agent-regression-lens-py
Detect regressions between baseline and current AI agent runs. Pure Python, zero deps. Python port of @mukundakatta/agent-regression-lens.
pip install agent-regression-lens-py
from agent_regression_lens import analyze_agent_regression
baseline = {"events": [{"type": "tool_call", "tool": "search"}, {"type": "final", "content": "ok"}], "success": True}
current = {"events": [{"type": "tool_call", "tool": "search"}, {"type": "error", "message": "boom"}], "success": False}
res = analyze_agent_regression(baseline, current)
# RegressionResult(passed=False, score=..., regressions=[Issue(code='lost_success', severity='critical', ...), ...])
API
analyze_agent_regression(baseline, current, *, thresholds=None) -> RegressionResultcompare_run_set(baseline_runs, current_runs, *, thresholds=None) -> ComparisonSummary
Detects: lost success, new errors, failed tool calls, output drift (Jaccard), step / latency / cost bloat above configurable ratios.
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for agent-regression-lens-py 0.1.0
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