abi-evals 0.1.2

Eval harness with golden management for the ABI ecosystem

abi-evals

Evaluation harness with failure taxonomy, regression store, and model canary for AI pipeline quality assurance. Works with any Python project — no ABI dependencies required in production.

Zero production dependencies.

Install (after PyPI publication)

pip install abi-evals

Status: Not yet published to PyPI. Install from source: pip install -e . from the repo root.

Quick start

Failure taxonomy

from abi_evals.failure_taxonomy import FailureTaxonomy

# Load a taxonomy from YAML or JSON, or build one programmatically
taxonomy = FailureTaxonomy.from_yaml("failure_types.yaml")

# Classify an error by matching detection probes against error text
matches = taxonomy.classify("Output exceeded token budget")
for failure_type in matches:
    print(failure_type.failure_id)  # e.g., "FT-BUDGET-001"
    print(failure_type.category)    # e.g., "budget"
    print(failure_type.severity)    # e.g., "high"

Model canary

from abi_evals.model_canary import ModelCanary

# Compare a new model version against a baseline
canary = ModelCanary(
    eval_suite_path="evals/suite.json",
    baseline_results_path="evals/baseline_results.json",
)
result = canary.run_canary(new_model_config={"run_id": "canary_test"})
print(result.verdict)          # "PASS" | "WARN" | "FAIL"
print(result.regression_count) # number of regressions detected
print(result.success_rate_delta)

Eval runner (function-based API)

from pathlib import Path
from abi_evals.runner import load_eval_suite, run_suite

suite = load_eval_suite(Path("evals/my_suite.json"))
results = run_suite(suite)

What's included

• Failure taxonomy -- structured failure classification for clear diagnostics
• Failure distiller -- converts classified failures into regression eval cases
• Regression store -- manages storage and deduplication of regression cases
• Model canary -- validates model version changes against baselines before acceptance
• Eval runner -- deterministic eval suites with pluggable comparators
• CI-friendly -- exit codes and JSON output for gating in any CI pipeline

Use it standalone

abi-evals works with any Python project. Point it at your eval suites and failure logs — no ABI ecosystem integration needed.

Within the ABI ecosystem, it integrates with abi-control-core schemas for eval case and result validation.

ABI ecosystem

Related packages:

• abi-control-core -- contracts and audit trail SDK
• abi-policy -- policy evaluation engine
• abi-observability -- OTLP-compliant telemetry

Versioning

Follows Semantic Versioning. Current version: 0.1.2. See CHANGELOG.md for release notes.

License

MIT License (see LICENSE file).