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Português(PT) Quando o eval reprova o eval: avaliando um agente Google ADK sem tools

Developer finds flaws in Google ADK agent evaluation process

By PulseAugur Editorial · [1 sources] ·

A developer encountered issues while evaluating a Google ADK agent designed to answer questions about the Twenty One Pilots' lore. Initially, the agent received a perfect score on its evaluation, but the developer found this score to be misleading due to flawed evaluation criteria. After refining the evaluation process, the agent began failing cases, revealing errors in both the agent's responses and the evaluation's design. This iterative process highlighted the challenges in creating robust evaluation methods for LLM agents, especially when the evaluation model itself might favor responses similar to the agent's. AI

IMPACT Highlights challenges in LLM agent evaluation and the need for robust testing methodologies.

RANK_REASON Developer's personal account of debugging and evaluating an LLM agent, not a primary release or industry-shaping event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Developer finds flaws in Google ADK agent evaluation process

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Developer's personal account of debugging and evaluating an LLM agent, not a primary release or industry-shaping event.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 Português(PT) · Caio Carvalho ·

    When eval fails eval: evaluating a Google ADK agent without tools

    <p>O primeiro eval do meu agente deu 8 de 8. Nota máxima em todas as rubricas, em todos os casos, inclusive nos adversariais. Era o tipo de resultado que dá vontade de commitar e seguir em frente.</p> <p>Aquele 8/8 não dizia nada. Nas rodadas seguintes, o eval reprovou cinco caso…

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