Signals

A signal runs the same labeling job on a repeating schedule: bind a job definition to an audience and an interval, and Rapidata creates a new job on every tick.

What a signal is

A signal ties together three things:

• an audience — who labels the data,
• a job definition — the task that gets run,
• an interval — how often it fires, in hours.

Each firing creates one RapidataJob, identical to a job you create directly. A signal is just a scheduler that keeps producing those jobs; every job runs the same job definition against the same audience.

graph LR
    S[Signal<br/>audience + job definition + interval] -->|every interval| J1[Job 1]
    S -->|every interval| J2[Job 2]
    S -->|every interval| J3[Job 3]

Creating a signal

from rapidata import RapidataClient

client = RapidataClient()

audience = client.audience.get_audience_by_id("aud_MU1GZYoESyO")

job_definition = client.job.create_compare_job_definition(
    name="Prompt Alignment Job",
    instruction="Which image follows the prompt more accurately?",
    datapoints=[
        ["https://assets.rapidata.ai/flux_book.jpg",
         "https://assets.rapidata.ai/mj_book.jpg"]
    ],
    contexts=["A small blue book sitting on a large red book."],
)

signal = client.signals.create_signal(
    name="Daily prompt alignment",
    audience=audience,
    job_definition=job_definition,
    interval_hours=24,
)

audience and job_definition also accept id strings. By default the signal uses the latest revision of the job definition at fire time; pin one with revision_number=.... Set is_public=True to let others in your organization read the signal.

The jobs a signal creates

Every firing creates a RapidataJob:

for job in signal.get_jobs(page_size=10):
    print(job, job.get_status())

results = signal.get_jobs(page_size=1)[0].get_results()

A firing can be skipped (for example if the previous job hasn't finished). A skipped firing creates no job and won't appear in get_jobs().

Triggering a job on demand

Fire one job immediately instead of waiting for the schedule:

signal.trigger()
job = signal.wait_for_next_job(timeout=600)
print(job.get_results())

trigger() returns right away; the job is created in the background. wait_for_next_job() blocks until the next firing has created its job and returns it.

Managing a signal

signal.pause()
signal.resume()
signal.update(name="Hourly prompt alignment", interval_hours=1)
signal.delete()

Look signals up later:

signal = client.signals.get_signal_by_id("signal_id")
signals = client.signals.find_signals(name="alignment")

Property reference

Property	Description
id	The signal's unique id.
name / description	Display name and optional description.
audience_id	The audience each job targets.
job_definition_id	The job definition each job is created from.
revision_number	Pinned job-definition revision, or None for "latest at fire time".
interval_hours	How often the signal fires, in hours.
next_run_at / last_run_at	Timestamps of the next and most recent firings.
is_paused	Whether the scheduler is currently skipping this signal.
is_public	Whether other users can discover and read it.
created_at	When the signal was created.

Copy for AI