TruLens

Open-source 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.

Pytest-style LLM evaluation framework. Open source.

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.

LangChain's hosted observability + eval platform.

Tracing, dataset management, eval orchestration, and prompt playground from the LangChain team. Pairs naturally if LangChain or LangGraph already runs in your stack, but works standalone via SDKs.

LLM tracing + evaluation. Strong on retrieval debugging.

Phoenix is Arize's observability platform — run locally in a notebook or as a hosted service. Especially strong for inspecting RAG pipelines, finding bad chunks, and tracking retrieval quality over time.