aiexpect
Python assertions for non-deterministic AI text that drop into pytest. Semantic and rule checks work offline; optional LLM judge with your own model; produces a Trust Score and a single-file HTML report.
- from
- Testing
- added
- 2026-10-10
- likes
- 0
similar
-
great-expectations github.com
-
GreatExpectation greatexpectations.io
Open Source data validation framework to manage data quality. Users can define and document “expectations” rules about how data should look and behave.
-
ai-evaluation github.com
Open-source LLM and agent evaluation framework with 50+ metrics, LLM-as-Judge augmentation, and guardrail scanners (jailbreak, PII, prompt-injection). Useful for scoring RAG outputs, agent trajectories, and function-calling behavior in data-science workflows.
-
eslint-plugin-ai-guard github.com
Detects bugs and security issues commonly introduced by AI-generated code (async misuse, empty catch, auth gaps, SQL concat, secrets).
-
httpexpect github.com
Concise, declarative, and easy to use end-to-end HTTP and REST API testing.
-
expect-test github.com
Testing › Software > AI & LLM Testing: “Python assertions for non-deterministic AI text that drop into pytest. Semantic and rule checks work offline; optional LLM judge with your own model; produces a Trust Score and a single-file HTML report.”