Who it is forA developer or evaluation engineer who needs to call robot tasks from a script or batch job.
The problemScripts need a non-interactive way to run a task and capture the outcome without opening a terminal interface.
The outcomeThe task runs against the Controller and the result is printed to stdout as JSON, with workspace files stored in ~/.Emerge/workspace.
What you need first
- Conda and Python 3.12 for the EmergePolicy environment
- GPUs assigned by index for the model services (OPENPI_GPU, VGGT_GPU, SAM3_GPU)
- Downloaded model checkpoints placed under checkpoints/ as listed in the README
- LIBERO-Plus assets.zip downloaded from Hugging Face and extracted into the submodule
- API configuration, which the first launch of Web or TUI walks you through
Steps
- Complete the environment setup with
conda activate EmergePolicyfrom the repository root. - Start the model services with
OPENPI_GPU=0 VGGT_GPU=1 SAM3_GPU=2 bash scripts/model_server/start_external_model_servers.sh --services openpi,vggt,sam3. (inferred, check the README) - Start the Controller in one terminal with
python -m robot.controller --driver libero_mujoco --driver-config dev/libero_mujoco_driver_sample.json. (inferred, check the README) - In a second terminal, run
python -m Emerge.cli.headless "Put the red block in the basket". - Read the JSON result from stdout and check the files in ~/.Emerge/workspace.
Prompt for your agent
In the EMERGE-Policy repo, with the Controller already running, execute `python -m Emerge.cli.headless "<task>"` and capture stdout. Expected output is a JSON result for the task. Verify that the output parses as valid JSON before reporting it.
Caveat. The README says to configure the API through Web or TUI before using Headless, so a script cannot run cold on a fresh machine.
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