[HN Gopher] We no longer use LangChain for building our AI agents
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We no longer use LangChain for building our AI agents
Author : ma_za
Score : 38 points
Date : 2024-06-20 15:41 UTC (7 hours ago)
(HTM) web link (www.octomind.dev)
(TXT) w3m dump (www.octomind.dev)
| CharlieDigital wrote:
| Bigger problem might be using agents in the first place.
|
| We did some testing with agents for content generation (e.g.
| "authoring" agent, "researcher" agent, "editor" agent) and found
| that it was easier to just write it as 3 sequential prompts with
| an explicit control loop.
|
| It's easier to debug, monitor, and control the output flow this
| way.
|
| But we still use Semantic Kernel[0] because the lowest level
| abstractions that it provides are still very useful in reducing
| the code that we have to roll ourselves and also makes some parts
| of the API very flexible. These are things we'd end up writing
| ourselves anyways so why not just use the framework primitives
| instead?
|
| [0] https://github.com/microsoft/semantic-kernel
| Kiro wrote:
| What's the difference? I thought "agents" was just a fancier
| word for sequential prompts.
| deckar01 wrote:
| I recently unwrapped linktransformer to get access to some
| intermediate calculations and realized it was a pretty thin
| wrapper around SentenceTransformer and DBScan. It would have
| taken me so much longer to get similar results without copying
| their defaults and IO flow. It's easy to take for granted code
| you didn't have to develop from scratch. It would be interesting
| if there was a tool that inlined dependency calls and shook out
| unvisited branches automatically.
| luke-stanley wrote:
| From memory, I recall Vulture might do something like that!
| danielmarkbruce wrote:
| Yup. The problem with frameworks is they assume (historically
| mostly but not always correctly) that layers of abstraction mean
| one can forget about the layers below. This just doesn't work
| with LLMs. The systems are closer to biology or something.
| Kydlaw wrote:
| IMO LangChain provides very high level abstractions that are very
| useful for prototyping. It allows you to abstract away components
| while you dig deeper on some parts that will deliver actual
| value.
|
| But aside from that, I don't think I would run it in production.
| If something breaks, I feel like we would be in a world of pain
| to get things back up and running. I am glad they shared their
| experience on that, this is an interesting data point.
| cyanydeez wrote:
| In some sense, this could be retitled "We no longer use training
| wheels on our bikes"
| maximilianburke wrote:
| I just pulled out LangChain from our AI agents; we now have much
| smaller docker images and the code is a lot easier to understand.
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