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Code Issues Actions 4 Packages Projects Releases Wiki Activity

Fix: Added azure openai and other new merges for individual rag config

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This commit is contained in:
weberm1 2025-06-06 12:08:45 +02:00
parent 5f43d42cfa
commit 03c27f1b2b
2 changed files with 432 additions and 14 deletions
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216
src/lib/components/workspace/Knowledge/CreateKnowledgeBase.svelte
View File

@ -42,6 +42,10 @@
let OpenAIUrl = '';
let OpenAIKey = '';
let AzureOpenAIUrl = '';
let AzureOpenAIKey = '';
let AzureOpenAIVersion = '';
let OllamaUrl = '';
let OllamaKey = '';
@ -85,7 +89,14 @@
return;
}
if ((embeddingEngine === 'openai' && OpenAIKey === '') || OpenAIUrl === '') {
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;
}
@ -105,6 +116,11 @@
key: OpenAIKey,
url: OpenAIUrl
},
azure_openai_config: {
key: AzureOpenAIKey,
url: AzureOpenAIUrl,
version: AzureOpenAIVersion
},
knowledge_id: knowledgeId
}).catch(async (error) => {
toast.error(`${error}`);
@ -135,6 +151,10 @@
OpenAIKey = embeddingConfig.openai_config.key;
OpenAIUrl = embeddingConfig.openai_config.url;
AzureOpenAIKey = embeddingConfig.azure_openai_config.key;
AzureOpenAIUrl = embeddingConfig.azure_openai_config.url;
AzureOpenAIVersion = embeddingConfig.azure_openai_config.version;
OllamaKey = embeddingConfig.ollama_config.key;
OllamaUrl = embeddingConfig.ollama_config.url;
}
@ -166,7 +186,24 @@
toast.error($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 === '' ||
@ -336,6 +373,7 @@
<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>
@ -353,6 +391,138 @@
</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
@ -500,6 +670,8 @@
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';
}
@ -508,6 +680,7 @@
<option value="">{$i18n.t('Default (SentenceTransformers)')}</option>
<option value="ollama">{$i18n.t('Ollama')}</option>
<option value="openai">{$i18n.t('OpenAI')}</option>
<option value="azure_openai">Azure OpenAI</option>
</select>
</div>
</div>
@ -538,6 +711,26 @@
required={false}
/>
</div>
{:else if embeddingEngine === 'azure_openai'}
<div class="my-0.5 flex flex-col gap-2 pr-2 w-full">
<div class="flex gap-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('API Base URL')}
bind:value={AzureOpenAIUrl}
required
/>
<SensitiveInput placeholder={$i18n.t('API Key')} bind:value={AzureOpenAIKey} />
</div>
<div class="flex gap-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder="Version"
bind:value={AzureOpenAIVersion}
required
/>
</div>
</div>
{/if}
</div>
@ -609,7 +802,7 @@
</div>
</div>
{#if embeddingEngine === 'ollama' || embeddingEngine === 'openai'}
{#if embeddingEngine === 'ollama' || embeddingEngine === 'openai' || embeddingEngine === 'azure_openai'}
<div class=" mb-2.5 flex w-full justify-between">
<div class=" self-center text-xs font-medium">
{$i18n.t('Embedding Batch Size')}
@ -819,6 +1012,25 @@
</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">

230
src/lib/components/workspace/common/RagConfigModal.svelte
View File

@ -45,6 +45,10 @@
let OpenAIUrl = RAGConfig.openai_config?.url || "";
let OpenAIKey = RAGConfig.openai_config?.key || "";
let AzureOpenAIUrl = RAGConfig.azure_openai_config?.url || "";
let AzureOpenAIKey = RAGConfig.azure_openai_config?.key || "";
let AzureOpenAIVersion = RAGConfig.azure_openai_config?.version || "";
let OllamaUrl = RAGConfig.ollama_config?.url || "";
let OllamaKey = RAGConfig.ollama_config?.key || "";
@ -61,6 +65,10 @@
OpenAIUrl = RAGConfig.openai_config?.url || "";
OpenAIKey = RAGConfig.openai_config?.key || "";
AzureOpenAIUrl = RAGConfig.azure_openai_config?.url || "";
AzureOpenAIKey = RAGConfig.azure_openai_config?.key || "";
AzureOpenAIVersion = RAGConfig.azure_openai_config?.version || "";
OllamaUrl = RAGConfig.ollama_config?.url || "";
OllamaKey = RAGConfig.ollama_config?.key || "";
needsReindex = false;
@ -101,10 +109,17 @@
return;
}
if ((embeddingEngine === 'openai' && OpenAIKey === '') || OpenAIUrl === '') {
toast.error($i18n.t('OpenAI URL/Key required.'));
return;
}
if (embeddingEngine === 'openai' && (OpenAIKey === '' || OpenAIUrl === '')) {
toast.error($i18n.t('OpenAI URL/Key required.'));
return;
}
if (
embeddingEngine === 'azure_openai' &&
(AzureOpenAIKey === '' || AzureOpenAIUrl === '' || AzureOpenAIVersion === '')
) {
toast.error($i18n.t('OpenAI URL/Key required.'));
return;
}
console.log('Update embedding model attempt:', embeddingModel);
@ -121,6 +136,11 @@
key: OpenAIKey,
url: OpenAIUrl
},
azure_openai_config: {
key: AzureOpenAIKey,
url: AzureOpenAIUrl,
version: AzureOpenAIVersion
},
knowledge_id: knowledgeId,
}).catch(async (error) => {
toast.error(`${error}`);
@ -151,6 +171,10 @@
OpenAIKey = embeddingConfig.openai_config.key;
OpenAIUrl = embeddingConfig.openai_config.url;
AzureOpenAIKey = embeddingConfig.azure_openai_config.key;
AzureOpenAIUrl = embeddingConfig.azure_openai_config.url;
AzureOpenAIVersion = embeddingConfig.azure_openai_config.version;
OllamaKey = embeddingConfig.ollama_config.key;
OllamaUrl = embeddingConfig.ollama_config.url;
}
@ -174,7 +198,7 @@
toast.error($i18n.t('Docling Server URL required.'));
return;
}
if (
if (
localRAGConfig.CONTENT_EXTRACTION_ENGINE === 'docling' &&
((localRAGConfig.DOCLING_OCR_ENGINE === '' && localRAGConfig.DOCLING_OCR_LANG !== '') ||
(localRAGConfig.DOCLING_OCR_ENGINE !== '' && localRAGConfig.DOCLING_OCR_LANG === ''))
@ -184,6 +208,13 @@
);
return;
}
if (
localRAGConfig.CONTENT_EXTRACTION_ENGINE === 'datalab_marker' &&
!localRAGConfig.DATALAB_MARKER_API_KEY
) {
toast.error($i18n.t('Datalab Marker API Key required.'));
return;
}
if (
localRAGConfig.CONTENT_EXTRACTION_ENGINE === 'document_intelligence' &&
@ -207,7 +238,8 @@
embedding_model,
embedding_batch_size,
openai_config,
ollama_config,
ollama_config,
azure_openai_config,
LOADED_EMBEDDING_MODELS,
DOWNLOADED_EMBEDDING_MODELS,
LOADED_RERANKING_MODELS,
@ -229,16 +261,15 @@
localRAGConfig.embedding_batch_size = embeddingBatchSize
localRAGConfig.openai_config = {"key": OpenAIKey, "url": OpenAIUrl}
localRAGConfig.ollama_config = {"key": OllamaKey, "url": OllamaUrl}
localRAGConfig.azure_openai_config = {"key": AzureOpenAIKey, "url": AzureOpenAIUrl, "version": AzureOpenAIVersion}
if (needsReindex) {
// Reindex knowledge files if reranking model changed
const reindexResponse = await reindexSpecificKnowledgeFiles(localStorage.token, knowledgeId,
);
if (reindexResponse.status === true) {
if (reindexResponse) {
toast.success($i18n.t('Knowledge files reindexed successfully.'));
} else {
toast.error($i18n.t('Failed to reindex knowledge files.'));
}
}
@ -290,6 +321,7 @@
<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>
@ -307,7 +339,139 @@
</div>
</div>
</div>
{:else if RAGConfig.CONTENT_EXTRACTION_ENGINE === 'external'}
{:else if localRAGConfig.CONTENT_EXTRACTION_ENGINE === 'datalab_marker'}
<div class="my-0.5 flex gap-2 pr-2">
<SensitiveInput
placeholder={$i18n.t('Enter Datalab Marker API Key')}
required={false}
bind:value={localRAGConfig.DATALAB_MARKER_API_KEY}
/>
</div>
<div class="flex justify-between w-full mt-2">
<div class="text-xs font-medium">
{$i18n.t('Languages')}
</div>
<input
class="text-sm bg-transparent outline-hidden"
type="text"
bind:value={localRAGConfig.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"
>
{$i18n.t('Use LLM')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={localRAGConfig.DATALAB_MARKER_USE_LLM} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t('Skip the cache and re-run the inference. Defaults to False.')}
placement="top-start"
>
{$i18n.t('Skip Cache')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={localRAGConfig.DATALAB_MARKER_SKIP_CACHE} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$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"
>
{$i18n.t('Force OCR')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={localRAGConfig.DATALAB_MARKER_FORCE_OCR} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$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"
>
{$i18n.t('Paginate')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={localRAGConfig.DATALAB_MARKER_PAGINATE} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$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"
>
{$i18n.t('Strip Existing OCR')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={localRAGConfig.DATALAB_MARKER_STRIP_EXISTING_OCR} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
'Disable image extraction from the PDF. If Use LLM is enabled, images will be automatically captioned. Defaults to False.'
)}
placement="top-start"
>
{$i18n.t('Disable Image Extraction')}
</Tooltip>
</div>
<div class="flex items-center">
<Switch bind:state={localRAGConfig.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION} />
</div>
</div>
<div class="flex justify-between w-full mt-2">
<div class="self-center text-xs font-medium">
<Tooltip
content={$i18n.t(
"The output format for the text. Can be 'json', 'markdown', or 'html'. Defaults to 'markdown'."
)}
placement="top-start"
>
{$i18n.t('Output Format')}
</Tooltip>
</div>
<div class="">
<select
class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 text-xs bg-transparent outline-hidden text-right"
bind:value={localRAGConfig.DATALAB_MARKER_OUTPUT_FORMAT}
>
<option value="markdown">{$i18n.t('Markdown')}</option>
<option value="json">{$i18n.t('JSON')}</option>
<option value="html">{$i18n.t('HTML')}</option>
</select>
</div>
</div>
{:else if localRAGConfig.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"
@ -454,6 +618,8 @@
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';
}
@ -462,6 +628,7 @@
<option value="">{$i18n.t('Default (SentenceTransformers)')}</option>
<option value="ollama">{$i18n.t('Ollama')}</option>
<option value="openai">{$i18n.t('OpenAI')}</option>
<option value="azure_openai">Azure OpenAI</option>
</select>
</div>
</div>
@ -492,6 +659,26 @@
required={false}
/>
</div>
{:else if embeddingEngine === 'azure_openai'}
<div class="my-0.5 flex flex-col gap-2 pr-2 w-full">
<div class="flex gap-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder={$i18n.t('API Base URL')}
bind:value={AzureOpenAIUrl}
required
/>
<SensitiveInput placeholder={$i18n.t('API Key')} bind:value={AzureOpenAIKey} />
</div>
<div class="flex gap-2">
<input
class="flex-1 w-full text-sm bg-transparent outline-hidden"
placeholder="Version"
bind:value={AzureOpenAIVersion}
required
/>
</div>
</div>
{/if}
</div>
@ -643,7 +830,7 @@
</div>
{#if embeddingEngine === 'ollama' || embeddingEngine === 'openai'}
{#if embeddingEngine === 'ollama' || embeddingEngine === 'openai'|| embeddingEngine === 'azure_openai'}
<div class=" mb-2.5 flex w-full justify-between">
<div class=" self-center text-xs font-medium">
{$i18n.t('Embedding Batch Size')}
@ -854,6 +1041,25 @@
</div>
</div>
{/if}
{#if localRAGConfig.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={localRAGConfig.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">