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Decide approach for reusing code between wagtail-ai and wagtail-vector-index #90
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I think another way you can achieve that is to consider the following solutions:
As for the next step, I'd suggest creating a decision record that should explain:
I think that would be a good step to:
If that's the case, shouldn't the natural next step be to merge both libraries into one? I would personally be on board with that, with a caveat that it's hard to say given the lack of my background in the decision in the first place. I don't understand the benefit that the separation brings at the moment. Especially given that both libraries are meant to be used with Wagtail only and have a lot of crossover in code. |
In my mind the two packages serve different purposes and as such should be distinct. So perhaps let's start by documenting the intersection of the two, the plans for wagtail-ai and what it may use from wagtail-vector-index. That should gives a good starting point for a discussion, and an ADR to follow |
For some context; The There are some parts of the There is also value in allowing users to provide a single Django setting to configure their AI providers - right now if you use both At the moment I see
Finally, there are plans for My original thinking around this was to:
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Renamed, new goal is to consider how best to reuse code between these packages. |
wagtail-vector-index has support for additional AI backends like LiteLLM. To stop us having to replicate AI changes between packages, wagtail-ai could depend on wagtail-vector-index and reuse the AI backends from it.
The vector index features are likely to be used in future Wagtail AI features anyway.
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