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mesa-runtime/lib

A thin, programmatic wrapper around CI in this repo comprising a simple backend and a library that communicates with it.

Usage

from mesa_runtime import MesaRuntime

client = MesaRuntime("https://example.cloudfront.net", "username", "password")

run_id = client.dispatch("batch-2026-01", "foo", "onco")
print(client.get_run(run_id))

Batch inference uploads the batch file with the caller's AWS credentials:

run_id = client.run_batch_inference("foo/bar", "baz", "qux.jsonl", "quux")
print(client.get_inference_run(run_id))

API

Method Description
list_training_data() List available training data objects from S3
dispatch(training_batch_name, model_name, schema, ...) Trigger a workflow run, returns its ID
get_run(run_id) Fetch a single run by ID
list_runs() List the ten most recent runs
list_queued_runs() List all pending runs
cancel(run_id) Cancel a run
get_logs(run_id, ...) Fetch step logs for a run
get_step_inputs(run_id) Extract dispatch inputs from step env vars
get_runner_status() Get runner online/busy status
run_batch_inference(job_id, model_id, batch_file, bucket, ...) Upload a Bedrock batch file and trigger an inference run, returns its ID (split_across_models=True splits across every endpoint model, model_id may then be empty)
get_inference_run(run_id) Fetch a single inference run by ID
list_inference_runs() List the ten most recent inference runs
cancel_inference(run_id) Cancel an inference run
get_inference_logs(run_id, ...) Fetch step logs for an inference run

Metadata

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