Deepchecks

Open-source evaluation and red-teaming for LLM agents and RAG apps.

Giskard is an open-source (Apache-2.0) Python library for testing LLMs, RAG pipelines, and ML models — its Scan automatically surfaces hallucinations, prompt injection, bias, and other vulnerabilities, while red-teaming agents run multi-turn adversarial attacks across dozens of probes. The paid Giskard Hub adds team collaboration, continuous testing, and scheduled scans. The team also publishes the open Phare LLM safety benchmark.

Pytest-style framework for evaluating LLM apps in CI.

Open-source (Apache 2.0) framework for evaluating LLM apps the way Pytest tests code — assertions backed by 50+ ready metrics spanning LLM-as-judge, RAG, agents, conversation, and safety. Plugs into LangChain, CrewAI, OpenAI Agents and more. Confident AI is the paid cloud platform that adds test management, dashboards, and observability on top.

Evaluation toolkit for RAG and LLM applications.

Open-source (Apache-2.0) Python framework for evaluating retrieval-augmented generation and LLM apps. Provides reference-free metrics — faithfulness, answer relevancy, context precision/recall — plus knowledge-graph-based synthetic test generation. Integrates with LangChain, LlamaIndex, and CI pipelines.

LLM eval CLI with rubric scoring and golden sets.

YAML-driven eval harness. Pair a prompt with a goldset, define rubrics, run across multiple models in CI. Strong for catching prompt regressions before they hit production.