. Saved values update[args]inapp_settings.toml.Distribute details: generates theAGI.get_distribsnippet and theCHECK DISTRIBUTEaction. When the command succeeds theDistribution treeexpander plots the resulting work plan (DAG or tree) andWorkplanlets you reassign partitions to different workers before saving the modified plan.
Runexposes theAGI.runsnippet together with aBenchmark all modestoggle if you want to iterate through every execution path.RUNstreams logs into theRun logsexpander and stores the output timings inbenchmark.json, which is summarised underBenchmark results.LOAD DATAfetches the latest dataframe path configured for the project and shows an in-place preview. The preview is available even after a rerun.Prepare Data for Experiment and Explorecreates (or updates) the CSV that powers the Experiment and Explore pages. Use the column selector withSelect allsupport to decide which fields are persisted to${AGILAB_EXPORT_ABS}/<module>/export.csv.