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Request: remote iterative evaluation service / web UI for sandbox backends #2

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@sakura-gui

Hi NatureBench team,

Thank you for releasing NatureBench and its iterative evaluation protocol.

The current open-source runner gives each agent an EVAL_SERVICE_URL and lets it repeatedly call POST /evaluate, using the best score across attempts. The existing eval_service.py works well when the agent container and evaluator share a host filesystem: the request passes an output_dir path that the service can read.

We are integrating NatureBench with remote sandbox/orchestration backends (for example, a sandbox running on a different worker from the controller/evaluator). In that setup, the agent and evaluation service do not share the local /workspace/output path. Running only a final verifier would lose NatureBench's official solve-evaluate-improve loop and make results less comparable.

Would you consider either:

  1. open-sourcing any remote/hosted evaluation website or service used internally, if one exists; or
  2. adding a deployable remote-submission mode (and optionally a minimal web UI) to the existing evaluation service?

A remote mode could support:

  • authenticated, run-scoped tokens;
  • uploading outputs or referencing an object-storage/shared-storage URI instead of a host-local path;
  • asynchronous evaluation plus polling for long-running evaluators;
  • pausing the solve timer while evaluation is in flight;
  • the same multi-attempt best-score tracking and submissions.jsonl records as the official runner;
  • container/deployment documentation, while keeping ground truth accessible only to evaluation workers.

Some task outputs can be quite large, so object-storage or shared-storage references would likely be more practical than sending the archive directly in every /evaluate request.

Is there already an internal implementation or roadmap for this? If not, would the maintainers be open to a community PR adding a remote submission backend to eval_service.py?

Thanks!

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