[munro]

I had built an agent with LangGraph a 9 months ago--now seems React agents are in LangChain. Over all pretty happy with that, I just don't use any of the dumb stuff like embedding/search layer: just tools&state

But I was actually playing with a few frameworks yesterday and struggling--I want what I want without having to write it. ;). Ended up using pydantic_ai package, literally just want tools w/ pydantic validation--but out of the box it doesn't have good observability, you would have to use their proprietary SaaS; and it comes bundled with Temporal.io (yo odio eso proyecto). I had to write my own observability which was annoying, and it sucks.

If anyone has any things they've built, I would love to know, and TypeScript is an option. I want: - ReAct agent with tools that have schema validation - built in REALTIME observability w/ WebUI - customizable playground ChatUI (This is where TypeScript would shine) - no corporate takeover tentacles

p.s.s: I know... I purposely try to avoid hard recommendations on HN, to avoid enshittification. "reddit best X" has been gamed. And generally skip these subtle promotional posts..

[DouweM]

Hey munro, Douwe from Pydantic AI here. Our docs have a page dedicated to observability: https://ai.pydantic.dev/logfire/, which is all based on OpenTelemetry and its gen_ai conventions.

The Logfire SDK that Pydantic AI uses is a generic OTel client that defaults to sending data to Pydantic Logfire, our SaaS observability platform: https://pydantic.dev/logfire, but can easily be pointed at any OTel sink: https://ai.pydantic.dev/logfire/#logfire-with-an-alternative...

Temporal is one of multiple durable execution solutions (https://ai.pydantic.dev/durable_execution/overview/) we support and its SDK is indeed included by default in the "fat" `pydantic-ai` package, as are the SDKs for all model providers. There's also a `pydantic-ai-slim` package that doesn't include any optional dependencies: https://ai.pydantic.dev/install/#slim-install

[thewhitetulip]

I have also worked on react agents using langgraph and I've not faced much issues! This thread has been confusing! Am I doing anything incorrectly? Or am I misunderstanding what people call as agents?