openllmetry
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What is openllmetry?
openllmetry is a small Python library that makes it easy to watch what your AI agent is doing and how well it is working. It wraps calls to large-language-model APIs, vector stores, and other tools, then sends logs, traces, and simple metrics to any backend that speaks the OpenTelemetry standard, such as Jaeger, Zipkin, or Grafana. You add one or two lines of code at start-up, and the library captures prompt text, model name, latency, token counts, and costs each time the agent asks the model for an answer. The data helps you spot slow steps, high spend, or bad answers, and it lets you play back full traces to debug agent chains. Because it follows OpenTelemetry, you can mix these AI traces with normal service traces and see the whole flow in one place.
Free resources to learn openllmetry
- Official docsOpenTelemetry Documentation
- Official docsWhat is OpenLLMetry? - traceloop
- Official docsUse Traceloop with Python
- Open sourcetraceloop/openllmetry
More in stage 30: Prompt Injection / Jailbreaks
openllmetry: common questions
Can I learn openllmetry in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain openllmetry in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this openllmetry tutorial for beginners?
It is lesson 97 of 101 in the free AI Agents roadmap, in stage 30, Prompt Injection / Jailbreaks. If you are new to AI Agents, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.