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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 RAG_EMBEDDING_ENGINE = '';
let RAG_EMBEDDING_MODEL = '';
let RAG_EMBEDDING_BATCH_SIZE = 1;
let ENABLE_ASYNC_EMBEDDING = true;
let RAG_EMBEDDING_CONCURRENT_REQUESTS = 0;
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 (RAG_EMBEDDING_ENGINE === '' && RAG_EMBEDDING_MODEL.split('/').length - 1 > 1) {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (RAG_EMBEDDING_ENGINE === 'ollama' && RAG_EMBEDDING_MODEL === '') {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (RAG_EMBEDDING_ENGINE === 'openai' && RAG_EMBEDDING_MODEL === '') {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (
RAG_EMBEDDING_ENGINE === 'azure_openai' &&
(AzureOpenAIKey === '' || AzureOpenAIUrl === '' || AzureOpenAIVersion === '')
) {
toast.error($i18n.t('OpenAI URL/Key required.'));
return;
}
console.debug('Update embedding model attempt:', {
RAG_EMBEDDING_ENGINE,
RAG_EMBEDDING_MODEL,
RAG_EMBEDDING_BATCH_SIZE,
ENABLE_ASYNC_EMBEDDING,
RAG_EMBEDDING_CONCURRENT_REQUESTS
});
updateEmbeddingModelLoading = true;
const res = await updateEmbeddingConfig(localStorage.token, {
RAG_EMBEDDING_ENGINE: RAG_EMBEDDING_ENGINE,
RAG_EMBEDDING_MODEL: RAG_EMBEDDING_MODEL,
RAG_EMBEDDING_BATCH_SIZE: RAG_EMBEDDING_BATCH_SIZE,
ENABLE_ASYNC_EMBEDDING: ENABLE_ASYNC_EMBEDDING,
RAG_EMBEDDING_CONCURRENT_REQUESTS: RAG_EMBEDDING_CONCURRENT_REQUESTS,
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(`${error}`);
await setEmbeddingConfig();
return null;
});
updateEmbeddingModelLoading = false;
if (res) {
console.debug('embeddingModelUpdateHandler:', res);
}
};
const submitHandler = async () => {
if (
RAGConfig.CONTENT_EXTRACTION_ENGINE === 'external' &&
RAGConfig.EXTERNAL_DOCUMENT_LOADER_URL === ''
) {
toast.error($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 === 'datalab_marker' &&
RAGConfig.DATALAB_MARKER_ADDITIONAL_CONFIG &&
RAGConfig.DATALAB_MARKER_ADDITIONAL_CONFIG.trim() !== ''
) {
try {
JSON.parse(RAGConfig.DATALAB_MARKER_ADDITIONAL_CONFIG);
} catch (e) {
toast.error($i18n.t('Invalid JSON format in Additional Config'));
return;
}
}
if (
RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence' &&
RAGConfig.DOCUMENT_INTELLIGENCE_ENDPOINT === ''
) {
toast.error($i18n.t('Document Intelligence endpoint required.'));
return;
}
if (
RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mistral_ocr' &&
RAGConfig.MISTRAL_OCR_API_KEY === ''
) {
toast.error($i18n.t('Mistral OCR API Key required.'));
return;
}
if (
RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mineru' &&
RAGConfig.MINERU_API_MODE === 'cloud' &&
RAGConfig.MINERU_API_KEY === ''
) {
toast.error($i18n.t('MinerU API Key required for Cloud API mode.'));
return;
}
if (!RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL) {
await embeddingModelUpdateHandler();
}
if (RAGConfig.DOCLING_PARAMS) {
try {
JSON.parse(RAGConfig.DOCLING_PARAMS);
} catch (e) {
toast.error(
$i18n.t('Invalid JSON format in {{NAME}}', {
NAME: $i18n.t('Docling Parameters')
})
);
return;
}
}
if (RAGConfig.MINERU_PARAMS) {
try {
JSON.parse(RAGConfig.MINERU_PARAMS);
} catch (e) {
toast.error($i18n.t('Invalid JSON format in MinerU Parameters'));
return;
}
}
const res = await updateRAGConfig(localStorage.token, {
...RAGConfig,
ALLOWED_FILE_EXTENSIONS: RAGConfig.ALLOWED_FILE_EXTENSIONS.split(',')
.map((ext) => ext.trim())
.filter((ext) => ext !== ''),
DOCLING_PARAMS:
typeof RAGConfig.DOCLING_PARAMS === 'string' && RAGConfig.DOCLING_PARAMS.trim() !== ''
? JSON.parse(RAGConfig.DOCLING_PARAMS)
: {},
MINERU_PARAMS:
typeof RAGConfig.MINERU_PARAMS === 'string' && RAGConfig.MINERU_PARAMS.trim() !== ''
? JSON.parse(RAGConfig.MINERU_PARAMS)
: {}
});
dispatch('save');
};
const setEmbeddingConfig = async () => {
const embeddingConfig = await getEmbeddingConfig(localStorage.token);
if (embeddingConfig) {
RAG_EMBEDDING_ENGINE = embeddingConfig.RAG_EMBEDDING_ENGINE;
RAG_EMBEDDING_MODEL = embeddingConfig.RAG_EMBEDDING_MODEL;
RAG_EMBEDDING_BATCH_SIZE = embeddingConfig.RAG_EMBEDDING_BATCH_SIZE ?? 1;
ENABLE_ASYNC_EMBEDDING = embeddingConfig.ENABLE_ASYNC_EMBEDDING ?? true;
RAG_EMBEDDING_CONCURRENT_REQUESTS = embeddingConfig.RAG_EMBEDDING_CONCURRENT_REQUESTS ?? 0;
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_PARAMS =
typeof config.DOCLING_PARAMS === 'object'
? JSON.stringify(config.DOCLING_PARAMS ?? {}, null, 2)
: config.DOCLING_PARAMS;
config.MINERU_PARAMS =
typeof config.MINERU_PARAMS === 'object'
? JSON.stringify(config.MINERU_PARAMS ?? {}, null, 2)
: config.MINERU_PARAMS;
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=" mt-0.5 mb-2.5 text-base font-medium">{$i18n.t('General')}</div>
<hr class=" border-gray-100/30 dark:border-gray-850/30 my-2" />
<div class="mb-2.5 flex flex-col w-full justify-between">
<div class="flex w-full justify-between mb-1">
<div class="self-center text-xs font-medium">
{$i18n.t('Content Extraction Engine')}
</div>
<div class="">
<select
class="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">{$i18n.t('Mistral OCR')}</option>
<option value="mineru">{$i18n.t('MinerU')}</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">
{$i18n.t('PDF Extract Images (OCR)')}
</div>
<div class="flex items-center relative">
<Switch bind:state={RAGConfig.PDF_EXTRACT_IMAGES} />
</div>
</div>
</div>
<div class="flex w-full mt-2">
<div class="flex-1 flex justify-between">
<div class=" self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
'Page mode creates one document per page. Single mode combines all pages into one document for better chunking across page boundaries.'
)}
placement="top-start"
>
{$i18n.t('PDF Loader Mode')}
</Tooltip>
</div>
<div class="">
<select
class="w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right"
bind:value={RAGConfig.PDF_LOADER_MODE}
>
<option value="page">{$i18n.t('Page')}</option>
<option value="single">{$i18n.t('Single')}</option>
</select>
</div>
</div>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'datalab_marker'}
<div class="my-0.5 flex gap-2 pr-2">
<Tooltip
content={$i18n.t(
'API Base URL for Datalab Marker service. Defaults to: https://www.datalab.to/api/v1/marker'
)}
placement="top-start"
className="w-full"
>
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('Enter Datalab Marker API Base URL')}
bind:value={RAGConfig.DATALAB_MARKER_API_BASE_URL}
/>
</Tooltip>
</div>
<div class="my-0.5 flex gap-2 pr-2">
<SensitiveInput
placeholder={$i18n.t('Enter Datalab Marker API Key')}
required={false}
bind:value={RAGConfig.DATALAB_MARKER_API_KEY}
/>
</div>
<div class="flex flex-col gap-2 mt-2">
<div class=" flex flex-col w-full justify-between">
<div class=" mb-1 text-xs font-medium">
{$i18n.t('Additional Config')}
</div>
<div class="flex w-full items-center relative">
<Tooltip
content={$i18n.t(
'Additional configuration options for marker. This should be a JSON string with key-value pairs. For example, \'{"key": "value"}\'. Supported keys include: disable_links, keep_pageheader_in_output, keep_pagefooter_in_output, filter_blank_pages, drop_repeated_text, layout_coverage_threshold, merge_threshold, height_tolerance, gap_threshold, image_threshold, min_line_length, level_count, default_level'
)}
placement="top-start"
className="w-full"
>
<Textarea
bind:value={RAGConfig.DATALAB_MARKER_ADDITIONAL_CONFIG}
placeholder={$i18n.t('Enter JSON config (e.g., {"disable_links": true})')}
/>
</Tooltip>
</div>
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
'Significantly improves accuracy by using an LLM to enhance tables, forms, inline math, and layout detection. Will increase latency. Defaults to False.'
)}
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(
'Format the lines in the output. Defaults to False. If set to True, the lines will be formatted to detect inline math and styles.'
)}
placement="top-start"
>
{$i18n.t('Format Lines')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={RAGConfig.DATALAB_MARKER_FORMAT_LINES} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
"The output format for the text. Can be 'json', 'markdown', or 'html'. Defaults to 'markdown'."
)}
placement="top-start"
>
{$i18n.t('Output Format')}
</Tooltip>
</div>
<div class="">
<select
class="w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right"
bind:value={RAGConfig.DATALAB_MARKER_OUTPUT_FORMAT}
>
<option value="markdown">{$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={$i18n.t('Enter Tika Server URL')}
bind:value={RAGConfig.TIKA_SERVER_URL}
/>
</div>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling'}
<div class="my-0.5 flex gap-2 pr-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('Enter Docling Server URL')}
bind:value={RAGConfig.DOCLING_SERVER_URL}
/>
<SensitiveInput
placeholder={$i18n.t('Enter Docling API Key')}
bind:value={RAGConfig.DOCLING_API_KEY}
required={false}
/>
</div>
<div class="flex flex-col gap-2 mt-2">
<div class=" flex flex-col w-full justify-between">
<div class=" mb-1 text-xs font-medium">
{$i18n.t('Parameters')}
</div>
<div class="flex w-full items-center relative">
<Textarea
bind:value={RAGConfig.DOCLING_PARAMS}
placeholder={$i18n.t('Enter additional parameters in JSON format')}
minSize={100}
/>
</div>
</div>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence'}
<div class="my-0.5 flex gap-2 pr-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('Enter Document Intelligence Endpoint')}
bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_ENDPOINT}
/>
<SensitiveInput
placeholder={$i18n.t('Enter Document Intelligence Key')}
bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_KEY}
required={false}
/>
</div>
<div class="my-0.5 flex flex-col w-full">
<div class=" mb-1 text-xs font-medium">
{$i18n.t('Document Intelligence Model')}
</div>
<div class="flex w-full">
<div class="flex-1 mr-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('Enter Document Intelligence Model')}
bind:value={RAGConfig.DOCUMENT_INTELLIGENCE_MODEL}
/>
</div>
</div>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mistral_ocr'}
<div class="my-0.5 flex gap-2 pr-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('Enter Mistral API Base URL')}
bind:value={RAGConfig.MISTRAL_OCR_API_BASE_URL}
/>
<SensitiveInput
placeholder={$i18n.t('Enter Mistral API Key')}
bind:value={RAGConfig.MISTRAL_OCR_API_KEY}
/>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'mineru'}
<!-- API Mode Selection -->
<div class="flex w-full mt-2">
<div class="flex-1 flex justify-between">
<div class="self-center text-xs font-medium">
{$i18n.t('API Mode')}
</div>
<select
class="w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden"
bind:value={RAGConfig.MINERU_API_MODE}
on:change={() => {
// Auto-update URL when switching modes if it's empty or matches the opposite mode's default
const cloudUrl = 'https://mineru.net/api/v4';
const localUrl = 'http://localhost:8000';
if (RAGConfig.MINERU_API_MODE === 'cloud') {
if (!RAGConfig.MINERU_API_URL || RAGConfig.MINERU_API_URL === localUrl) {
RAGConfig.MINERU_API_URL = cloudUrl;
}
} else {
if (!RAGConfig.MINERU_API_URL || RAGConfig.MINERU_API_URL === cloudUrl) {
RAGConfig.MINERU_API_URL = localUrl;
}
}
}}
>
<option value="local">{$i18n.t('local')}</option>
<option value="cloud">{$i18n.t('cloud')}</option>
</select>
</div>
</div>
<!-- API URL -->
<div class="flex w-full mt-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={RAGConfig.MINERU_API_MODE === 'cloud'
? $i18n.t('https://mineru.net/api/v4')
: $i18n.t('http://localhost:8000')}
bind:value={RAGConfig.MINERU_API_URL}
/>
</div>
<div class="flex w-full mt-2">
<SensitiveInput
placeholder={$i18n.t('Enter MinerU API Key')}
bind:value={RAGConfig.MINERU_API_KEY}
/>
</div>
<div class="flex w-full mt-2">
<div class="flex-1 flex justify-between">
<div class="self-center text-xs font-medium">
{$i18n.t('API Timeout')}
</div>
<input
class="w-16 text-sm bg-transparent outline-hidden text-right"
type="number"
min="1"
bind:value={RAGConfig.MINERU_API_TIMEOUT}
placeholder="60"
/>
</div>
</div>
<!-- Parameters -->
<div class="flex flex-col justify-between w-full mt-2">
<div class="text-xs font-medium">
<Tooltip
content={$i18n.t(
'Advanced parameters for MinerU parsing (enable_ocr, enable_formula, enable_table, language, model_version, page_ranges)'
)}
placement="top-start"
>
{$i18n.t('Parameters')}
</Tooltip>
</div>
<div class="mt-1.5">
<Textarea
bind:value={RAGConfig.MINERU_PARAMS}
placeholder={`{\n "enable_ocr": false,\n "enable_formula": true,\n "enable_table": true,\n "language": "en",\n "model_version": "pipeline",\n "page_ranges": ""\n}`}
minSize={100}
/>
</div>
</div>
{/if}
</div>
<div class=" mb-2.5 flex w-full justify-between">
<div class=" self-center text-xs font-medium">
<Tooltip content={$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="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=" self-center text-xs font-medium">
<Tooltip
placement="top-start"
content={$i18n.t(
'Split documents by markdown headers before applying character/token splitting.'
)}
>
{$i18n.t('Markdown Header Text Splitter')}
</Tooltip>
</div>
<div class="flex items-center relative">
<Switch bind:state={RAGConfig.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER} />
</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 RAGConfig.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER}
<div class=" mb-2.5 flex w-full justify-between">
<div class=" flex gap-1.5 w-full">
<div class="w-full">
<div class="self-center text-xs font-medium min-w-fit mb-1">
<Tooltip
placement="top-start"
content={$i18n.t(
'Chunks smaller than this threshold will be merged with neighboring chunks when possible. Set to 0 to disable merging.'
)}
>
{$i18n.t('Chunk Min Size Target')}
</Tooltip>
</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={$i18n.t('Enter Chunk Min Size Target')}
bind:value={RAGConfig.CHUNK_MIN_SIZE_TARGET}
autocomplete="off"
min="0"
/>
</div>
</div>
</div>
</div>
{/if}
{/if}
</div>
{#if !RAGConfig.BYPASS_EMBEDDING_AND_RETRIEVAL}
<div class="mb-3">
<div class=" mt-0.5 mb-2.5 text-base font-medium">{$i18n.t('Embedding')}</div>
<hr class=" border-gray-100/30 dark:border-gray-850/30 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">
{$i18n.t('Embedding Model Engine')}
</div>
<div class="flex items-center relative">
<select
class="w-fit pr-8 rounded-sm px-2 p-1 text-xs bg-transparent outline-hidden text-right"
bind:value={RAG_EMBEDDING_ENGINE}
placeholder={$i18n.t('Select an embedding model engine')}
on:change={(e) => {
if (e.target.value === 'ollama') {
RAG_EMBEDDING_MODEL = '';
} else if (e.target.value === 'openai') {
RAG_EMBEDDING_MODEL = 'text-embedding-3-small';
} else if (e.target.value === 'azure_openai') {
RAG_EMBEDDING_MODEL = 'text-embedding-3-small';
} else if (e.target.value === '') {
RAG_EMBEDDING_MODEL = 'sentence-transformers/all-MiniLM-L6-v2';
}
}}
>
<option value="">{$i18n.t('Default (SentenceTransformers)')}</option>
<option value="ollama">{$i18n.t('Ollama')}</option>
<option value="openai">{$i18n.t('OpenAI')}</option>
<option value="azure_openai">{$i18n.t('Azure OpenAI')}</option>
</select>
</div>
</div>
{#if RAG_EMBEDDING_ENGINE === '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}
required={false}
/>
</div>
{:else if RAG_EMBEDDING_ENGINE === '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 RAG_EMBEDDING_ENGINE === '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={$i18n.t('Version')}
bind:value={AzureOpenAIVersion}
required
/>
</div>
</div>
{/if}
</div>
<div class=" mb-2.5 flex flex-col w-full">
<div class=" mb-1 text-xs font-medium">{$i18n.t('Embedding Model')}</div>
<div class="">
{#if RAG_EMBEDDING_ENGINE === '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={RAG_EMBEDDING_MODEL}
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: RAG_EMBEDDING_MODEL.slice(-40)
})}
bind:value={RAG_EMBEDDING_MODEL}
/>
</div>
{#if RAG_EMBEDDING_ENGINE === ''}
<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">
<Spinner />
</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">
{$i18n.t(
'After updating or changing the embedding model, you must reindex the knowledge base for the changes to take effect. You can do this using the "Reindex" button below.'
)}
</div>
</div>
<div class=" mb-2.5 flex w-full justify-between">
<div class=" self-center text-xs font-medium">
{$i18n.t('Embedding Batch Size')}
</div>
<div class="">
<input
bind:value={RAG_EMBEDDING_BATCH_SIZE}
type="number"
class=" bg-transparent text-center w-14 outline-none"
min="-2"
max="16000"
step="1"
/>
</div>
</div>
{#if RAG_EMBEDDING_ENGINE === 'ollama' || RAG_EMBEDDING_ENGINE === 'openai' || RAG_EMBEDDING_ENGINE === 'azure_openai'}
<div class=" mb-2.5 flex w-full justify-between">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
'Runs embedding tasks concurrently to speed up processing. Turn off if rate limits become an issue.'
)}
placement="top-start"
>
{$i18n.t('Async Embedding Processing')}
</Tooltip>
</div>
<div class="flex items-center relative">
<Switch bind:state={ENABLE_ASYNC_EMBEDDING} />
</div>
</div>
<div class=" mb-2.5 flex w-full justify-between">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
'Limits the number of concurrent embedding requests. Set to 0 for unlimited.'
)}
placement="top-start"
>
{$i18n.t('Embedding Concurrent Requests')}
</Tooltip>
</div>
<div class="">
<input
bind:value={RAG_EMBEDDING_CONCURRENT_REQUESTS}
type="number"
class=" bg-transparent text-center w-14 outline-none"
min="0"
step="1"
/>
</div>
</div>
{/if}
</div>
<div class="mb-3">
<div class=" mt-0.5 mb-2.5 text-base font-medium">{$i18n.t('Retrieval')}</div>
<hr class=" border-gray-100/30 dark:border-gray-850/30 my-2" />
<div class=" mb-2.5 flex w-full justify-between">
<div class=" self-center text-xs font-medium">{$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 w-full justify-between">
<div class="self-center text-xs font-medium">
{$i18n.t('Enrich Hybrid Search Text')}
</div>
<div class="flex items-center relative">
<Tooltip
content={$i18n.t(
'Adds filenames, titles, sections, and snippets into the BM25 text to improve lexical recall.'
)}
>
<Switch bind:state={RAGConfig.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS} />
</Tooltip>
</div>
</div>
<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">
{$i18n.t('Reranking Engine')}
</div>
<div class="flex items-center relative">
<select
class="w-fit pr-8 rounded-sm px-2 p-1 text-xs bg-transparent outline-hidden text-right"
bind:value={RAGConfig.RAG_RERANKING_ENGINE}
placeholder={$i18n.t('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 py-0.5 w-full justify-between">
<Tooltip
content={$i18n.t(
'The Weight of BM25 Hybrid Search. 0 more semantic, 1 more lexical. Default 0.5'
)}
placement="top-start"
className="inline-tooltip"
>
<div class="flex w-full justify-between">
<div class=" self-center text-xs font-medium">
{$i18n.t('BM25 Weight')}
</div>
<button
class="p-1 px-3 text-xs flex rounded-sm transition shrink-0 outline-hidden"
type="button"
on:click={() => {
RAGConfig.HYBRID_BM25_WEIGHT =
(RAGConfig?.HYBRID_BM25_WEIGHT ?? null) === null ? 0.5 : null;
}}
>
{#if (RAGConfig?.HYBRID_BM25_WEIGHT ?? null) === null}
<span class="ml-2 self-center"> {$i18n.t('Default')} </span>
{:else}
<span class="ml-2 self-center"> {$i18n.t('Custom')} </span>
{/if}
</button>
</div>
</Tooltip>
{#if (RAGConfig?.HYBRID_BM25_WEIGHT ?? null) !== null}
<div class="flex mt-0.5 space-x-2">
<div class=" flex-1">
<input
id="steps-range"
type="range"
min="0"
max="1"
step="0.05"
bind:value={RAGConfig.HYBRID_BM25_WEIGHT}
class="w-full h-2 rounded-lg appearance-none cursor-pointer dark:bg-gray-700"
/>
<div class="py-0.5">
<div class="flex w-full justify-between">
<div class=" text-left text-xs font-small">
{$i18n.t('semantic')}
</div>
<div class=" text-right text-xs font-small">
{$i18n.t('lexical')}
</div>
</div>
</div>
</div>
<div>
<input
bind:value={RAGConfig.HYBRID_BM25_WEIGHT}
type="number"
class=" bg-transparent text-center w-14"
min="0"
max="1"
step="any"
/>
</div>
</div>
{/if}
</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={$i18n.t(
'Leave empty to use the default prompt, or enter a custom prompt'
)}
/>
</Tooltip>
</div>
</div>
</div>
{/if}
<div class="mb-3">
<div class=" mt-0.5 mb-2.5 text-base font-medium">{$i18n.t('Files')}</div>
<hr class=" border-gray-100/30 dark:border-gray-850/30 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={$i18n.t('Leave empty for no compression')}
bind:value={RAGConfig.FILE_IMAGE_COMPRESSION_HEIGHT}
autocomplete="off"
min="0"
/>
</Tooltip>
</div>
</div>
</div>
<div class="mb-3">
<div class=" mt-0.5 mb-2.5 text-base font-medium">{$i18n.t('Integration')}</div>
<hr class=" border-gray-100/30 dark:border-gray-850/30 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=" mt-0.5 mb-2.5 text-base font-medium">{$i18n.t('Danger Zone')}</div>
<hr class=" border-gray-100/30 dark:border-gray-850/30 my-2" />
<div class=" mb-2.5 flex w-full justify-between">
<div class=" self-center text-xs font-medium">{$i18n.t('Reset Upload Directory')}</div>
<div class="flex items-center relative">
<button
class="text-xs"
type="button"
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"
type="button"
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"
type="button"
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 className="size-5" />
</div>
{/if}
</form>
<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 RAG_EMBEDDING_ENGINE = '';
let RAG_EMBEDDING_MODEL = '';
let RAG_EMBEDDING_BATCH_SIZE = 1;
let ENABLE_ASYNC_EMBEDDING = true;
let RAG_EMBEDDING_CONCURRENT_REQUESTS = 0;
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 (RAG_EMBEDDING_ENGINE === '' && RAG_EMBEDDING_MODEL.split('/').length - 1 > 1) {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (RAG_EMBEDDING_ENGINE === 'ollama' && RAG_EMBEDDING_MODEL === '') {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (RAG_EMBEDDING_ENGINE === 'openai' && RAG_EMBEDDING_MODEL === '') {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (
RAG_EMBEDDING_ENGINE === 'azure_openai' &&
(AzureOpenAIKey === '' || AzureOpenAIUrl === '' || AzureOpenAIVersion === '')
) {
toast.error($i18n.t('OpenAI URL/Key required.'));