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💽 refactor(client): Optimize ModelsConfig Query Cache #2330

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merged 2 commits into from
Apr 5, 2024

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danny-avila
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@danny-avila danny-avila commented Apr 5, 2024

Summary

The cache/state of modelsConfig was a bit complex/convoluted, also causing a weird bug when the app is loaded for the first time, causing all custom endpoints to auto-select the first model from the initial static data for openAI.

This fixes the highlighted issue but improves DX surrounding the models query data, removing more code than adding.

No observable changes should be created aside from the above fix.

Other changes

Attempted to remove eslint bypasses for exhaustive dependencies for useEffect. One such case creates infinite render, another doesn't. removed where it doesn't. made note where it does for other devs.

Change Type

  • Bug fix (non-breaking change which fixes an issue)

Checklist

  • My code adheres to this project's style guidelines
  • I have performed a self-review of my own code
  • I have commented in any complex areas of my code
  • I have made pertinent documentation changes
  • My changes do not introduce new warnings
  • I have written tests demonstrating that my changes are effective or that my feature works
  • Local unit tests pass with my changes
  • Any changes dependent on mine have been merged and published in downstream modules.
  • New documents have been locally validated with mkdocs

@danny-avila danny-avila merged commit f6a8488 into main Apr 5, 2024
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@danny-avila danny-avila deleted the modelQuery-refactor branch April 5, 2024 21:08
@mrtngrsbch
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Will this change result in a new release soon?

@danny-avila
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Will this change result in a new release soon?

Not necessarily but I am going to cut releases more often. Ideally weekly so updates are made more frequently.

kenshinsamue pushed a commit to intelequia/LibreChat that referenced this pull request Sep 17, 2024
* refactor(client): remove double caching of models via recoil to rely exclusively on react-query

* chore(useConversation): add modelsQuery.data dep to callback
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2 participants