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LangSmith能逐层记录每次模型调用的Prompt输入、模型输出、Token消耗与延迟，并将复杂调用链可视化为树状结构

1

Sources

50%

Confidence

Medium-term (~90 days)

Relevance

7/7/2026

First Seen

Valid until: 10/5/2026

Sources

LangChain 1.0全面解析：三大框架与AI应用开发实战指南

bilibiliClaudeCode教程7/6/2026

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UnverifiedLangSmith、LangFuse、Arize Phoenix等工具专为大模型可观测性场景设计，能记录并回放模型推理的输入输出、工具调用参数与返回值、Token消耗量及延迟数据73% similar UnverifiedTree-of-Thought允许模型同时展开多条推理路径，从中筛选出最优执行路径72% similar UnverifiedLangGraph借鉴了Pregel图计算模型，支持有状态的循环执行，更适合需要反复迭代的代理工作流71% similar UnverifiedJMeter线程组通过配置线程数、加速时间（Ramp-Up Period）和循环次数（Loop Count）来控制负载模型69% similar Unverified模型路由是更广泛的模型编排趋势的核心组成部分，编排层还涵盖提示词管理、上下文压缩、结果缓存和多模型并行调用69% similar

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