cerbia-core provides cerbia.core, the configurable pipeline used by CerbIA
integrations. It includes entries, loaders, preprocessors, scanners, score
aggregators, configuration models, Runner, and SecurityGate.
Install
pip install cerbia-core
The core package requires Python 3.12 or later and Pydantic. It does not require the optional ML or NLP runtimes; those capabilities are provided by separate distributions.
Create and run a pipeline
This example creates a text loader, a keyword scanner, and a maximum score aggregator, then scans the configured entry:
from cerbia.core.config import (
CerbIAConfig,
LoaderConfig,
ScannerConfig,
ScoreAggregatorConfig,
)
from cerbia.core.runner import Runner
config = CerbIAConfig(
name="inline",
loaders=[LoaderConfig(loader="cerbia.core.loaders.TextLoader", init_args={"texts": "hello"})],
scanners=[ScannerConfig(scanner="cerbia.core.scanners.KeywordScanner")],
score_aggregator=ScoreAggregatorConfig(
score_aggregator="cerbia.core.score_aggregators.MaxScoreAggregator"
),
)
result = Runner(config).scan()
Runner requires at least one loader and scanner. It applies configured
preprocessors in order, then evaluates each resulting entry through the gate.
result.entry_results contains per-entry results, and result.is_safe reports
whether the complete run is safe.
Find component details
Use the product-wide references for the pipeline lifecycle, configuration format, loaders, preprocessors, scanners, and score aggregators. The quickstart walks through a working CLI example.