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AI Infra2023
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Langfuse

Tracks, evaluates, and debugs LLM applications with traces, prompt management, datasets, playgrounds, and observability that can run in cloud or self-hosted setups.

Introduction

LLM applications fail in ways normal logs do not explain: prompts, retrieval context, tool calls, outputs, and feedback interact. Langfuse treats those pieces as one engineering system.

What Sets It Apart

It combines observability, prompt management, evaluations, datasets, and a playground. OpenTelemetry and ecosystem integrations help connect LangChain, OpenAI SDK, LiteLLM, and custom stacks to shared debugging and improvement loops.

Who Should Use It

Great fit if a team is moving from prototype to maintained AI product and needs visibility over time. Look elsewhere if you only need ad hoc local debugging.

Information

  • Websitegithub.com
  • OrganizationsLangfuse
  • AuthorsLangfuse (company)
  • Published date2023/05/18

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