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Troubleshooting

Solutions for common issues across the CLI, web UI, agents, compute, and paper pipeline.

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CLI Issues

The CLI is not in your PATH. Fix depends on your install method:
Tokens expire periodically. Re-authenticate:
For CI environments, create a long-lived token:
Commands run against the active lab. Switch labs:
The CLI communicates with www.hubify.com/api over HTTPS. Check your network:
If behind a proxy:

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Agent Issues

Check agent status:
If an agent shows as stuck, restart it:
Verify external API keys are configured:
If a provider’s key is expired or invalid, update it:
Ensure auto-scheduling is enabled:
Check if the orchestrator is overloaded:

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Compute Issues

The requested GPU may be out of stock. Check availability:
Try a different GPU type or region:
Reduce batch size or upgrade GPU:
  • H100 (80 GB) handles most workloads
  • H200 (141 GB) for the largest datasets
For PyTorch, enable gradient checkpointing to reduce memory:
Find and terminate idle pods:
Prevent future waste by setting an idle timeout:
When the monthly budget is hit, new experiments queue instead of launching:

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Paper Issues

Figures must be in the same directory as the .tex file. The compile command handles this, but verify:
If the PDF is under 1 MB, figures are not embedded.
Run compilation multiple times (the compile command does this automatically):
If references persist, check that all \cite{} keys exist in your .bib file.
Common issues:
  • Using \citep/\citet, use \cite{} with revtex4-2
  • Using \deluxetable, use \begin{table}\begin{ruledtabular}\begin{tabular}
  • Using aastex631 class, use revtex4-2
View the full compile log:

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Lab Site Issues

Force a sync and redeploy:
Verify DNS and SSL:
Ensure your CNAME record points to cname.hubify.app. SSL provisioning takes 1-5 minutes.

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Getting Help

If your issue is not listed here: