ИИ-агенты
opik
Open-source LLM observability: trace, evaluate and monitor apps and agents
★ 22,5 тыс. звёздApache-2.0
Смотреть руководство →openllmetry — проект с открытым исходным кодом из категории «ИИ-агенты» от traceloop (traceloop/openllmetry на GitHub). У него 7 477 звёзд на GitHub и 1 134 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 6 октября 2026.
OpenTelemetry-native observability for LLM apps.
Choose one real workload to test the project against.
Clone it locally and read through the getting-started guide.
Install the stack it needs and set any environment variables.
Execute the starter example and check results before going further.
Vendor-neutral traces, metrics, and logs.
Captures prompts, completions, and token usage.
Drop-in tracing for Python LLM apps.
Maintained by the Traceloop team.
Permissive licensing.
Built for operating GenAI in production.
Add the instrumentation package to your project.
pip install openllmetryInitialize tracing at your app's startup per the docs.
# see docs for the init snippetSend traces to your OpenTelemetry collector or backend.
# works with Jaeger, Grafana, and other OTel backendsIt is maintained by Traceloop at traceloop/openllmetry, with 1,134 forks.
Yes. It is released under the Apache-2.0 license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
The instrumentation is free; you bring your own tracing backend, self-hosted or otherwise.
It is OpenTelemetry-native and vendor-neutral, so it fits existing observability stacks rather than a dedicated LLM platform.
Install the package, initialize it in your app per the docs, and point it at your collector.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.