mirror of
https://github.com/open-webui/open-webui
synced 2025-06-23 02:16:52 +00:00
Feat: Added indiviudal rag config - switch between default and individual
This commit is contained in:
weberm1
parent
baeecbb9d1
commit
4de37362eb
@ -1,47 +1,237 @@
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<script>
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import { goto } from '$app/navigation';
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import { getContext } from 'svelte';
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const i18n = getContext('i18n');
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import { onMount, getContext, createEventDispatcher } from 'svelte';
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import { toast } from 'svelte-sonner';
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import Switch from '$lib/components/common/Switch.svelte';
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import SensitiveInput from '$lib/components/common/SensitiveInput.svelte';
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import Tooltip from '$lib/components/common/Tooltip.svelte';
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import { createNewKnowledge, getKnowledgeBases } from '$lib/apis/knowledge';
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import { toast } from 'svelte-sonner';
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import { knowledge, user } from '$lib/stores';
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import AccessControl from '../common/AccessControl.svelte';
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let loading = false;
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import {
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getQuerySettings,
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updateQuerySettings,
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resetVectorDB,
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getEmbeddingConfig,
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updateEmbeddingConfig,
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getRerankingConfig,
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updateRerankingConfig,
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getRAGConfig,
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updateRAGConfig
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} from '$lib/apis/retrieval';
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import Textarea from '$lib/components/common/Textarea.svelte';
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import resourcesToBackend from 'i18next-resources-to-backend';
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const i18n = getContext('i18n');
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let loading = false;
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let name = '';
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let description = '';
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let accessControl = {};
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let updateEmbeddingModelLoading = false;
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let embeddingEngine = '';
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let embeddingModel = '';
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let embeddingBatchSize = 1;
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let OpenAIUrl = '';
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let OpenAIKey = '';
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let OllamaUrl = '';
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let OllamaKey = '';
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let querySettings = {
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template: '',
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r: 0.0,
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k: 4,
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k_reranker: 4,
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hybrid: false
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};
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let enableIndividualRagConfig = false;
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let RAGConfig = null;
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const embeddingModelUpdateHandler = async (knowledgeId) => {
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if (embeddingEngine === '' && embeddingModel.split('/').length - 1 > 1) {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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)
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);
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return;
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}
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if (embeddingEngine === 'ollama' && embeddingModel === '') {
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toast.error(
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$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 === 'openai' && embeddingModel === '') {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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)
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);
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return;
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}
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if ((embeddingEngine === 'openai' && OpenAIKey === '') || OpenAIUrl === '') {
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toast.error($i18n.t('OpenAI URL/Key required.'));
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return;
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}
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console.log('Update embedding model attempt:', embeddingModel);
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updateEmbeddingModelLoading = true;
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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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embedding_batch_size: embeddingBatchSize,
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ollama_config: {
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key: OllamaKey,
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url: OllamaUrl
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},
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openai_config: {
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key: OpenAIKey,
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url: OpenAIUrl
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},
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knowledge_id: knowledgeId
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}).catch(async (error) => {
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toast.error(`${error}`);
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await setEmbeddingConfig();
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return null;
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});
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updateEmbeddingModelLoading = false;
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if (res) {
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console.log('embeddingModelUpdateHandler:', res);
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if (res.status === true) {
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toast.success($i18n.t('Embedding model set to "{{embedding_model}}"', res), {
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duration: 1000 * 10
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});
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}
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}
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};
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const setEmbeddingConfig = async () => {
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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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embeddingBatchSize = embeddingConfig.embedding_batch_size ?? 1;
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OpenAIKey = embeddingConfig.openai_config.key;
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OpenAIUrl = embeddingConfig.openai_config.url;
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OllamaKey = embeddingConfig.ollama_config.key;
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OllamaUrl = embeddingConfig.ollama_config.url;
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}
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};
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const submitHandler = async () => {
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loading = true;
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if (name.trim() === '' || description.trim() === '') {
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toast.error($i18n.t('Please fill in all fields.'));
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name = '';
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description = '';
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loading = false;
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return;
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}
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const res = await createNewKnowledge(
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localStorage.token,
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if (enableIndividualRagConfig) {
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if (
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RAGConfig.CONTENT_EXTRACTION_ENGINE === 'external' &&
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RAGConfig.EXTERNAL_DOCUMENT_LOADER_URL === ''
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) {
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toast.error($i18n.t('External Document Loader URL required.'));
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return;
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}
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if (RAGConfig.CONTENT_EXTRACTION_ENGINE === 'tika' && RAGConfig.TIKA_SERVER_URL === '') {
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toast.error($i18n.t('Tika Server URL required.'));
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return;
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}
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if (RAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling' && RAGConfig.DOCLING_SERVER_URL === '') {
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toast.error($i18n.t('Docling Server URL required.'));
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return;
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}
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if (
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RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence' &&
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(RAGConfig.DOCUMENT_INTELLIGENCE_ENDPOINT === '' ||
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RAGConfig.DOCUMENT_INTELLIGENCE_KEY === '')
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) {
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toast.error($i18n.t('Document Intelligence endpoint and key required.'));
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return;
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}
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if (
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RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mistral_ocr' &&
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RAGConfig.MISTRAL_OCR_API_KEY === ''
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) {
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toast.error($i18n.t('Mistral OCR API Key required.'));
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return;
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}
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}
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const res = await createNewKnowledge(localStorage.token,
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name,
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description,
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accessControl
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accessControl,
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RAGConfig
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).catch((e) => {
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toast.error(`${e}`);
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});
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if (res) {
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toast.success($i18n.t('Knowledge created successfully.'));
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toast.success($i18n.t('Knowledge base created successfully.'));
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knowledge.set(await getKnowledgeBases(localStorage.token));
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goto(`/workspace/knowledge/${res.id}`);
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}
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if (enableIndividualRagConfig) {
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if (!RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL) {
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await embeddingModelUpdateHandler(res.id);
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if (RAGConfig.ENABLE_RAG_HYBRID_SEARCH) {
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const {
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embedding_engine,
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embedding_model,
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embedding_batch_size,
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openai_config,
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ollama_config,
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LOADED_EMBEDDING_MODELS,
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DOWNLOADED_EMBEDDING_MODELS,
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LOADED_RERANKING_MODELS,
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DOWNLOADED_RERANKING_MODELS,
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...filteredRAGConfig
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} = RAGConfig;
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// update ragconfig to load reranker
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const backendRAGConfig = { ...filteredRAGConfig, knowledge_id: res.id };
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await updateRAGConfig(localStorage.token, backendRAGConfig);
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}
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}
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}
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loading = false;
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};
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onMount(async () => {
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await setEmbeddingConfig();
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RAGConfig = await getRAGConfig(localStorage.token);
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});
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</script>
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<div class="w-full max-h-full">
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@ -104,7 +294,7 @@
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bind:value={description}
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placeholder={$i18n.t('Describe your knowledge base and objectives')}
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required
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/>
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></textarea>
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</div>
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</div>
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</div>
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@ -120,8 +310,597 @@
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</div>
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</div>
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<div class="flex justify-end mt-2">
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<div>
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<div class="mt-4">
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<div class="block text-sm font-medium mb-1">
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{$i18n.t('Enable Individual RAG Configuration')}
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<Switch
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bind:state={enableIndividualRagConfig}
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on:change={() => {
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RAGConfig.DEFAULT_RAG_SETTINGS = !enableIndividualRagConfig;
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}}
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/>
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</div>
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</div>
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{#if enableIndividualRagConfig}
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<div class="flex w-full justify-between">
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<div class="self-center text-xs font-medium">
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{$i18n.t('Content Extraction Engine')}
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</div>
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<div class="">
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<select
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class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right"
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bind:value={RAGConfig.CONTENT_EXTRACTION_ENGINE}
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>
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<option value="">{$i18n.t('Default')}</option>
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<option value="external">{$i18n.t('External')}</option>
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<option value="tika">{$i18n.t('Tika')}</option>
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<option value="docling">{$i18n.t('Docling')}</option>
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<option value="document_intelligence">{$i18n.t('Document Intelligence')}</option>
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<option value="mistral_ocr">{$i18n.t('Mistral OCR')}</option>
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</select>
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</div>
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</div>
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<div class="space-y-4 mt-4">
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{#if RAGConfig.CONTENT_EXTRACTION_ENGINE === ''}
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<div class="flex w-full mt-1">
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<div class="flex-1 flex justify-between">
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<div class=" self-center text-xs font-medium">
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{$i18n.t('PDF Extract Images (OCR)')}
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</div>
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<div class="flex items-center relative">
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<Switch bind:state={RAGConfig.PDF_EXTRACT_IMAGES} />
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</div>
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</div>
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</div>
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{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'external'}
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<div class="my-0.5 flex gap-2 pr-2">
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<input
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class="flex-1 w-full text-sm bg-transparent outline-hidden"
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placeholder={$i18n.t('Enter External Document Loader URL')}
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bind:value={RAGConfig.EXTERNAL_DOCUMENT_LOADER_URL}
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/>
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<SensitiveInput
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placeholder={$i18n.t('Enter External Document Loader API Key')}
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required={false}
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bind:value={RAGConfig.EXTERNAL_DOCUMENT_LOADER_API_KEY}
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/>
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</div>
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{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'tika'}
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<div class="flex w-full mt-1">
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<div class="flex-1 mr-2">
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<input
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class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
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placeholder={$i18n.t('Enter Tika Server URL')}
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bind:value={RAGConfig.TIKA_SERVER_URL}
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/>
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</div>
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</div>
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{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling'}
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<div class="flex w-full mt-1">
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<input
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class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
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placeholder={$i18n.t('Enter Docling Server URL')}
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bind:value={RAGConfig.DOCLING_SERVER_URL}
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/>
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</div>
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{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence'}
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<div class="my-0.5 flex gap-2 pr-2">
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<input
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class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
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placeholder={$i18n.t('Enter Document Intelligence Endpoint')}
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bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_ENDPOINT}
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/>
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<SensitiveInput
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placeholder={$i18n.t('Enter Document Intelligence Key')}
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bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_KEY}
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/>
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</div>
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{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mistral_ocr'}
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<div class="my-0.5 flex gap-2 pr-2">
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<SensitiveInput
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placeholder={$i18n.t('Enter Mistral API Key')}
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bind:value={RAGConfig.MISTRAL_OCR_API_KEY}
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/>
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</div>
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{/if}
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</div>
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<div class=" mb-2.5 flex w-full justify-between">
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<div class=" self-center text-xs font-medium">
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<Tooltip content={$i18n.t('Full Context Mode')} placement="top-start">
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{$i18n.t('Bypass Embedding and Retrieval')}
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</Tooltip>
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</div>
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<div class="flex items-center relative">
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<Tooltip
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content={RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL
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? $i18n.t(
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'Inject the entire content as context for comprehensive processing, this is recommended for complex queries.'
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)
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: $i18n.t(
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'Default to segmented retrieval for focused and relevant content extraction, this is recommended for most cases.'
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)}
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>
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<Switch bind:state={RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL} />
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</Tooltip>
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</div>
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</div>
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{#if !RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL}
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<div class=" mb-2.5 flex w-full justify-between">
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<div class=" self-center text-xs font-medium">{$i18n.t('Text Splitter')}</div>
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<div class="flex items-center relative">
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<select
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class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right"
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bind:value={RAGConfig.TEXT_SPLITTER}
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>
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<option value="">{$i18n.t('Default')} ({$i18n.t('Character')})</option>
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<option value="token">{$i18n.t('Token')} ({$i18n.t('Tiktoken')})</option>
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</select>
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</div>
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</div>
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<div class=" mb-2.5 flex w-full justify-between">
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<div class=" flex gap-1.5 w-full">
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<div class=" w-full justify-between">
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<div class="self-center text-xs font-medium min-w-fit mb-1">
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{$i18n.t('Chunk Size')}
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</div>
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<div class="self-center">
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<input
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class=" w-full rounded-lg py-1.5 px-4 text-sm bg-gray-50 dark:text-gray-300 dark:bg-gray-850 outline-hidden"
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type="number"
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placeholder={$i18n.t('Enter Chunk Size')}
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bind:value={RAGConfig.CHUNK_SIZE}
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autocomplete="off"
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min="0"
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/>
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</div>
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</div>
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<div class="w-full">
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<div class=" self-center text-xs font-medium min-w-fit mb-1">
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{$i18n.t('Chunk Overlap')}
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</div>
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<div class="self-center">
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<input
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class="w-full rounded-lg py-1.5 px-4 text-sm bg-gray-50 dark:text-gray-300 dark:bg-gray-850 outline-hidden"
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type="number"
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placeholder={$i18n.t('Enter Chunk Overlap')}
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bind:value={RAGConfig.CHUNK_OVERLAP}
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autocomplete="off"
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min="0"
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/>
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</div>
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</div>
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</div>
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</div>
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{/if}
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{#if !RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL}
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<div class="mb-3">
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<div class=" mb-2.5 text-base font-medium">{$i18n.t('Embedding')}</div>
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<hr class=" border-gray-100 dark:border-gray-850 my-2" />
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<div class=" mb-2.5 flex flex-col w-full justify-between">
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<div class="flex w-full justify-between">
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<div class=" self-center text-xs font-medium">
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{$i18n.t('Embedding Model Engine')}
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</div>
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<div class="flex items-center relative">
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<select
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class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 p-1 text-xs bg-transparent outline-hidden text-right"
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||||
bind:value={embeddingEngine}
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placeholder="Select an embedding model engine"
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on:change={(e) => {
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if (e.target.value === 'ollama') {
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embeddingModel = '';
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} else if (e.target.value === 'openai') {
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embeddingModel = 'text-embedding-3-small';
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} else if (e.target.value === '') {
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embeddingModel = 'sentence-transformers/all-MiniLM-L6-v2';
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}
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||||
}}
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>
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<option value="">{$i18n.t('Default (SentenceTransformers)')}</option>
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||||
<option value="ollama">{$i18n.t('Ollama')}</option>
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<option value="openai">{$i18n.t('OpenAI')}</option>
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</select>
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</div>
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</div>
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{#if embeddingEngine === 'openai'}
|
||||
<div class="my-0.5 flex gap-2 pr-2">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
placeholder={$i18n.t('API Base URL')}
|
||||
bind:value={OpenAIUrl}
|
||||
required
|
||||
/>
|
||||
|
||||
<SensitiveInput placeholder={$i18n.t('API Key')} bind:value={OpenAIKey} />
|
||||
</div>
|
||||
{:else if embeddingEngine === 'ollama'}
|
||||
<div class="my-0.5 flex gap-2 pr-2">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
placeholder={$i18n.t('API Base URL')}
|
||||
bind:value={OllamaUrl}
|
||||
required
|
||||
/>
|
||||
|
||||
<SensitiveInput
|
||||
placeholder={$i18n.t('API Key')}
|
||||
bind:value={OllamaKey}
|
||||
required={false}
|
||||
/>
|
||||
</div>
|
||||
{/if}
|
||||
</div>
|
||||
|
||||
<div class=" mb-2.5 flex flex-col w-full">
|
||||
<div class=" mb-1 text-xs font-medium">{$i18n.t('Embedding Model')}</div>
|
||||
{#if $user?.role === 'admin'}
|
||||
<div class="">
|
||||
{#if embeddingEngine === 'ollama'}
|
||||
<div class="flex w-full">
|
||||
<div class="flex-1 mr-2">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
bind:value={embeddingModel}
|
||||
placeholder={$i18n.t('Set embedding model')}
|
||||
required
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
{:else}
|
||||
<div class="flex w-full">
|
||||
<div class="flex-1 mr-2">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
placeholder={$i18n.t('Set embedding model (e.g. {{model}})', {
|
||||
model: embeddingModel.slice(-40)
|
||||
})}
|
||||
bind:value={embeddingModel}
|
||||
/>
|
||||
</div>
|
||||
|
||||
{#if embeddingEngine === ''}
|
||||
<button
|
||||
class="px-2.5 bg-transparent text-gray-800 dark:bg-transparent dark:text-gray-100 rounded-lg transition"
|
||||
on:click={() => {
|
||||
embeddingModelUpdateHandler();
|
||||
}}
|
||||
disabled={updateEmbeddingModelLoading}
|
||||
>
|
||||
{#if updateEmbeddingModelLoading}
|
||||
<div class="self-center">
|
||||
<svg
|
||||
class=" w-4 h-4"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
>
|
||||
<style>
|
||||
.spinner_ajPY {
|
||||
transform-origin: center;
|
||||
animation: spinner_AtaB 0.75s infinite linear;
|
||||
}
|
||||
|
||||
@keyframes spinner_AtaB {
|
||||
100% {
|
||||
transform: rotate(360deg);
|
||||
}
|
||||
}
|
||||
</style>
|
||||
<path
|
||||
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"
|
||||
opacity=".25"
|
||||
/>
|
||||
<path
|
||||
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"
|
||||
class="spinner_ajPY"
|
||||
/>
|
||||
</svg>
|
||||
</div>
|
||||
{:else}
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 16 16"
|
||||
fill="currentColor"
|
||||
class="w-4 h-4"
|
||||
>
|
||||
<path
|
||||
d="M8.75 2.75a.75.75 0 0 0-1.5 0v5.69L5.03 6.22a.75.75 0 0 0-1.06 1.06l3.5 3.5a.75.75 0 0 0 1.06 0l3.5-3.5a.75.75 0 0 0-1.06-1.06L8.75 8.44V2.75Z"
|
||||
/>
|
||||
<path
|
||||
d="M3.5 9.75a.75.75 0 0 0-1.5 0v1.5A2.75 2.75 0 0 0 4.75 14h6.5A2.75 2.75 0 0 0 14 11.25v-1.5a.75.75 0 0 0-1.5 0v1.5c0 .69-.56 1.25-1.25 1.25h-6.5c-.69 0-1.25-.56-1.25-1.25v-1.5Z"
|
||||
/>
|
||||
</svg>
|
||||
{/if}
|
||||
</button>
|
||||
{/if}
|
||||
</div>
|
||||
{/if}
|
||||
</div>
|
||||
{/if}
|
||||
<div class="flex w-full">
|
||||
<div class="flex-1 mr-2">
|
||||
<select
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden p-2 border border-gray-300"
|
||||
bind:value={embeddingModel}
|
||||
required
|
||||
>
|
||||
<option value="" disabled selected>{$i18n.t('Select embedding model')}</option>
|
||||
<!-- Always show the current value first if it's not empty -->
|
||||
{#if embeddingModel && embeddingModel.trim() !== ''}
|
||||
<option value={embeddingModel} class="py-1 font-semibold">
|
||||
{embeddingModel}
|
||||
{#if embeddingEngine &&
|
||||
RAGConfig.DOWNLOADED_EMBEDDING_MODELS[embeddingEngine] &&
|
||||
!RAGConfig.DOWNLOADED_EMBEDDING_MODELS[embeddingEngine]?.includes(embeddingModel)}
|
||||
(custom)
|
||||
{/if}
|
||||
</option>
|
||||
{/if}
|
||||
|
||||
<!-- Then show all downloaded models from the selected engine -->
|
||||
{#if embeddingEngine && RAGConfig.DOWNLOADED_EMBEDDING_MODELS[embeddingEngine]}
|
||||
{#each RAGConfig.DOWNLOADED_EMBEDDING_MODELS[embeddingEngine] as model}
|
||||
{#if model !== embeddingModel} <!-- Skip the current model as it's already shown -->
|
||||
<option value={model} class="py-1">{model}</option>
|
||||
{/if}
|
||||
{/each}
|
||||
{/if}
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
<div class="mt-1 mb-1 text-xs text-gray-400 dark:text-gray-500">
|
||||
{$i18n.t(
|
||||
'Warning: If you update or change your embedding model, you will need to re-import all documents.'
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{#if embeddingEngine === 'ollama' || embeddingEngine === 'openai'}
|
||||
<div class=" mb-2.5 flex w-full justify-between">
|
||||
<div class=" self-center text-xs font-medium">
|
||||
{$i18n.t('Embedding Batch Size')}
|
||||
</div>
|
||||
|
||||
<div class="">
|
||||
<input
|
||||
bind:value={embeddingBatchSize}
|
||||
type="number"
|
||||
class=" bg-transparent text-center w-14 outline-none"
|
||||
min="-2"
|
||||
max="16000"
|
||||
step="1"
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
</div>
|
||||
|
||||
<div class="mb-3">
|
||||
<div class=" mb-2.5 text-base font-medium">{$i18n.t('Retrieval')}</div>
|
||||
|
||||
<hr class=" border-gray-100 dark:border-gray-850 my-2" />
|
||||
|
||||
<div class=" mb-2.5 flex w-full justify-between">
|
||||
<div class=" self-center text-xs font-medium">{$i18n.t('Full Context Mode')}</div>
|
||||
<div class="flex items-center relative">
|
||||
<Tooltip
|
||||
content={RAGConfig.RAG_FULL_CONTEXT
|
||||
? $i18n.t(
|
||||
'Inject the entire content as context for comprehensive processing, this is recommended for complex queries.'
|
||||
)
|
||||
: $i18n.t(
|
||||
'Default to segmented retrieval for focused and relevant content extraction, this is recommended for most cases.'
|
||||
)}
|
||||
>
|
||||
<Switch bind:state={RAGConfig.RAG_FULL_CONTEXT} />
|
||||
</Tooltip>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{#if !RAGConfig.RAG_FULL_CONTEXT}
|
||||
<div class=" mb-2.5 flex w-full justify-between">
|
||||
<div class=" self-center text-xs font-medium">{$i18n.t('Hybrid Search')}</div>
|
||||
<div class="flex items-center relative">
|
||||
<Switch
|
||||
bind:state={RAGConfig.ENABLE_RAG_HYBRID_SEARCH}
|
||||
on:change={() => {
|
||||
if (!RAGConfig.ENABLE_RAG_HYBRID_SEARCH) {
|
||||
RAGConfig.RAG_RERANKING_MODEL = "";
|
||||
}
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{#if RAGConfig.ENABLE_RAG_HYBRID_SEARCH === true}
|
||||
<div class=" mb-2.5 flex flex-col w-full justify-between">
|
||||
<div class="flex w-full justify-between">
|
||||
<div class=" self-center text-xs font-medium">
|
||||
{$i18n.t('Reranking Engine')}
|
||||
</div>
|
||||
<div class="flex items-center relative">
|
||||
<select
|
||||
class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 p-1 text-xs bg-transparent outline-hidden text-right"
|
||||
bind:value={RAGConfig.RAG_RERANKING_ENGINE}
|
||||
placeholder="Select a reranking model engine"
|
||||
on:change={(e) => {
|
||||
if (e.target.value === 'external') {
|
||||
RAGConfig.RAG_RERANKING_MODEL = '';
|
||||
} else if (e.target.value === '') {
|
||||
RAGConfig.RAG_RERANKING_MODEL = 'BAAI/bge-reranker-v2-m3';
|
||||
}
|
||||
}}
|
||||
>
|
||||
<option value="">{$i18n.t('Default (SentenceTransformers)')}</option>
|
||||
<option value="external">{$i18n.t('External')}</option>
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{#if RAGConfig.RAG_RERANKING_ENGINE === 'external'}
|
||||
<div class="my-0.5 flex gap-2 pr-2">
|
||||
<input
|
||||
class="flex-1 w-full text-sm bg-transparent outline-hidden"
|
||||
placeholder={$i18n.t('API Base URL')}
|
||||
bind:value={RAGConfig.RAG_EXTERNAL_RERANKER_URL}
|
||||
required
|
||||
/>
|
||||
|
||||
<SensitiveInput
|
||||
placeholder={$i18n.t('API Key')}
|
||||
bind:value={RAGConfig.RAG_EXTERNAL_RERANKER_API_KEY}
|
||||
required={false}
|
||||
/>
|
||||
</div>
|
||||
{/if}
|
||||
</div>
|
||||
<div class=" mb-2.5 flex flex-col w-full">
|
||||
<div class=" mb-1 text-xs font-medium">{$i18n.t('Reranking Model')}</div>
|
||||
{#if $user?.role === 'admin'}
|
||||
<div class="">
|
||||
<div class="flex w-full">
|
||||
<div class="flex-1 mr-2">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
placeholder={$i18n.t('Set reranking model (e.g. {{model}})', {
|
||||
model: 'BAAI/bge-reranker-v2-m3'
|
||||
})}
|
||||
bind:value={RAGConfig.RAG_RERANKING_MODEL}
|
||||
on:input={() => {
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
<div class="flex w-full">
|
||||
<div class="flex-1 mr-2">
|
||||
<select
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden p-2 border border-gray-300"
|
||||
bind:value={RAGConfig.RAG_RERANKING_MODEL}
|
||||
required
|
||||
>
|
||||
<option value="" disabled selected>{$i18n.t('Select reranking model')}</option>
|
||||
<!-- Always show the current value first if it's not empty -->
|
||||
{#if RAGConfig.RAG_RERANKING_MODEL && RAGConfig.RAG_RERANKING_MODEL.trim() !== ''}
|
||||
<option value={RAGConfig.RAG_RERANKING_MODEL} class="py-1 font-semibold">
|
||||
{RAGConfig.RAG_RERANKING_MODEL}
|
||||
{#if RAGConfig.RAG_RERANKING_ENGINE !== undefined &&
|
||||
RAGConfig.DOWNLOADED_RERANKING_MODELS[RAGConfig.RAG_RERANKING_ENGINE] &&
|
||||
!RAGConfig.DOWNLOADED_RERANKING_MODELS[RAGConfig.RAG_RERANKING_ENGINE]?.some(model => model.RAG_RERANKING_MODEL === RAGConfig.RAG_RERANKING_MODEL)}
|
||||
(custom)
|
||||
{/if}
|
||||
</option>
|
||||
{/if}
|
||||
|
||||
<!-- Then show all downloaded models from the selected engine -->
|
||||
{#if RAGConfig.RAG_RERANKING_ENGINE !== undefined && RAGConfig.DOWNLOADED_RERANKING_MODELS[RAGConfig.RAG_RERANKING_ENGINE]}
|
||||
{#each RAGConfig.DOWNLOADED_RERANKING_MODELS[RAGConfig.RAG_RERANKING_ENGINE] as model}
|
||||
{#if model !== RAGConfig.RAG_RERANKING_MODEL} <!-- Skip the current model as it's already shown -->
|
||||
<option value={model} class="py-1">{model}</option>
|
||||
{/if}
|
||||
{/each}
|
||||
{/if}
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
<div class=" mb-2.5 flex w-full justify-between">
|
||||
<div class=" self-center text-xs font-medium">{$i18n.t('Top K')}</div>
|
||||
<div class="flex items-center relative">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
type="number"
|
||||
placeholder={$i18n.t('Enter Top K')}
|
||||
bind:value={RAGConfig.TOP_K}
|
||||
autocomplete="off"
|
||||
min="0"
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{#if RAGConfig.ENABLE_RAG_HYBRID_SEARCH === true}
|
||||
<div class="mb-2.5 flex w-full justify-between">
|
||||
<div class="self-center text-xs font-medium">{$i18n.t('Top K Reranker')}</div>
|
||||
<div class="flex items-center relative">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
type="number"
|
||||
placeholder={$i18n.t('Enter Top K Reranker')}
|
||||
bind:value={RAGConfig.TOP_K_RERANKER}
|
||||
autocomplete="off"
|
||||
min="0"
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
|
||||
{#if RAGConfig.ENABLE_RAG_HYBRID_SEARCH === true}
|
||||
<div class=" mb-2.5 flex flex-col w-full justify-between">
|
||||
<div class=" flex w-full justify-between">
|
||||
<div class=" self-center text-xs font-medium">
|
||||
{$i18n.t('Relevance Threshold')}
|
||||
</div>
|
||||
<div class="flex items-center relative">
|
||||
<input
|
||||
class="flex-1 w-full rounded-lg text-sm bg-transparent outline-hidden"
|
||||
type="number"
|
||||
step="0.01"
|
||||
placeholder={$i18n.t('Enter Score')}
|
||||
bind:value={RAGConfig.RELEVANCE_THRESHOLD}
|
||||
autocomplete="off"
|
||||
min="0.0"
|
||||
title={$i18n.t(
|
||||
'The score should be a value between 0.0 (0%) and 1.0 (100%).'
|
||||
)}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
<div class="mt-1 text-xs text-gray-400 dark:text-gray-500">
|
||||
{$i18n.t(
|
||||
'Note: If you set a minimum score, the search will only return documents with a score greater than or equal to the minimum score.'
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
{/if}
|
||||
|
||||
<div class=" mb-2.5 flex flex-col w-full justify-between">
|
||||
<div class=" mb-1 text-xs font-medium">{$i18n.t('RAG Template')}</div>
|
||||
<div class="flex w-full items-center relative">
|
||||
<Tooltip
|
||||
content={$i18n.t(
|
||||
'Leave empty to use the default prompt, or enter a custom prompt'
|
||||
)}
|
||||
placement="top-start"
|
||||
className="w-full"
|
||||
>
|
||||
<Textarea
|
||||
bind:value={RAGConfig.RAG_TEMPLATE}
|
||||
placeholder={$i18n.t(
|
||||
'Leave empty to use the default prompt, or enter a custom prompt'
|
||||
)}
|
||||
/>
|
||||
</Tooltip>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{/if}
|
||||
{/if}
|
||||
|
||||
<div class="flex justify-end mt-6">
|
||||
<button
|
||||
class="text-sm px-4 py-2 transition rounded-lg {loading
|
||||
? 'cursor-not-allowed bg-gray-100 dark:bg-gray-800'
|
||||
@ -160,6 +939,6 @@
|
||||
{/if}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
Loading…
Reference in New Issue
Block a user