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DocumentationSynthesize Safe Data

Safe Synthesizer NeMo Helix SDK Resources

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The nemo_safe_synthesizer_plugin.sdk module provides NeMo Helix-specific helpers for creating and monitoring NeMo Safe Synthesizer jobs. Use these objects when you want to create jobs through the platform Jobs service and retrieve platform-managed results.

SafeSynthesizerResource

SafeSynthesizerResource is the entry point for working with NeMo Safe Synthesizer on NeMo Helix. Build it from a NemoClient instance:

from nemo_helix_plugin.client.client import NemoClient
from nemo_safe_synthesizer_plugin.sdk.resources import SafeSynthesizerResource
client = NemoClient.from_config()
safe_synthesizer = SafeSynthesizerResource(client)

These examples use the default workspace. If your current CLI context uses a different workspace, run nemo config set --workspace default first. To check, run nemo config view.

An AsyncSafeSynthesizerResource with the same surface is available for AsyncNemoClient.

SafeSynthesizerJobsResource

safe_synthesizer.jobs calls the plugin API for NeMo Safe Synthesizer jobs.

MethodDescription
create(*, spec, name=None, workspace=None, project=None, timeout=None, **params)Creates a NeMo Safe Synthesizer platform job from a job spec.
list(*, workspace=None, **params)Lists NeMo Safe Synthesizer jobs in a workspace.
retrieve(name, *, workspace=None)Retrieves one NeMo Safe Synthesizer job by name.
get_status(name, *, workspace=None)Returns the job status from the platform Jobs service.
get_logs(name, *, workspace=None, **kwargs)Returns paginated job logs from the platform Jobs service.

The async resource exposes the same methods as async def methods.

SafeSynthesizerJobBuilder

SafeSynthesizerJobBuilder assembles a job spec, uploads local datasets to Files, creates the job, and returns a SafeSynthesizerJob wrapper.

import time
import pandas as pd
from nemo_safe_synthesizer_plugin.sdk.job_builder import SafeSynthesizerJobBuilder
df = pd.DataFrame({"text": [f"sample record {i}" for i in range(200)]})
job = (
    SafeSynthesizerJobBuilder(client, workspace="default")
    .with_data_source(df)
    .with_classify_model_provider("default/nvidia-build")
    .with_replace_pii()
    .synthesize()
    .create_job(name=f"safe-synth-job-{int(time.time())}")
)
MethodDescription
with_data_source(data_source)Sets a pandas DataFrame or local .csv, .parquet, .json, or .jsonl file as input. Local data is uploaded to Files before submission.
with_data(config=None, **kwargs)Sets data preparation parameters.
with_train(config=None, **kwargs)Sets fine-tuning parameters.
with_generate(config=None, **kwargs)Sets generation parameters and enables synthesis.
synthesize()Enables synthesis.
with_evaluate(config=None, **kwargs)Sets evaluation parameters.
with_differential_privacy(config=None, **kwargs)Sets DP-SGD parameters. Pass dp_enabled=True to enable DP-SGD.
with_time_series(config=None, **kwargs)Sets time-series parameters.
with_replace_pii(config=None, **kwargs)Enables PII replacement.
with_classify_model_provider(provider_name)Sets the Inference Gateway provider used for PII column classification. Pair with with_replace_pii().
with_hf_token_secret(secret_name)Passes a platform secret name as HF_TOKEN to the runtime job.
with_pretrained_model_job(job_name)Reuses a prior job’s adapter result for generation-only synthesis.
resolve_job_config()Uploads data and validates the generated job spec without creating a job.
create_job(**kwargs)Creates the job and returns SafeSynthesizerJob.

SafeSynthesizerJob

SafeSynthesizerJob is a convenience wrapper returned by the builder.

MethodDescription
fetch_status()Returns the current platform job status string.
fetch_status_info()Returns the full platform job status response.
wait_for_completion(poll_interval=10, verbose=True, log_timeout=None)Polls status and logs until the job reaches a terminal state. Raises RuntimeError for error or cancelled.
fetch_logs(timeout=None)Iterates over platform job log entries.
print_logs(timeout=None)Prints platform job logs to stdout.
fetch_data()Downloads the synthetic-data result and returns it as a pandas DataFrame.
fetch_summary()Downloads the summary result as a SafeSynthesizerSummary.
fetch_report()Downloads the evaluation-report result as HTML.
save_report(path)Saves the HTML evaluation report to a local file.
display_report_in_notebook(width="100%", height=1000)Displays the evaluation report in a notebook.