TUI Guide

The Terminal User Interface (TUI) provides a text-based interactive dashboard directly in your terminal. It is the easiest way to browse the model and benchmark catalogs, check readiness, and generate CLI commands without memorizing flags.

Launch the TUI

Before launching, ensure the WorldFoundry package is installed. The recommended setup uses the unified environment:

bash scripts/setup/unified_install.sh
source tmp/worldfoundry_unified_env.sh
conda activate "${WORLDFOUNDRY_UNIFIED_ENV_PREFIX}"

If you manage your own conda environment, install the package with the [tui] extra from the repo root:

pip install -e ".[tui]"

Once your environment is active, launch the TUI:

worldfoundry-eval tui

The TUI reads the same model-zoo and benchmark-zoo manifests as the CLI discovery commands. It does not bypass manifest readiness, runtime profiles, or runner validation.

Launch options

Example — generate a command for a specific model × benchmark pair and exit:

worldfoundry-eval tui --model-id openvla --benchmark-id libero --print-command

This is useful in scripts or CI pipelines where you need the canonical command without manual interaction.

Navigate the TUI

The TUI displays three main panels:

1. Model Catalog — Lists all model-zoo entries with their ids, aliases, maturity levels, and runtime status. Use arrow keys to browse; press Enter to select a model.

2. Benchmark Catalog — Lists all benchmark-zoo entries with their ids, task scopes, maturity levels, and dataset readiness. Use arrow keys to browse; press Enter to select a benchmark.

3. Command Output — The bottom panel dynamically generates the corresponding worldfoundry-eval run command based on your selections. You can copy this command to execute later on a GPU node.

Configuration

After selecting a model and a benchmark, the TUI presents inference parameters you can adjust:

• Steps / iterations — Number of denoising or sampling steps.
• Guidance scale / cfg — Classifier-free guidance strength.
• Sequence length — Maximum token or frame count.
• Seed — Deterministic generation seed (optional).

These fields map to the same flags accepted by worldfoundry-eval run. Changing a parameter in the TUI updates the generated command in real time.

Readiness indicators

The TUI surfaces readiness warnings alongside catalog entries:

• Missing checkpoint — The model requires a checkpoint that is not found at the declared path.
• Missing dataset — The benchmark requires a dataset that is not staged locally.
• Missing environment — The runtime profile declares conda packages or CUDA versions that are not satisfied.
• License gate — The model or dataset has a gated or non-commercial license that requires manual review.

When a readiness blocker is present, the generated command includes --mode official-validation by default. This ensures you can validate the wiring without committing GPU resources to a blocked run.

Fallback mode

If the Textual dependency is not installed, the TUI prints a static fallback summary instead of the interactive dashboard. The fallback lists model ids, benchmark ids, and a brief readiness note.

To restore the full interactive TUI, install the [tui] extra:

pip install -e ".[tui]"

TUI vs CLI discovery

Both the TUI and the CLI discovery commands read the same catalog manifests. Choose based on your workflow:

Next steps