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https://github.com/invoke-ai/InvokeAI
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feat(ui): optimize model query caching
When we retrieve a list of models, upsert that data into the `getModelConfig` and `getModelConfigByAttrs` query caches. With this change, calls to those two queries are almost always going to be free, because their caches will already have all models in them. The exception is queries for models that no longer exist.
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@ -1,4 +1,4 @@
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import type { EntityAdapter, EntityState } from '@reduxjs/toolkit';
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import type { EntityAdapter, EntityState, ThunkDispatch, UnknownAction } from '@reduxjs/toolkit';
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import { createEntityAdapter } from '@reduxjs/toolkit';
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import { getSelectorsOptions } from 'app/store/createMemoizedSelector';
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import queryString from 'query-string';
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@ -111,6 +111,12 @@ export const vaeModelsAdapter = createEntityAdapter<VAEModelConfig, string>({
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});
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export const vaeModelsAdapterSelectors = vaeModelsAdapter.getSelectors(undefined, getSelectorsOptions);
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export const anyModelConfigAdapter = createEntityAdapter<AnyModelConfig, string>({
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selectId: (entity) => entity.key,
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sortComparer: (a, b) => a.name.localeCompare(b.name),
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});
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export const anyModelConfigAdapterSelectors = anyModelConfigAdapter.getSelectors(undefined, getSelectorsOptions);
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const buildProvidesTags =
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<TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
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(result: EntityState<TEntity, string> | undefined) => {
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@ -141,8 +147,6 @@ const buildTransformResponse =
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*/
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const buildModelsUrl = (path: string = '') => buildV2Url(`models/${path}`);
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// TODO(psyche): Ideally we can share the cache between the `getXYZModels` queries and `getModelConfig` query
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export const modelsApi = api.injectEndpoints({
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endpoints: (build) => ({
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getMainModels: build.query<EntityState<MainModelConfig, string>, BaseModelType[]>({
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@ -157,6 +161,11 @@ export const modelsApi = api.injectEndpoints({
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},
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providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
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transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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getModelMetadata: build.query<GetModelMetadataResponse, string>({
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query: (key) => {
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@ -236,6 +245,7 @@ export const modelsApi = api.injectEndpoints({
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return tags;
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},
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serializeQueryArgs: ({ queryArgs }) => `${queryArgs.name}.${queryArgs.base}.${queryArgs.type}`,
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}),
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syncModels: build.mutation<void, void>({
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query: () => {
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@ -250,31 +260,61 @@ export const modelsApi = api.injectEndpoints({
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query: () => ({ url: buildModelsUrl(), params: { model_type: 'lora' } }),
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providesTags: buildProvidesTags<LoRAModelConfig>('LoRAModel'),
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transformResponse: buildTransformResponse<LoRAModelConfig>(loraModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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getControlNetModels: build.query<EntityState<ControlNetModelConfig, string>, void>({
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query: () => ({ url: buildModelsUrl(), params: { model_type: 'controlnet' } }),
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providesTags: buildProvidesTags<ControlNetModelConfig>('ControlNetModel'),
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transformResponse: buildTransformResponse<ControlNetModelConfig>(controlNetModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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getIPAdapterModels: build.query<EntityState<IPAdapterModelConfig, string>, void>({
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query: () => ({ url: buildModelsUrl(), params: { model_type: 'ip_adapter' } }),
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providesTags: buildProvidesTags<IPAdapterModelConfig>('IPAdapterModel'),
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transformResponse: buildTransformResponse<IPAdapterModelConfig>(ipAdapterModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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getT2IAdapterModels: build.query<EntityState<T2IAdapterModelConfig, string>, void>({
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query: () => ({ url: buildModelsUrl(), params: { model_type: 't2i_adapter' } }),
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providesTags: buildProvidesTags<T2IAdapterModelConfig>('T2IAdapterModel'),
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transformResponse: buildTransformResponse<T2IAdapterModelConfig>(t2iAdapterModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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getVaeModels: build.query<EntityState<VAEModelConfig, string>, void>({
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query: () => ({ url: buildModelsUrl(), params: { model_type: 'vae' } }),
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providesTags: buildProvidesTags<VAEModelConfig>('VaeModel'),
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transformResponse: buildTransformResponse<VAEModelConfig>(vaeModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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getTextualInversionModels: build.query<EntityState<TextualInversionModelConfig, string>, void>({
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query: () => ({ url: buildModelsUrl(), params: { model_type: 'embedding' } }),
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providesTags: buildProvidesTags<TextualInversionModelConfig>('TextualInversionModel'),
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transformResponse: buildTransformResponse<TextualInversionModelConfig>(textualInversionModelsAdapter),
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onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
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queryFulfilled.then(({ data }) => {
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upsertModelConfigs(data, dispatch);
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});
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},
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}),
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scanModels: build.query<ScanFolderResponse, ScanFolderArg>({
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query: (arg) => {
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@ -336,3 +376,15 @@ export const {
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useDeleteModelImportMutation,
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usePruneModelImportsMutation,
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} = modelsApi;
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const upsertModelConfigs = (
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modelConfigs: EntityState<AnyModelConfig, string>,
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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dispatch: ThunkDispatch<any, any, UnknownAction>
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) => {
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anyModelConfigAdapterSelectors.selectAll(modelConfigs).forEach((modelConfig) => {
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dispatch(modelsApi.util.upsertQueryData('getModelConfig', modelConfig.key, modelConfig));
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const { base, name, type } = modelConfig;
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dispatch(modelsApi.util.upsertQueryData('getModelConfigByAttrs', { base, name, type }, modelConfig));
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});
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};
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