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Remote execution runs your EDSL job on Expected Parrot’s servers. Your questions, scenarios, agents, and models still define the study in Python; the hosted service carries out the interviews and returns Results for analysis. This is useful for running a study across many inputs or models through your Expected Parrot account. Start with a Jobs object and model access configured. You can run a job you have just constructed or load one from a saved package, as below.

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Run and save

Load a prepared job, inspect its prompts, and estimate the workload before running it:
With account access configured, request hosted execution explicitly:
This call waits for results before the next line saves them. For long jobs, use Background jobs to submit and return immediately, then inspect status and retrieve the answers later.

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Python execution settings

With a prepared job, use job.run(offload_execution=True) to request hosted execution explicitly. To orchestrate the job locally with direct provider access, use job.run(disable_remote_inference=True). Local orchestration may still call remote model APIs. Remote execution, API proxying, and remote caching are separate settings. Set disable_remote_cache=True when a local run must avoid the remote cache. Use disable_remote_inference=True for direct provider access from your machine; offload_execution=False alone does not establish that execution mode. See Jobs execution options for accepted execution options and Remote caching for response reuse.

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Failed or partial remote runs

A submitted job is not necessarily a completed dataset. Inspect the final status, completed interview count, and errors before analysis:
Replace JOB_UUID with your submitted job’s identifier. See Background jobs for finding jobs, retrieving completed Results, and reading results by page.

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CLI alternatives

Read each command’s JSON status before continuing. The blocking run saves completed data in results.ep; stdout contains execution metadata. For an existing remote job:
Replace JOB_UUID with the identifier returned at submission. The CLI rejects a failed or partially failed remote run by default. If you deliberately want its successful observations, use --allow-partial on the run command and inspect the missing observations before using the output:
This command submits or runs the job; it is not a download command for an existing job. A run with no successful observations still fails. To retrieve a previously submitted job, use ep jobs results JOB_UUID --output results.ep and inspect its returned status and warnings.