I'm Rogerio, founder of LangWatch, I've been helping many customers building LLM applications in this past two years and worked with Alex on this.
Most of the efforts for LLM quality so far were about evaluations, single-turn, there was nothing actually good to test agents, it all felt forced, but we believe we cracked it now, we have built an agent testing library that test your agent by simulating a user and playing a conversation back and forth with it.
One of the key challenges there was that we had to make it compatible with all the 273+ AI frameworks (and counting) there are. Luckliy AG-UI protocol popped up recently, standardizing agents frameworks and UI interactions, this is perfect, because at the end of the day, we want our user simulator to "see" just the same that the user sees.
So we made Scenario in a way that is really easy to connect to any agent no matter the tech stack, from a simple string <-> string connection, to openai standard messages format, to AG-UI.
The other key challenge was to balance testing the open-endedness of agents vs having reliable cases you want to test, so we worked a lot on thinking through the autopilot simulation vs the fully scripted one, and here again, the goal was complete interoperability. At the end of the day, the design we achieved was simply having lambdas, that you can call at any point of the test, so it's just code, where you can connect any other evaluation or assertion tool you want, we are not restrictive.
Check out the repo and the docs, we would love to get some feedback in here!
tl;dr: We built Scenario, an open-source testing library for AI agents. It simulates real conversations with your agent, its code-driven, and lets you assert anything mid-dialogue. Repo: https://github.com/langwatch/scenario Docs: https://scenario.langwatch.ai/
I'm Rogerio, founder of LangWatch, I've been helping many customers building LLM applications in this past two years and worked with Alex on this.
Most of the efforts for LLM quality so far were about evaluations, single-turn, there was nothing actually good to test agents, it all felt forced, but we believe we cracked it now, we have built an agent testing library that test your agent by simulating a user and playing a conversation back and forth with it.
One of the key challenges there was that we had to make it compatible with all the 273+ AI frameworks (and counting) there are. Luckliy AG-UI protocol popped up recently, standardizing agents frameworks and UI interactions, this is perfect, because at the end of the day, we want our user simulator to "see" just the same that the user sees.
So we made Scenario in a way that is really easy to connect to any agent no matter the tech stack, from a simple string <-> string connection, to openai standard messages format, to AG-UI.
The other key challenge was to balance testing the open-endedness of agents vs having reliable cases you want to test, so we worked a lot on thinking through the autopilot simulation vs the fully scripted one, and here again, the goal was complete interoperability. At the end of the day, the design we achieved was simply having lambdas, that you can call at any point of the test, so it's just code, where you can connect any other evaluation or assertion tool you want, we are not restrictive.
Check out the repo and the docs, we would love to get some feedback in here!
Repo: https://github.com/langwatch/scenario Docs: https://scenario.langwatch.ai/