martosaur

martosaur

Handwave - just handwave any problem with LLM

Handwave is a thin wrapper around InstructorLite that makes it simpler to use vague handwaving in your apps.

It comes with 3 built-in providers (Handwave.OpenAI, Handwave.Claude and Handwave.Gemini) and behaviour to define your own.

Here’s its whole API surface:

  1. Use llm_if when you can’t come up with a regular if:
import Handwave.OpenAI

llm_if user_email, "looks suspicious?" do
  {:error, :blocked}
else
  create_user(user_email)
end
  1. Use llm_rewrite when you just need that term() -> 🧠🪄✨ -> string function:
iex> llm_rewrite(
          %Req.Response{status: 401, body: "session token expired"},
          "Tell user what to do without technical details"
        )
"Your session has expired. Please log in again to continue."
  1. Use llm_route when you want LLM to just figure out what to do:
import Handwave.OpenAI

@impl Oban.Worker
def process(job) do
  # do things
catch
  kind, error ->
    formatted = Exception.format(kind, error, __STACKTRACE__)
    
    formatted
    |> llm_route([:snooze, :cancel, :error], "Snooze if it makes sense to try later, cancel if it's a lost cause, otherwise just error")
    |> case do
      :snooze -> {:snooze, 60}
      :cancel -> {:cancel, error}
      _ -> {:error, formatted}
    end
end

Have fun.

https://github.com/martosaur/handwave

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martosaur

martosaur

That were exactly my thoughts that led me to making this package, but ultimately, I came to realization that this is a useful library (that’s why I released it). Structured outputs for LLMs enable embedding small bits of intelligence in conventional application code and at this point I can’t help but admit that sometimes this is useful. Admittedly, examples in the readme are silly, because they have to be small and because I chose a playful tone for the library as a way to cope with new reality. But in real life I use this type of stuff to determine, for example, if user wants to do a “broad” search or “focused” one and trigger different search pipeline based on perceived intent.

I agree that this can be an absolutely cursed way to do things in the wrong hands. I’m not too worried though as it seems like nobody it writing code by hand these days and Claude won’t use this library.

FlyingNoodle

FlyingNoodle

llm_if user_email, "looks suspicious?" do

llm_if ← this is a joke right? Are we really at that point?

DaAnalyst

DaAnalyst

I actually like this, specially the llm_rewrite.

llm_if could be useful for non- too-deterministic cases, such as branching in video games.

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