Job management system#

The OpenProtein.AI platform operates with an asynchronous framework. When initiating a task using our Python client, the system schedules the job, returning a prompt response with a unique Job ID. This mechanism ensures that tasks requiring longer processing times do not necessitate immediate waiting.

About Future Classes#

When you submit a task, for example creating an MSA with session.poet.create_msa(), a Future Class is returned for results tracking and access. You can check a job’s status using the refresh() and done() methods on this Future Class. If you wish to wait for the results, you can use the wait() method, or the get() method if the results are already completed.

Accessing previous jobs#

Resume a prompt, PoET, MSA, or embeddings workflow using the load_job function with the unique job ID obtained during task execution. This method will return a Future Class, allowing you to continue from where you left off.

[ ]:
job = session.load_job(job_id)

To download an assay you have uploaded:

[ ]:
assay =