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LangSmith enables LLM regression testing and audit trails

By PulseAugur Editorial · [2 sources] ·

This two-part series explores LLM observability and traceability, focusing on the LangSmith platform. Part 1 details how to make LLM applications replayable and create tamper-evident audit logs using LangSmith's tracing capabilities and custom callbacks. Part 2 addresses how to prevent regressions by implementing datasets, evaluators, and experiments, akin to traditional software regression testing, and discusses choosing the right tooling stack. AI

IMPACT Provides developers with tools for robust LLM application management, including regression testing and audit trails.

RANK_REASON The cluster discusses a specific software product, LangSmith, and its features for LLM observability and testing, rather than a new model release or research paper.

Read on Towards AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LangSmith enables LLM regression testing and audit trails

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0 / 100
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Newsworthiness bucket
Tool
The cluster discusses a specific software product, LangSmith, and its features for LLM observability and testing, rather than a new model release or research paper.
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2 independent sources
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Topics
product, infra
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High
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105 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

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COVERAGE [2]

  1. Towards AI TIER_1 English(EN) · Prashant Sahu ·

    LLM Observability with LangSmith — Part 2: Eval Gates, Prompt Versioning & Choosing Your Stack

    <h4><em>In Part 1, we made an agent replayable and audit-proof. Now we make it regression-proof — and then decide, with a clear head, whether LangSmith is even the right tool for your team.</em></h4><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*4lkz8-U6X9osB…

  2. Towards AI TIER_1 English(EN) · Prashant Sahu ·

    LLM Observability with LangSmith -Part 1: Tracing Everything & Building Audit-Grade Callbacks

    <h4><em>Your agent demoed perfectly. Then someone asked, “What exactly did the bot tell that customer on the 14th?” — and nobody could answer. This is the story of fixing that, end to end, with code.</em></h4><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*whJ…

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