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Scenario generation + real conversation import - Our scenario generation agent bootstraps your test suite from a description of your agent. But real users find paths no generator anticipates, so we also ingest your production conversations and automatically extract test cases from them. Your coverage evolves as your users do.Mock tool platform - Agents call tools. Running simulations against real APIs is slow and flaky. Our mock tool platform lets you define tool schemas, behavior, and return values so simulations exercise tool selection and decision-making without touching production systems.Deterministic, structured test cases - LLMs are stochastic. A CI test that passes "most of the time" is useless. Rather than free-form prompts, our evaluators are defined as structured conditional action trees: explicit conditions that trigger specific responses, with support for fixed messages when word-for-word precision matters. This means the synthetic user behaves consistently across runs - same branching logic, same inputs - so a failure is a real regression, not noise.Cekura also monitors your live agent traffic. The obvious alternative here is a tracing platform like Langfuse or LangSmith - and they're great tools for debugging individual LLM calls. But conversational agents have a different failure mode: the bug isn't in any single turn, it's in how turns relate to each other. Take a verification flow that requires name, date of birth, and phone number before proceeding - if the agent skips asking for DOB and moves on anyway, every individual turn looks fine in isolation. The failure only becomes visible when you evaluate the full session as a unit. Cekura is built around this from the ground up.

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然而,他並未提及戰爭結束後的伊朗將會是什麼模樣,也未解釋為何他認為該國在這次行動後就不再威脅美國。。关于这个话题,体育直播提供了深入分析

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美以军事打击伊朗

美国普林斯顿大学资深中东问题专家凯文·哈里斯就指出,美国商务部、财政部和中央情报局已形成专门小组,从2024年起秘密接洽伊朗某些被制裁的公司和家族财阀,寻求幕后交易,例如伊朗社保组织(SSO)下属的退休基金公司负责人已和美方建立联系,存在关键时刻“输诚”的可能性。