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Update README with agentrial and Chidori details #39

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Expand Up @@ -34,6 +34,28 @@ This list is made by the team behind [e2b](https://github.com/e2b-dev/e2b). E2b
Feel free to reach out to us at [hello@e2b.dev](mailto:hello@e2b.dev).
Check out also our database of [AI agents](https://github.com/e2b-dev/awesome-ai-agents).

## [agentrial](https://github.com/alepot55/agentrial)
agentrial is the pytest for AI agents: run N trials, get confidence intervals, catch regressions before production.

<details>

<!-- ### Description -->

AI agents pass benchmarks but fail in production. Why? Single-run evaluations hide variance. agentrial runs your agent N times, computes Wilson confidence intervals, and uses Fisher exact tests to detect regressions in CI/CD. pip install agentrial, write a YAML, done.

Unlike DeepEval/Promptfoo (LLM-first, agent bolted on), agentrial is agent-native: trajectory evaluation, step-level failure attribution, multi-agent coordination metrics, and real API cost tracking. Framework-agnostic via adapters for LangGraph, CrewAI, AutoGen, Pydantic AI, OpenAI Agents, smolagents.

</details>


## [Chidori](https://github.com/ThousandBirdsInc/chidori)
Chidori is a reactive runtime for building AI agents. It provides a framework for building AI agents that are reactive, observable, and robust. It supports building agents with Node.js, Python, and Rust.
It is currently in alpha, and is not yet ready for production use.

<details>

<!-- ### Description -->


## [E2B](https://www.e2b.dev/)
E2b is an operating system for AI agents, that is, a set of tools, APIs, and cloud environments for agents.
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