<script lang="ts"> import { toast } from 'svelte-sonner'; import { onMount, getContext, createEventDispatcher } from 'svelte'; const dispatch = createEventDispatcher(); import { getQuerySettings, updateQuerySettings, resetVectorDB, getEmbeddingConfig, updateEmbeddingConfig, getRerankingConfig, updateRerankingConfig, getRAGConfig, updateRAGConfig } from '$lib/apis/retrieval'; import { reindexKnowledgeFiles } from '$lib/apis/knowledge'; import { deleteAllFiles } from '$lib/apis/files'; import ResetUploadDirConfirmDialog from '$lib/components/common/ConfirmDialog.svelte'; import ResetVectorDBConfirmDialog from '$lib/components/common/ConfirmDialog.svelte'; import ReindexKnowledgeFilesConfirmDialog from '$lib/components/common/ConfirmDialog.svelte'; import SensitiveInput from '$lib/components/common/SensitiveInput.svelte'; import Tooltip from '$lib/components/common/Tooltip.svelte'; import Switch from '$lib/components/common/Switch.svelte'; import Textarea from '$lib/components/common/Textarea.svelte'; import Spinner from '$lib/components/common/Spinner.svelte'; const i18n = getContext('i18n'); let updateEmbeddingModelLoading = false; let updateRerankingModelLoading = false; let showResetConfirm = false; let showResetUploadDirConfirm = false; let showReindexConfirm = false; let embeddingEngine = ''; let embeddingModel = ''; let embeddingBatchSize = 1; let rerankingModel = ''; let OpenAIUrl = ''; let OpenAIKey = ''; let AzureOpenAIUrl = ''; let AzureOpenAIKey = ''; let AzureOpenAIVersion = ''; let OllamaUrl = ''; let OllamaKey = ''; let querySettings = { template: '', r: 0.0, k: 4, k_reranker: 4, hybrid: false }; let RAGConfig = null; const embeddingModelUpdateHandler = async () => { if (embeddingEngine === '' && embeddingModel.split('/').length - 1 > 1) { toast.error( $i18n.t( 'Model filesystem path detected. Model shortname is required for update, cannot continue.' ) ); return; } if (embeddingEngine === 'ollama' && embeddingModel === '') { toast.error( $i18n.t( 'Model filesystem path detected. Model shortname is required for update, cannot continue.' ) ); return; } if (embeddingEngine === 'openai' && embeddingModel === '') { toast.error( $i18n.t( 'Model filesystem path detected. Model shortname is required for update, cannot continue.' ) ); return; } if (embeddingEngine === 'openai' && (OpenAIKey === '' || OpenAIUrl === '')) { toast.error($i18n.t('OpenAI URL/Key required.')); return; } if ( embeddingEngine === 'azure_openai' && (AzureOpenAIKey === '' || AzureOpenAIUrl === '' || AzureOpenAIVersion === '') ) { toast.error($i18n.t('OpenAI URL/Key required.')); return; } console.debug('Update embedding model attempt:', embeddingModel); updateEmbeddingModelLoading = true; const res = await updateEmbeddingConfig(localStorage.token, { embedding_engine: embeddingEngine, embedding_model: embeddingModel, embedding_batch_size: embeddingBatchSize, ollama_config: { key: OllamaKey, url: OllamaUrl }, openai_config: { key: OpenAIKey, url: OpenAIUrl }, azure_openai_config: { key: AzureOpenAIKey, url: AzureOpenAIUrl, version: AzureOpenAIVersion } }).catch(async (error) => { toast.error(`${error}`); await setEmbeddingConfig(); return null; }); updateEmbeddingModelLoading = false; if (res) { console.debug('embeddingModelUpdateHandler:', res); if (res.status === true) { toast.success($i18n.t('Embedding model set to "{{embedding_model}}"', res), { duration: 1000 * 10 }); } } }; const submitHandler = async () => { if ( RAGConfig.CONTENT_EXTRACTION_ENGINE === 'external' && RAGConfig.EXTERNAL_DOCUMENT_LOADER_URL === '' ) { toast.error($i18n.t('External Document Loader URL required.')); return; } if (RAGConfig.CONTENT_EXTRACTION_ENGINE === 'tika' && RAGConfig.TIKA_SERVER_URL === '') { toast.error($i18n.t('Tika Server URL required.')); return; } if (RAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling' && RAGConfig.DOCLING_SERVER_URL === '') { toast.error($i18n.t('Docling Server URL required.')); return; } if ( RAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling' && ((RAGConfig.DOCLING_OCR_ENGINE === '' && RAGConfig.DOCLING_OCR_LANG !== '') || (RAGConfig.DOCLING_OCR_ENGINE !== '' && RAGConfig.DOCLING_OCR_LANG === '')) ) { toast.error( $i18n.t('Both Docling OCR Engine and Language(s) must be provided or both left empty.') ); return; } if ( RAGConfig.CONTENT_EXTRACTION_ENGINE === 'datalab_marker' && !RAGConfig.DATALAB_MARKER_API_KEY ) { toast.error($i18n.t('Datalab Marker API Key required.')); return; } if ( RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence' && (RAGConfig.DOCUMENT_INTELLIGENCE_ENDPOINT === '' || RAGConfig.DOCUMENT_INTELLIGENCE_KEY === '') ) { toast.error($i18n.t('Document Intelligence endpoint and key required.')); return; } if ( RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mistral_ocr' && RAGConfig.MISTRAL_OCR_API_KEY === '' ) { toast.error($i18n.t('Mistral OCR API Key required.')); return; } if (!RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL) { await embeddingModelUpdateHandler(); } const res = await updateRAGConfig(localStorage.token, { ...RAGConfig, ALLOWED_FILE_EXTENSIONS: RAGConfig.ALLOWED_FILE_EXTENSIONS.split(',') .map((ext) => ext.trim()) .filter((ext) => ext !== ''), DATALAB_MARKER_LANGS: RAGConfig.DATALAB_MARKER_LANGS.split(',') .map((code) => code.trim()) .filter((code) => code !== '') .join(', '), DOCLING_PICTURE_DESCRIPTION_LOCAL: JSON.parse( RAGConfig.DOCLING_PICTURE_DESCRIPTION_LOCAL || '{}' ), DOCLING_PICTURE_DESCRIPTION_API: JSON.parse(RAGConfig.DOCLING_PICTURE_DESCRIPTION_API || '{}') }); dispatch('save'); }; const setEmbeddingConfig = async () => { const embeddingConfig = await getEmbeddingConfig(localStorage.token); if (embeddingConfig) { embeddingEngine = embeddingConfig.embedding_engine; embeddingModel = embeddingConfig.embedding_model; embeddingBatchSize = embeddingConfig.embedding_batch_size ?? 1; OpenAIKey = embeddingConfig.openai_config.key; OpenAIUrl = embeddingConfig.openai_config.url; OllamaKey = embeddingConfig.ollama_config.key; OllamaUrl = embeddingConfig.ollama_config.url; AzureOpenAIKey = embeddingConfig.azure_openai_config.key; AzureOpenAIUrl = embeddingConfig.azure_openai_config.url; AzureOpenAIVersion = embeddingConfig.azure_openai_config.version; } }; onMount(async () => { await setEmbeddingConfig(); const config = await getRAGConfig(localStorage.token); config.ALLOWED_FILE_EXTENSIONS = (config?.ALLOWED_FILE_EXTENSIONS ?? []).join(', '); config.DOCLING_PICTURE_DESCRIPTION_LOCAL = JSON.stringify( config.DOCLING_PICTURE_DESCRIPTION_LOCAL ?? {}, null, 2 ); config.DOCLING_PICTURE_DESCRIPTION_API = JSON.stringify( config.DOCLING_PICTURE_DESCRIPTION_API ?? {}, null, 2 ); RAGConfig = config; }); </script> <ResetUploadDirConfirmDialog bind:show={showResetUploadDirConfirm} on:confirm={async () => { const res = await deleteAllFiles(localStorage.token).catch((error) => { toast.error(`${error}`); return null; }); if (res) { toast.success($i18n.t('Success')); } }} /> <ResetVectorDBConfirmDialog bind:show={showResetConfirm} on:confirm={() => { const res = resetVectorDB(localStorage.token).catch((error) => { toast.error(`${error}`); return null; }); if (res) { toast.success($i18n.t('Success')); } }} /> <ReindexKnowledgeFilesConfirmDialog bind:show={showReindexConfirm} on:confirm={async () => { const res = await reindexKnowledgeFiles(localStorage.token).catch((error) => { toast.error(`${error}`); return null; }); if (res) { toast.success($i18n.t('Success')); } }} /> <form class="flex flex-col h-full justify-between space-y-3 text-sm" on:submit|preventDefault={() => { submitHandler(); }} > {#if RAGConfig} <div class=" space-y-2.5 overflow-y-scroll scrollbar-hidden h-full pr-1.5"> <div class=""> <div class="mb-3"> <div class=" mb-2.5 text-base font-medium">{$i18n.t('General')}</div> <hr class=" border-gray-100 dark:border-gray-850 my-2" /> <div class="mb-2.5 flex flex-col w-full justify-between"> <div class="flex w-full justify-between mb-1"> <div class="self-center text-xs font-medium"> {$i18n.t('Content Extraction Engine')} </div> <div class=""> <select class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right" bind:value={RAGConfig.CONTENT_EXTRACTION_ENGINE} > <option value="">{$i18n.t('Default')}</option> <option value="external">{$i18n.t('External')}</option> <option value="tika">{$i18n.t('Tika')}</option> <option value="docling">{$i18n.t('Docling')}</option> <option value="datalab_marker">{$i18n.t('Datalab Marker API')}</option> <option value="document_intelligence">{$i18n.t('Document Intelligence')}</option> <option value="mistral_ocr">{$i18n.t('Mistral OCR')}</option> </select> </div> </div> {#if RAGConfig.CONTENT_EXTRACTION_ENGINE === ''} <div class="flex w-full mt-1"> <div class="flex-1 flex justify-between"> <div class=" self-center text-xs font-medium"> {$i18n.t('PDF Extract Images (OCR)')} </div> <div class="flex items-center relative"> <Switch bind:state={RAGConfig.PDF_EXTRACT_IMAGES} /> </div> </div> </div> {:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'datalab_marker'} <div class="my-0.5 flex gap-2 pr-2"> <SensitiveInput placeholder={$i18n.t('Enter Datalab Marker API Key')} required={false} bind:value={RAGConfig.DATALAB_MARKER_API_KEY} /> </div> <div class="flex justify-between w-full mt-2"> <div class="text-xs font-medium"> {$i18n.t('Languages')} </div> <input class="text-sm bg-transparent outline-hidden" type="text" bind:value={RAGConfig.DATALAB_MARKER_LANGS} placeholder={$i18n.t('e.g.) en,fr,de')} /> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t( 'Significantly improves accuracy by using an LLM to enhance tables, forms, inline math, and layout detection. Will increase latency. Defaults to True.' )} placement="top-start" > {$i18n.t('Use LLM')} </Tooltip> </div> <div class="flex items-center"> <Switch bind:state={RAGConfig.DATALAB_MARKER_USE_LLM} /> </div> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t('Skip the cache and re-run the inference. Defaults to False.')} placement="top-start" > {$i18n.t('Skip Cache')} </Tooltip> </div> <div class="flex items-center"> <Switch bind:state={RAGConfig.DATALAB_MARKER_SKIP_CACHE} /> </div> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t( 'Force OCR on all pages of the PDF. This can lead to worse results if you have good text in your PDFs. Defaults to False.' )} placement="top-start" > {$i18n.t('Force OCR')} </Tooltip> </div> <div class="flex items-center"> <Switch bind:state={RAGConfig.DATALAB_MARKER_FORCE_OCR} /> </div> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t( 'Whether to paginate the output. Each page will be separated by a horizontal rule and page number. Defaults to False.' )} placement="top-start" > {$i18n.t('Paginate')} </Tooltip> </div> <div class="flex items-center"> <Switch bind:state={RAGConfig.DATALAB_MARKER_PAGINATE} /> </div> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t( 'Strip existing OCR text from the PDF and re-run OCR. Ignored if Force OCR is enabled. Defaults to False.' )} placement="top-start" > {$i18n.t('Strip Existing OCR')} </Tooltip> </div> <div class="flex items-center"> <Switch bind:state={RAGConfig.DATALAB_MARKER_STRIP_EXISTING_OCR} /> </div> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t( 'Disable image extraction from the PDF. If Use LLM is enabled, images will be automatically captioned. Defaults to False.' )} placement="top-start" > {$i18n.t('Disable Image Extraction')} </Tooltip> </div> <div class="flex items-center"> <Switch bind:state={RAGConfig.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION} /> </div> </div> <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={$i18n.t( "The output format for the text. Can be 'json', 'markdown', or 'html'. Defaults to 'markdown'." )} placement="top-start" > {$i18n.t('Output Format')} </Tooltip> </div> <div class=""> <select class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right" bind:value={RAGConfig.DATALAB_MARKER_OUTPUT_FORMAT} > <option value="markdown">{$i18n.t('Markdown')}</option> <option value="json">{$i18n.t('JSON')}</option> <option value="html">{$i18n.t('HTML')}</option> </select> </div> </div> {:else if RAGConfig.CONTENT_EXTRACTION_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={$i18n.t('Enter External Document Loader URL')} bind:value={RAGConfig.EXTERNAL_DOCUMENT_LOADER_URL} /> <SensitiveInput placeholder={$i18n.t('Enter External Document Loader API Key')} required={false} bind:value={RAGConfig.EXTERNAL_DOCUMENT_LOADER_API_KEY} /> </div> {:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'tika'} <div class="flex w-full mt-1"> <div class="flex-1 mr-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Enter Tika Server URL')} bind:value={RAGConfig.TIKA_SERVER_URL} /> </div> </div> {:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling'} <div class="flex w-full mt-1"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Enter Docling Server URL')} bind:value={RAGConfig.DOCLING_SERVER_URL} /> </div> <div class="flex w-full mt-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Enter Docling OCR Engine')} bind:value={RAGConfig.DOCLING_OCR_ENGINE} /> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Enter Docling OCR Language(s)')} bind:value={RAGConfig.DOCLING_OCR_LANG} /> </div> <div class="flex w-full mt-2"> <div class="flex-1 flex justify-between"> <div class=" self-center text-xs font-medium"> {$i18n.t('Describe Pictures in Documents')} </div> <div class="flex items-center relative"> <Switch bind:state={RAGConfig.DOCLING_DO_PICTURE_DESCRIPTION} /> </div> </div> </div> {#if RAGConfig.DOCLING_DO_PICTURE_DESCRIPTION} <div class="flex justify-between w-full mt-2"> <div class="self-center text-xs font-medium"> <Tooltip content={''} placement="top-start"> {$i18n.t('Picture Description Mode')} </Tooltip> </div> <div class=""> <select class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right" bind:value={RAGConfig.DOCLING_PICTURE_DESCRIPTION_MODE} > <option value="">{$i18n.t('Default')}</option> <option value="local">{$i18n.t('Local')}</option> <option value="api">{$i18n.t('API')}</option> </select> </div> </div> {#if RAGConfig.DOCLING_PICTURE_DESCRIPTION_MODE === 'local'} <div class="flex flex-col gap-2 mt-2"> <div class=" flex flex-col w-full justify-between"> <div class=" mb-1 text-xs font-medium"> {$i18n.t('Picture Description Local Config')} </div> <div class="flex w-full items-center relative"> <Tooltip content={$i18n.t( 'Options for running a local vision-language model in the picture description. The parameters refer to a model hosted on Hugging Face. This parameter is mutually exclusive with picture_description_api.' )} placement="top-start" className="w-full" > <Textarea bind:value={RAGConfig.DOCLING_PICTURE_DESCRIPTION_LOCAL} placeholder={$i18n.t('Enter Config in JSON format')} /> </Tooltip> </div> </div> </div> {:else if RAGConfig.DOCLING_PICTURE_DESCRIPTION_MODE === 'api'} <div class="flex flex-col gap-2 mt-2"> <div class=" flex flex-col w-full justify-between"> <div class=" mb-1 text-xs font-medium"> {$i18n.t('Picture Description API Config')} </div> <div class="flex w-full items-center relative"> <Tooltip content={$i18n.t( 'API details for using a vision-language model in the picture description. This parameter is mutually exclusive with picture_description_local.' )} placement="top-start" className="w-full" > <Textarea bind:value={RAGConfig.DOCLING_PICTURE_DESCRIPTION_API} placeholder={$i18n.t('Enter Config in JSON format')} /> </Tooltip> </div> </div> </div> {/if} {/if} {:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence'} <div class="my-0.5 flex gap-2 pr-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Enter Document Intelligence Endpoint')} bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_ENDPOINT} /> <SensitiveInput placeholder={$i18n.t('Enter Document Intelligence Key')} bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_KEY} /> </div> {:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mistral_ocr'} <div class="my-0.5 flex gap-2 pr-2"> <SensitiveInput placeholder={$i18n.t('Enter Mistral API Key')} bind:value={RAGConfig.MISTRAL_OCR_API_KEY} /> </div> {/if} </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium"> <Tooltip content={$i18n.t('Full Context Mode')} placement="top-start"> {$i18n.t('Bypass Embedding and Retrieval')} </Tooltip> </div> <div class="flex items-center relative"> <Tooltip content={RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL ? $i18n.t( 'Inject the entire content as context for comprehensive processing, this is recommended for complex queries.' ) : $i18n.t( 'Default to segmented retrieval for focused and relevant content extraction, this is recommended for most cases.' )} > <Switch bind:state={RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL} /> </Tooltip> </div> </div> {#if !RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL} <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Text Splitter')}</div> <div class="flex items-center relative"> <select class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right" bind:value={RAGConfig.TEXT_SPLITTER} > <option value="">{$i18n.t('Default')} ({$i18n.t('Character')})</option> <option value="token">{$i18n.t('Token')} ({$i18n.t('Tiktoken')})</option> <option value="markdown_header">{$i18n.t('Markdown (Header)')}</option> </select> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" flex gap-1.5 w-full"> <div class=" w-full justify-between"> <div class="self-center text-xs font-medium min-w-fit mb-1"> {$i18n.t('Chunk Size')} </div> <div class="self-center"> <input 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" type="number" placeholder={$i18n.t('Enter Chunk Size')} bind:value={RAGConfig.CHUNK_SIZE} autocomplete="off" min="0" /> </div> </div> <div class="w-full"> <div class=" self-center text-xs font-medium min-w-fit mb-1"> {$i18n.t('Chunk Overlap')} </div> <div class="self-center"> <input 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" type="number" placeholder={$i18n.t('Enter Chunk Overlap')} bind:value={RAGConfig.CHUNK_OVERLAP} autocomplete="off" min="0" /> </div> </div> </div> </div> {/if} </div> {#if !RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL} <div class="mb-3"> <div class=" mb-2.5 text-base font-medium">{$i18n.t('Embedding')}</div> <hr class=" border-gray-100 dark:border-gray-850 my-2" /> <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"> {$i18n.t('Embedding Model Engine')} </div> <div class="flex items-center relative"> <select class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 p-1 text-xs bg-transparent outline-hidden text-right" bind:value={embeddingEngine} placeholder="Select an embedding model engine" on:change={(e) => { if (e.target.value === 'ollama') { embeddingModel = ''; } else if (e.target.value === 'openai') { embeddingModel = 'text-embedding-3-small'; } else if (e.target.value === 'azure_openai') { embeddingModel = 'text-embedding-3-small'; } else if (e.target.value === '') { embeddingModel = 'sentence-transformers/all-MiniLM-L6-v2'; } }} > <option value="">{$i18n.t('Default (SentenceTransformers)')}</option> <option value="ollama">{$i18n.t('Ollama')}</option> <option value="openai">{$i18n.t('OpenAI')}</option> <option value="azure_openai">Azure OpenAI</option> </select> </div> </div> {#if embeddingEngine === 'openai'} <div class="my-0.5 flex gap-2 pr-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('API Base URL')} bind:value={OpenAIUrl} required /> <SensitiveInput placeholder={$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 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> {:else if embeddingEngine === 'azure_openai'} <div class="my-0.5 flex flex-col gap-2 pr-2 w-full"> <div class="flex gap-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('API Base URL')} bind:value={AzureOpenAIUrl} required /> <SensitiveInput placeholder={$i18n.t('API Key')} bind:value={AzureOpenAIKey} /> </div> <div class="flex gap-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder="Version" bind:value={AzureOpenAIVersion} required /> </div> </div> {/if} </div> <div class=" mb-2.5 flex flex-col w-full"> <div class=" mb-1 text-xs font-medium">{$i18n.t('Embedding Model')}</div> <div class=""> {#if embeddingEngine === 'ollama'} <div class="flex w-full"> <div class="flex-1 mr-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" bind:value={embeddingModel} placeholder={$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 text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Set embedding model (e.g. {{model}})', { model: embeddingModel.slice(-40) })} bind:value={embeddingModel} /> </div> {#if embeddingEngine === ''} <button class="px-2.5 bg-transparent text-gray-800 dark:bg-transparent dark:text-gray-100 rounded-lg transition" on:click={() => { embeddingModelUpdateHandler(); }} disabled={updateEmbeddingModelLoading} > {#if updateEmbeddingModelLoading} <div class="self-center"> <svg class=" w-4 h-4" viewBox="0 0 24 24" fill="currentColor" xmlns="http://www.w3.org/2000/svg" > <style> .spinner_ajPY { transform-origin: center; animation: spinner_AtaB 0.75s infinite linear; } @keyframes spinner_AtaB { 100% { transform: rotate(360deg); } } </style> <path d="M12,1A11,11,0,1,0,23,12,11,11,0,0,0,12,1Zm0,19a8,8,0,1,1,8-8A8,8,0,0,1,12,20Z" opacity=".25" /> <path d="M10.14,1.16a11,11,0,0,0-9,8.92A1.59,1.59,0,0,0,2.46,12,1.52,1.52,0,0,0,4.11,10.7a8,8,0,0,1,6.66-6.61A1.42,1.42,0,0,0,12,2.69h0A1.57,1.57,0,0,0,10.14,1.16Z" class="spinner_ajPY" /> </svg> </div> {:else} <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" fill="currentColor" class="w-4 h-4" > <path d="M8.75 2.75a.75.75 0 0 0-1.5 0v5.69L5.03 6.22a.75.75 0 0 0-1.06 1.06l3.5 3.5a.75.75 0 0 0 1.06 0l3.5-3.5a.75.75 0 0 0-1.06-1.06L8.75 8.44V2.75Z" /> <path d="M3.5 9.75a.75.75 0 0 0-1.5 0v1.5A2.75 2.75 0 0 0 4.75 14h6.5A2.75 2.75 0 0 0 14 11.25v-1.5a.75.75 0 0 0-1.5 0v1.5c0 .69-.56 1.25-1.25 1.25h-6.5c-.69 0-1.25-.56-1.25-1.25v-1.5Z" /> </svg> {/if} </button> {/if} </div> {/if} </div> <div class="mt-1 mb-1 text-xs text-gray-400 dark:text-gray-500"> {$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' || embeddingEngine === 'azure_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} /> </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> <div class=""> <div class="flex w-full"> <div class="flex-1 mr-2"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" placeholder={$i18n.t('Set reranking model (e.g. {{model}})', { model: 'BAAI/bge-reranker-v2-m3' })} bind:value={RAGConfig.RAG_RERANKING_MODEL} /> </div> </div> </div> </div> {/if} <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Top K')}</div> <div class="flex items-center relative"> <input class="flex-1 w-full 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 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 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"> {$i18n.t( 'Note: If you set a minimum score, the search will only return documents with a score greater than or equal to the minimum score.' )} </div> </div> {/if} {#if RAGConfig.ENABLE_RAG_HYBRID_SEARCH === true} <div class="mb-2.5 flex w-full justify-between"> <div class="self-center text-xs font-medium"> {$i18n.t('Weight of BM25 Retrieval')} </div> <div class="flex items-center relative"> <input class="flex-1 w-full text-sm bg-transparent outline-hidden" type="number" step="0.01" placeholder={$i18n.t('Enter BM25 Weight')} bind:value={RAGConfig.HYBRID_BM25_WEIGHT} autocomplete="off" min="0.0" max="1.0" /> </div> </div> {/if} {/if} <div class=" mb-2.5 flex flex-col w-full justify-between"> <div class=" mb-1 text-xs font-medium">{$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} <div class="mb-3"> <div class=" mb-2.5 text-base font-medium">{$i18n.t('Files')}</div> <hr class=" border-gray-100 dark:border-gray-850 my-2" /> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Allowed File Extensions')}</div> <div class="flex items-center relative"> <Tooltip content={$i18n.t( 'Allowed file extensions for upload. Separate multiple extensions with commas. Leave empty for all file types.' )} placement="top-start" > <input class="flex-1 w-full text-sm bg-transparent outline-hidden" type="text" placeholder={$i18n.t('e.g. pdf, docx, txt')} bind:value={RAGConfig.ALLOWED_FILE_EXTENSIONS} autocomplete="off" /> </Tooltip> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Max Upload Size')}</div> <div class="flex items-center relative"> <Tooltip content={$i18n.t( 'The maximum file size in MB. If the file size exceeds this limit, the file will not be uploaded.' )} placement="top-start" > <input class="flex-1 w-full text-sm bg-transparent outline-hidden" type="number" placeholder={$i18n.t('Leave empty for unlimited')} bind:value={RAGConfig.FILE_MAX_SIZE} autocomplete="off" min="0" /> </Tooltip> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Max Upload Count')}</div> <div class="flex items-center relative"> <Tooltip content={$i18n.t( 'The maximum number of files that can be used at once in chat. If the number of files exceeds this limit, the files will not be uploaded.' )} placement="top-start" > <input class="flex-1 w-full text-sm bg-transparent outline-hidden" type="number" placeholder={$i18n.t('Leave empty for unlimited')} bind:value={RAGConfig.FILE_MAX_COUNT} autocomplete="off" min="0" /> </Tooltip> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Image Compression Width')}</div> <div class="flex items-center relative"> <Tooltip content={$i18n.t( 'The width in pixels to compress images to. Leave empty for no compression.' )} placement="top-start" > <input class="flex-1 w-full text-sm bg-transparent outline-hidden" type="number" placeholder={$i18n.t('Leave empty for no compression')} bind:value={RAGConfig.FILE_IMAGE_COMPRESSION_WIDTH} autocomplete="off" min="0" /> </Tooltip> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium"> {$i18n.t('Image Compression Height')} </div> <div class="flex items-center relative"> <Tooltip content={$i18n.t( 'The height in pixels to compress images to. Leave empty for no compression.' )} placement="top-start" > <input class="flex-1 w-full text-sm bg-transparent outline-hidden" type="number" placeholder={$i18n.t('Leave empty for no compression')} bind:value={RAGConfig.FILE_IMAGE_COMPRESSION_HEIGHT} autocomplete="off" min="0" /> </Tooltip> </div> </div> </div> <div class="mb-3"> <div class=" mb-2.5 text-base font-medium">{$i18n.t('Integration')}</div> <hr class=" border-gray-100 dark:border-gray-850 my-2" /> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('Google Drive')}</div> <div class="flex items-center relative"> <Switch bind:state={RAGConfig.ENABLE_GOOGLE_DRIVE_INTEGRATION} /> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium">{$i18n.t('OneDrive')}</div> <div class="flex items-center relative"> <Switch bind:state={RAGConfig.ENABLE_ONEDRIVE_INTEGRATION} /> </div> </div> </div> <div class="mb-3"> <div class=" mb-2.5 text-base font-medium">{$i18n.t('Danger Zone')}</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">{$i18n.t('Reset Upload Directory')}</div> <div class="flex items-center relative"> <button class="text-xs" on:click={() => { showResetUploadDirConfirm = true; }} > {$i18n.t('Reset')} </button> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium"> {$i18n.t('Reset Vector Storage/Knowledge')} </div> <div class="flex items-center relative"> <button class="text-xs" on:click={() => { showResetConfirm = true; }} > {$i18n.t('Reset')} </button> </div> </div> <div class=" mb-2.5 flex w-full justify-between"> <div class=" self-center text-xs font-medium"> {$i18n.t('Reindex Knowledge Base Vectors')} </div> <div class="flex items-center relative"> <button class="text-xs" on:click={() => { showReindexConfirm = true; }} > {$i18n.t('Reindex')} </button> </div> </div> </div> </div> </div> <div class="flex justify-end pt-3 text-sm font-medium"> <button class="px-3.5 py-1.5 text-sm font-medium bg-black hover:bg-gray-900 text-white dark:bg-white dark:text-black dark:hover:bg-gray-100 transition rounded-full" type="submit" > {$i18n.t('Save')} </button> </div> {:else} <div class="flex items-center justify-center h-full"> <Spinner /> </div> {/if} </form>