mirror of
https://github.com/open-webui/open-webui
synced 2024-11-06 00:32:05 +00:00
feat: frontend integration
This commit is contained in:
parent
2952e61167
commit
9cdb5bf9fe
@ -138,20 +138,22 @@ async def get_status():
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}
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@app.get("/embedding/model")
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async def get_embedding_model(user=Depends(get_admin_user)):
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@app.get("/embedding")
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async def get_embedding_config(user=Depends(get_admin_user)):
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return {
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"status": True,
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"embedding_engine": app.state.RAG_EMBEDDING_ENGINE,
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"embedding_model": app.state.RAG_EMBEDDING_MODEL,
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}
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class EmbeddingModelUpdateForm(BaseModel):
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embedding_engine: str
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embedding_model: str
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@app.post("/embedding/model/update")
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async def update_embedding_model(
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@app.post("/embedding/update")
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async def update_embedding_config(
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form_data: EmbeddingModelUpdateForm, user=Depends(get_admin_user)
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):
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@ -160,18 +162,26 @@ async def update_embedding_model(
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)
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try:
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sentence_transformer_ef = (
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embedding_functions.SentenceTransformerEmbeddingFunction(
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model_name=get_embedding_model_path(form_data.embedding_model, True),
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device=DEVICE_TYPE,
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)
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)
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app.state.RAG_EMBEDDING_ENGINE = form_data.embedding_engine
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app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model
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app.state.sentence_transformer_ef = sentence_transformer_ef
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if app.state.RAG_EMBEDDING_ENGINE == "ollama":
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app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model
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app.state.sentence_transformer_ef = None
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else:
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sentence_transformer_ef = (
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embedding_functions.SentenceTransformerEmbeddingFunction(
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model_name=get_embedding_model_path(
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form_data.embedding_model, True
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),
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device=DEVICE_TYPE,
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)
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)
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app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model
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app.state.sentence_transformer_ef = sentence_transformer_ef
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return {
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"status": True,
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"embedding_engine": app.state.RAG_EMBEDDING_ENGINE,
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"embedding_model": app.state.RAG_EMBEDDING_MODEL,
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}
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@ -346,10 +346,10 @@ export const resetVectorDB = async (token: string) => {
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return res;
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};
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export const getEmbeddingModel = async (token: string) => {
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export const getEmbeddingConfig = async (token: string) => {
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let error = null;
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const res = await fetch(`${RAG_API_BASE_URL}/embedding/model`, {
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const res = await fetch(`${RAG_API_BASE_URL}/embedding`, {
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method: 'GET',
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headers: {
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'Content-Type': 'application/json',
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@ -374,13 +374,14 @@ export const getEmbeddingModel = async (token: string) => {
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};
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type EmbeddingModelUpdateForm = {
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embedding_engine: string;
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embedding_model: string;
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};
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export const updateEmbeddingModel = async (token: string, payload: EmbeddingModelUpdateForm) => {
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export const updateEmbeddingConfig = async (token: string, payload: EmbeddingModelUpdateForm) => {
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let error = null;
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const res = await fetch(`${RAG_API_BASE_URL}/embedding/model/update`, {
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const res = await fetch(`${RAG_API_BASE_URL}/embedding/update`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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@ -7,11 +7,11 @@
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scanDocs,
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updateQuerySettings,
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resetVectorDB,
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getEmbeddingModel,
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updateEmbeddingModel
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getEmbeddingConfig,
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updateEmbeddingConfig
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} from '$lib/apis/rag';
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import { documents } from '$lib/stores';
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import { documents, models } from '$lib/stores';
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import { onMount, getContext } from 'svelte';
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import { toast } from 'svelte-sonner';
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@ -27,6 +27,8 @@
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let showResetConfirm = false;
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let embeddingEngine = '';
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let embeddingModel = '';
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let chunkSize = 0;
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let chunkOverlap = 0;
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let pdfExtractImages = true;
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@ -36,8 +38,6 @@
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k: 4
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};
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let embeddingModel = '';
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const scanHandler = async () => {
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scanDirLoading = true;
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const res = await scanDocs(localStorage.token);
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@ -50,7 +50,16 @@
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};
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const embeddingModelUpdateHandler = async () => {
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if (embeddingModel.split('/').length - 1 > 1) {
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if (embeddingModel === '') {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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)
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);
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return;
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}
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if (embeddingEngine === '' && embeddingModel.split('/').length - 1 > 1) {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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@ -62,11 +71,17 @@
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console.log('Update embedding model attempt:', embeddingModel);
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updateEmbeddingModelLoading = true;
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const res = await updateEmbeddingModel(localStorage.token, {
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const res = await updateEmbeddingConfig(localStorage.token, {
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embedding_engine: embeddingEngine,
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embedding_model: embeddingModel
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}).catch(async (error) => {
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toast.error(error);
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embeddingModel = (await getEmbeddingModel(localStorage.token)).embedding_model;
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const embeddingConfig = await getEmbeddingConfig(localStorage.token);
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if (embeddingConfig) {
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embeddingEngine = embeddingConfig.embedding_engine;
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embeddingModel = embeddingConfig.embedding_model;
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}
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return null;
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});
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updateEmbeddingModelLoading = false;
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@ -102,7 +117,12 @@
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chunkOverlap = res.chunk.chunk_overlap;
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}
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embeddingModel = (await getEmbeddingModel(localStorage.token)).embedding_model;
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const embeddingConfig = await getEmbeddingConfig(localStorage.token);
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if (embeddingConfig) {
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embeddingEngine = embeddingConfig.embedding_engine;
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embeddingModel = embeddingConfig.embedding_model;
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}
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querySettings = await getQuerySettings(localStorage.token);
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});
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@ -126,6 +146,9 @@
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class="dark:bg-gray-900 w-fit pr-8 rounded px-2 p-1 text-xs bg-transparent outline-none text-right"
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bind:value={embeddingEngine}
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placeholder="Select an embedding engine"
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on:change={() => {
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embeddingModel = '';
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}}
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>
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<option value="">{$i18n.t('Default (SentenceTransformer)')}</option>
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<option value="ollama">{$i18n.t('Ollama')}</option>
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@ -136,10 +159,77 @@
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<div class="space-y-2">
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<div>
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<div class=" mb-2 text-sm font-medium">{$i18n.t('Update Embedding Model')}</div>
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{#if embeddingEngine === 'ollama'}
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<div>da</div>
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<div class="flex w-full">
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<div class="flex-1 mr-2">
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<select
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class="w-full rounded-lg py-2 px-4 text-sm dark:text-gray-300 dark:bg-gray-850 outline-none"
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bind:value={embeddingModel}
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placeholder={$i18n.t('Select a model')}
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required
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>
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{#if !embeddingModel}
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<option value="" disabled selected>{$i18n.t('Select a model')}</option>
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{/if}
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{#each $models.filter((m) => m.id && !m.external) as model}
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<option value={model.name} class="bg-gray-100 dark:bg-gray-700"
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>{model.name + ' (' + (model.size / 1024 ** 3).toFixed(1) + ' GB)'}</option
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>
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{/each}
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</select>
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</div>
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<button
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class="px-2.5 bg-gray-100 hover:bg-gray-200 text-gray-800 dark:bg-gray-850 dark:hover:bg-gray-800 dark:text-gray-100 rounded-lg transition"
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on:click={() => {
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embeddingModelUpdateHandler();
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}}
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disabled={updateEmbeddingModelLoading}
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>
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{#if updateEmbeddingModelLoading}
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<div class="self-center">
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<svg
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class=" w-4 h-4"
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viewBox="0 0 24 24"
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fill="currentColor"
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xmlns="http://www.w3.org/2000/svg"
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><style>
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.spinner_ajPY {
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transform-origin: center;
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animation: spinner_AtaB 0.75s infinite linear;
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}
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@keyframes spinner_AtaB {
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100% {
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transform: rotate(360deg);
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}
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}
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</style><path
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d="M12,1A11,11,0,1,0,23,12,11,11,0,0,0,12,1Zm0,19a8,8,0,1,1,8-8A8,8,0,0,1,12,20Z"
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opacity=".25"
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/><path
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d="M10.14,1.16a11,11,0,0,0-9,8.92A1.59,1.59,0,0,0,2.46,12,1.52,1.52,0,0,0,4.11,10.7a8,8,0,0,1,6.66-6.61A1.42,1.42,0,0,0,12,2.69h0A1.57,1.57,0,0,0,10.14,1.16Z"
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class="spinner_ajPY"
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/></svg
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>
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</div>
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{:else}
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<svg
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xmlns="http://www.w3.org/2000/svg"
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viewBox="0 0 16 16"
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fill="currentColor"
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class="w-4 h-4"
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>
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<path
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fill-rule="evenodd"
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d="M12.416 3.376a.75.75 0 0 1 .208 1.04l-5 7.5a.75.75 0 0 1-1.154.114l-3-3a.75.75 0 0 1 1.06-1.06l2.353 2.353 4.493-6.74a.75.75 0 0 1 1.04-.207Z"
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clip-rule="evenodd"
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/>
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</svg>
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{/if}
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</button>
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</div>
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{:else}
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<div class=" mb-2 text-sm font-medium">{$i18n.t('Update Embedding Model')}</div>
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<div class="flex w-full">
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<div class="flex-1 mr-2">
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<input
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@ -200,14 +290,14 @@
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{/if}
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</button>
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</div>
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<div class="mt-2 mb-1 text-xs text-gray-400 dark:text-gray-500">
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{$i18n.t(
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'Warning: If you update or change your embedding model, you will need to re-import all documents.'
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)}
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</div>
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{/if}
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<div class="mt-2 mb-1 text-xs text-gray-400 dark:text-gray-500">
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{$i18n.t(
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'Warning: If you update or change your embedding model, you will need to re-import all documents.'
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)}
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</div>
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<hr class=" dark:border-gray-700 my-3" />
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<div class=" flex w-full justify-between">
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