ИИ-агенты
opik
Open-source LLM observability: trace, evaluate and monitor apps and agents
★ 22,5 тыс. звёздApache-2.0
Смотреть руководство →helicone — проект с открытым исходным кодом из категории «ИИ-агенты» от Helicone (Helicone/helicone на GitHub). У него 6 207 звёзд на GitHub и 683 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 16 сентября 2026.
Open-source LLM observability: monitor, evaluate, and experiment.
Start with one concrete task rather than a grand architecture.
Clone the repo and check the examples folder for a quickstart.
Install packages, set environment variables, and point it at your model.
Execute the demo workflow, then adapt it to your own data.
Proxy your calls with minimal code.
Every prompt and completion recorded.
Score outputs and track quality.
A/B prompts and models.
See what your agents spend.
Self-hostable and open.
Download the source and move into the project folder.
git clone https://github.com/Helicone/helicone.git
cd heliconePull in the Node packages the project needs.
npm installTreat these as starting points - the README documents the exact commands.
npm run buildHelicone/helicone is its home on GitHub, with 683 forks so far. The contributors tab and recent commits show how actively it is maintained.
Yes - it is Apache-2.0 licensed, so it is free for commercial use with attribution.
Self-hosting is free and open source; the hosted cloud version may have a paid tier.
Both observe LLM apps. Helicone is a proxy-based observability platform; Weave is a dev toolkit from the Weights & Biases team. Try Helicone for drop-in monitoring, Weave for deeper experiment tracking.
Follow the README quickstart, then browse the examples directory for patterns that match what you want to build.
Open-source LLM observability: trace, evaluate and monitor apps and agents
OpenTelemetry-native observability for LLM apps.
Open-source observability for AI agents: trace, evaluate, guard, and improve.
One open platform to simulate, evaluate, guardrail, trace, and optimise LLM and agent apps, self-hostable.
Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic syst…
Code, build and evaluate LLM agents with full MCP, Skills, ACP and A2A support.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.