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<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();
}
RAGConfig.ALLOWED_FILE_EXTENSIONS = (RAGConfig?.ALLOWED_FILE_EXTENSIONS ?? '')
.split(',')
.map((ext) => ext.trim())
.filter((ext) => ext !== '');
RAGConfig.DATALAB_MARKER_LANGS = RAGConfig.DATALAB_MARKER_LANGS.split(',')
.map((code) => code.trim())
.filter((code) => code !== '')
.join(', ');
const res = await updateRAGConfig(localStorage.token, RAGConfig);
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(', ');
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">
{$i18n.t('Describe Pictures in Documents')}
</div>
<div class="flex items-center relative">
<Switch bind:state={RAGConfig.DOCLING_DO_PICTURE_DESCRIPTION} />
</div>
</div>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence'}
<div class="my-0.5 flex gap-2 pr-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$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>
</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}
on:change={() => {
submitHandler();
}}
/>
</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>
<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>
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