How to debug and trace LLM application failures in production environments

How to debug and trace LLM application failures in production environments

This task can be performed using Agenta

Agenta is an open-source LLMOps platform for building reliable AI apps. Manage prompts, run evaluations, and debug traces. We help developers and domain experts collaborate to ship LLM applications faster and with confidence.

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Agenta

Agenta

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Agenta is an open-source LLMOps platform that helps AI teams build and ship reliable LLM applications. Developers and subject matter experts work together to experiment with prompts, run evaluations, and debug production issues. The platform addresses a common problem: LLMs are unpredictable, and most teams lack the right processes. Prompts get scattered across tools. Teams work in silos and deploy without validation. When things break, debugging feels like guesswork. Agenta centralizes your LLM development workflow: Experiment: Compare prompts and models side by side. Track version history and debug with real production data. Evaluate: Replace guesswork with automated evaluations. Integrate LLM-as-a-judge, built-in evaluators, or your own code. Observe: Trace every request to find failure points. Turn any trace into a test with one click. Monitor production with live evaluations.

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What to expect from an ideal product

  1. Track every LLM request in real-time with detailed traces that show exactly where your application failed and why it happened
  2. Turn production failures into reproducible test cases with one click, so you can debug issues using the same data that caused the problem
  3. Monitor your LLM apps continuously with live evaluations that catch problems before users do, instead of waiting for complaints
  4. Compare different prompt versions side by side using real production data to see which changes actually fix the issues you're facing
  5. Debug with your whole team by centralizing traces and evaluation results in one place, so developers and domain experts can work together to solve problems faster

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