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so i m trying to think through how to

so i'm trying to think through how to effectively make this assistant. I think react out of the gate is probably not quite going to work.
What I'm envisioning is a chain where the first step is "Task breakdown", then each task is separately processed, and then the final result is either summarized or just spit out at the end.
For example, trying to set up cluster autoscaling in OpenShift (Kubernetes) involves 2 steps - creating a clusterautoscaler object and then creating a machineautoscaler object.

  • I have various forms of docs that can be queried/indexed to spit out that task list
  • I have docs that can be queried/indexed that describe both cluster and machine autoscaler objects
I haven't tried setting up multiple "tools" (task breakdown tool, documentation search) yet, but was just curious about people's thoughts here
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So if you don't use react, you'd have to design your own way of parsing results right?

Prompt the LLM with some message + instructions, prompt results, and go from there?
i'm not opposed to that method
i'm just not sure there's a "better" way
Take a look at ReWoo - haven't had a chance to implement it myself yet but it's pretty much aiming to parallelize and accomplish a set of outlined tasks, passing all the work to the LLM
will look, thanks
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