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giskard-oss vs Ragas

Giskard v3: modular Python evals and red-teaming for agentic systems — scenario-based checks with LLM-as-judge, plus an automatic vulnerability scanner across OWASP LLM Top-10 categories. — versus — Evaluation toolkit for your RAG and agent pipelines — faithfulness, relevance, and more.

The curated verdict

Overlapping LLM-evaluation job: ragas is the specialist for RAG pipeline metrics; Giskard v3 covers multi-turn agent scenarios with built-in checks and LLM-as-judge, with RAG evaluation still pending its v3 port.

giskard-ossRagas
Stars5.6k15k
Forks4941.6k
LanguagePythonPython
LicenseApache-2.0Apache-2.0
Last activitytoday4 months ago
Topicsevals, securityevals, rag
Curated connections35

giskard-oss — the curator's take

One of the OG names in LLM testing, freshly rewritten: v3 drops the heavyweight monolith for focused packages — giskard-checks (scenario API for multi-turn agent evals: groundedness, conformity, LLM-judge) and giskard-scan (generates adversarial suites from a plain-language description of your agent, prompt-injection probes included). Async-first, wraps anything callable. Mind the transition, though: v3 is beta, RAG evaluation (RAGET) hasn't been ported yet, and v2 — where scan and RAG eval are mature — is no longer maintained. Python 3.12+ only, and libraries on giskard-core send aggregated telemetry (opt-out documented). Pick ragas for pure RAG metrics; Giskard earns its place on multi-turn agent scenarios plus red-teaming in one stack.

Ragas — the curator's take

Evaluation toolkit for your RAG and agent pipelines — faithfulness, relevance, and more.