[danenania]

I haven't used LangChain, but my sense is that much of what it's really helping people with is stream handling and async control flow. While there are libraries that make it easier, I think doing this stuff right in Python can feel like swimming against the current given its history as a primarily synchronous, single-threaded runtime.

I built an agent-based AI coding tool in Go (https://github.com/plandex-ai/plandex) and I've been very happy with that choice. While there's much less of an ecosystem of LLM-related libraries and frameworks, Go's concurrency primitives make it straightforward to implement whatever I need, and I never have to worry about leaky or awkward abstractions.

[siva7]

Not really. There isn't much that langchain is doing in this regard. The heavy lifting is already done by the original libs like from openai which they use and the rest are just wrappers around their api calls.

[danenania]

The langchain apis seem to include a lot of functionality for ‘chaining’ LLM calls and streams. That’s what I was referring to.