mirror of
https://github.com/open-webui/open-webui.git
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refac
This commit is contained in:
Timothy Jaeryang Baek
parent
2328dc284e
commit
488631db98
2 changed files with 69 additions and 62 deletions
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@ -241,13 +241,13 @@ class SearchForm(BaseModel):
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async def get_status(request: Request):
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return {
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"status": True,
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"chunk_size": request.app.state.config.CHUNK_SIZE,
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"chunk_overlap": request.app.state.config.CHUNK_OVERLAP,
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"template": request.app.state.config.RAG_TEMPLATE,
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"embedding_engine": request.app.state.config.RAG_EMBEDDING_ENGINE,
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"embedding_model": request.app.state.config.RAG_EMBEDDING_MODEL,
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"reranking_model": request.app.state.config.RAG_RERANKING_MODEL,
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"embedding_batch_size": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
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"CHUNK_SIZE": request.app.state.config.CHUNK_SIZE,
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"CHUNK_OVERLAP": request.app.state.config.CHUNK_OVERLAP,
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"RAG_TEMPLATE": request.app.state.config.RAG_TEMPLATE,
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"RAG_EMBEDDING_ENGINE": request.app.state.config.RAG_EMBEDDING_ENGINE,
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"RAG_EMBEDDING_MODEL": request.app.state.config.RAG_EMBEDDING_MODEL,
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"RAG_RERANKING_MODEL": request.app.state.config.RAG_RERANKING_MODEL,
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"RAG_EMBEDDING_BATCH_SIZE": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
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"ENABLE_ASYNC_EMBEDDING": request.app.state.config.ENABLE_ASYNC_EMBEDDING,
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}
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@ -256,9 +256,9 @@ async def get_status(request: Request):
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async def get_embedding_config(request: Request, user=Depends(get_admin_user)):
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return {
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"status": True,
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"embedding_engine": request.app.state.config.RAG_EMBEDDING_ENGINE,
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"embedding_model": request.app.state.config.RAG_EMBEDDING_MODEL,
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"embedding_batch_size": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
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"RAG_EMBEDDING_ENGINE": request.app.state.config.RAG_EMBEDDING_ENGINE,
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"RAG_EMBEDDING_MODEL": request.app.state.config.RAG_EMBEDDING_MODEL,
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"RAG_EMBEDDING_BATCH_SIZE": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
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"ENABLE_ASYNC_EMBEDDING": request.app.state.config.ENABLE_ASYNC_EMBEDDING,
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"openai_config": {
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"url": request.app.state.config.RAG_OPENAI_API_BASE_URL,
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@ -296,19 +296,13 @@ class EmbeddingModelUpdateForm(BaseModel):
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openai_config: Optional[OpenAIConfigForm] = None
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ollama_config: Optional[OllamaConfigForm] = None
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azure_openai_config: Optional[AzureOpenAIConfigForm] = None
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embedding_engine: str
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embedding_model: str
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embedding_batch_size: Optional[int] = 1
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RAG_EMBEDDING_ENGINE: str
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RAG_EMBEDDING_MODEL: str
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RAG_EMBEDDING_BATCH_SIZE: Optional[int] = 1
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ENABLE_ASYNC_EMBEDDING: Optional[bool] = True
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@router.post("/embedding/update")
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async def update_embedding_config(
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request: Request, form_data: EmbeddingModelUpdateForm, user=Depends(get_admin_user)
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):
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log.info(
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f"Updating embedding model: {request.app.state.config.RAG_EMBEDDING_MODEL} to {form_data.embedding_model}"
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)
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def unload_embedding_model(request: Request):
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if request.app.state.config.RAG_EMBEDDING_ENGINE == "":
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# unloads current internal embedding model and clears VRAM cache
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request.app.state.ef = None
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@ -321,9 +315,25 @@ async def update_embedding_config(
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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@router.post("/embedding/update")
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async def update_embedding_config(
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request: Request, form_data: EmbeddingModelUpdateForm, user=Depends(get_admin_user)
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):
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log.info(
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f"Updating embedding model: {request.app.state.config.RAG_EMBEDDING_MODEL} to {form_data.RAG_EMBEDDING_MODEL}"
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)
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unload_embedding_model(request)
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try:
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request.app.state.config.RAG_EMBEDDING_ENGINE = form_data.embedding_engine
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request.app.state.config.RAG_EMBEDDING_MODEL = form_data.embedding_model
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request.app.state.config.RAG_EMBEDDING_ENGINE = form_data.RAG_EMBEDDING_ENGINE
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request.app.state.config.RAG_EMBEDDING_MODEL = form_data.RAG_EMBEDDING_MODEL
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request.app.state.config.RAG_EMBEDDING_BATCH_SIZE = (
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form_data.RAG_EMBEDDING_BATCH_SIZE
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)
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request.app.state.config.ENABLE_ASYNC_EMBEDDING = (
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form_data.ENABLE_ASYNC_EMBEDDING
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)
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if request.app.state.config.RAG_EMBEDDING_ENGINE in [
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"ollama",
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@ -357,14 +367,6 @@ async def update_embedding_config(
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form_data.azure_openai_config.version
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)
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request.app.state.config.RAG_EMBEDDING_BATCH_SIZE = (
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form_data.embedding_batch_size
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)
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request.app.state.config.ENABLE_ASYNC_EMBEDDING = (
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form_data.enable_async_embedding
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)
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request.app.state.ef = get_ef(
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request.app.state.config.RAG_EMBEDDING_ENGINE,
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request.app.state.config.RAG_EMBEDDING_MODEL,
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@ -403,9 +405,9 @@ async def update_embedding_config(
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return {
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"status": True,
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"embedding_engine": request.app.state.config.RAG_EMBEDDING_ENGINE,
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"embedding_model": request.app.state.config.RAG_EMBEDDING_MODEL,
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"embedding_batch_size": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
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"RAG_EMBEDDING_ENGINE": request.app.state.config.RAG_EMBEDDING_ENGINE,
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"RAG_EMBEDDING_MODEL": request.app.state.config.RAG_EMBEDDING_MODEL,
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"RAG_EMBEDDING_BATCH_SIZE": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
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"ENABLE_ASYNC_EMBEDDING": request.app.state.config.ENABLE_ASYNC_EMBEDDING,
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"openai_config": {
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"url": request.app.state.config.RAG_OPENAI_API_BASE_URL,
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@ -38,9 +38,9 @@
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let showResetUploadDirConfirm = false;
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let showReindexConfirm = false;
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let embeddingEngine = '';
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let embeddingModel = '';
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let embeddingBatchSize = 1;
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let RAG_EMBEDDING_ENGINE = '';
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let RAG_EMBEDDING_MODEL = '';
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let RAG_EMBEDDING_BATCH_SIZE = 1;
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let ENABLE_ASYNC_EMBEDDING = true;
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let rerankingModel = '';
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@ -66,7 +66,7 @@
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let RAGConfig = null;
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const embeddingModelUpdateHandler = async () => {
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if (embeddingEngine === '' && embeddingModel.split('/').length - 1 > 1) {
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if (RAG_EMBEDDING_ENGINE === '' && RAG_EMBEDDING_MODEL.split('/').length - 1 > 1) {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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@ -74,7 +74,7 @@
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);
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return;
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}
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if (embeddingEngine === 'ollama' && embeddingModel === '') {
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if (RAG_EMBEDDING_ENGINE === 'ollama' && RAG_EMBEDDING_MODEL === '') {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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@ -83,7 +83,7 @@
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return;
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}
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if (embeddingEngine === 'openai' && embeddingModel === '') {
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if (RAG_EMBEDDING_ENGINE === 'openai' && RAG_EMBEDDING_MODEL === '') {
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toast.error(
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$i18n.t(
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'Model filesystem path detected. Model shortname is required for update, cannot continue.'
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@ -93,20 +93,25 @@
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}
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if (
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embeddingEngine === 'azure_openai' &&
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RAG_EMBEDDING_ENGINE === 'azure_openai' &&
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(AzureOpenAIKey === '' || AzureOpenAIUrl === '' || AzureOpenAIVersion === '')
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) {
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toast.error($i18n.t('OpenAI URL/Key required.'));
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return;
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}
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console.debug('Update embedding model attempt:', embeddingModel);
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console.debug('Update embedding model attempt:', {
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RAG_EMBEDDING_ENGINE,
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RAG_EMBEDDING_MODEL,
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RAG_EMBEDDING_BATCH_SIZE,
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ENABLE_ASYNC_EMBEDDING
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});
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updateEmbeddingModelLoading = true;
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const res = await updateEmbeddingConfig(localStorage.token, {
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embedding_engine: embeddingEngine,
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embedding_model: embeddingModel,
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embedding_batch_size: embeddingBatchSize,
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RAG_EMBEDDING_ENGINE: RAG_EMBEDDING_ENGINE,
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RAG_EMBEDDING_MODEL: RAG_EMBEDDING_MODEL,
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RAG_EMBEDDING_BATCH_SIZE: RAG_EMBEDDING_BATCH_SIZE,
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ENABLE_ASYNC_EMBEDDING: ENABLE_ASYNC_EMBEDDING,
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ollama_config: {
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key: OllamaKey,
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@ -237,9 +242,9 @@
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const embeddingConfig = await getEmbeddingConfig(localStorage.token);
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if (embeddingConfig) {
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embeddingEngine = embeddingConfig.embedding_engine;
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embeddingModel = embeddingConfig.embedding_model;
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embeddingBatchSize = embeddingConfig.embedding_batch_size ?? 1;
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RAG_EMBEDDING_ENGINE = embeddingConfig.RAG_EMBEDDING_ENGINE;
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RAG_EMBEDDING_MODEL = embeddingConfig.RAG_EMBEDDING_MODEL;
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RAG_EMBEDDING_BATCH_SIZE = embeddingConfig.RAG_EMBEDDING_BATCH_SIZE ?? 1;
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ENABLE_ASYNC_EMBEDDING = embeddingConfig.ENABLE_ASYNC_EMBEDDING ?? true;
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OpenAIKey = embeddingConfig.openai_config.key;
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@ -772,17 +777,17 @@
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<div class="flex items-center relative">
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<select
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class="dark:bg-gray-900 w-fit pr-8 rounded-sm px-2 p-1 text-xs bg-transparent outline-hidden text-right"
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bind:value={embeddingEngine}
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bind:value={RAG_EMBEDDING_ENGINE}
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placeholder={$i18n.t('Select an embedding model engine')}
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on:change={(e) => {
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if (e.target.value === 'ollama') {
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embeddingModel = '';
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RAG_EMBEDDING_MODEL = '';
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} else if (e.target.value === 'openai') {
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embeddingModel = 'text-embedding-3-small';
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RAG_EMBEDDING_MODEL = 'text-embedding-3-small';
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} else if (e.target.value === 'azure_openai') {
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embeddingModel = 'text-embedding-3-small';
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RAG_EMBEDDING_MODEL = 'text-embedding-3-small';
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} else if (e.target.value === '') {
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embeddingModel = 'sentence-transformers/all-MiniLM-L6-v2';
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RAG_EMBEDDING_MODEL = 'sentence-transformers/all-MiniLM-L6-v2';
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}
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}}
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>
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@ -794,7 +799,7 @@
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</div>
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</div>
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{#if embeddingEngine === 'openai'}
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{#if RAG_EMBEDDING_ENGINE === 'openai'}
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<div class="my-0.5 flex gap-2 pr-2">
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<input
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class="flex-1 w-full text-sm bg-transparent outline-hidden"
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@ -809,7 +814,7 @@
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required={false}
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/>
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</div>
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{:else if embeddingEngine === 'ollama'}
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{:else if RAG_EMBEDDING_ENGINE === 'ollama'}
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<div class="my-0.5 flex gap-2 pr-2">
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<input
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class="flex-1 w-full text-sm bg-transparent outline-hidden"
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@ -824,7 +829,7 @@
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required={false}
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/>
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</div>
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{:else if embeddingEngine === 'azure_openai'}
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{:else if RAG_EMBEDDING_ENGINE === 'azure_openai'}
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<div class="my-0.5 flex flex-col gap-2 pr-2 w-full">
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<div class="flex gap-2">
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<input
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@ -851,12 +856,12 @@
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<div class=" mb-1 text-xs font-medium">{$i18n.t('Embedding Model')}</div>
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<div class="">
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{#if embeddingEngine === 'ollama'}
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{#if RAG_EMBEDDING_ENGINE === 'ollama'}
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<div class="flex w-full">
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<div class="flex-1 mr-2">
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<input
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class="flex-1 w-full text-sm bg-transparent outline-hidden"
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bind:value={embeddingModel}
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bind:value={RAG_EMBEDDING_MODEL}
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placeholder={$i18n.t('Set embedding model')}
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required
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/>
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@ -868,13 +873,13 @@
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<input
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class="flex-1 w-full text-sm bg-transparent outline-hidden"
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placeholder={$i18n.t('Set embedding model (e.g. {{model}})', {
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model: embeddingModel.slice(-40)
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model: RAG_EMBEDDING_MODEL.slice(-40)
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})}
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bind:value={embeddingModel}
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bind:value={RAG_EMBEDDING_MODEL}
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/>
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</div>
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{#if embeddingEngine === ''}
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{#if RAG_EMBEDDING_ENGINE === ''}
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<button
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class="px-2.5 bg-transparent text-gray-800 dark:bg-transparent dark:text-gray-100 rounded-lg transition"
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on:click={() => {
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@ -914,7 +919,7 @@
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</div>
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</div>
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{#if embeddingEngine === 'ollama' || embeddingEngine === 'openai' || embeddingEngine === 'azure_openai'}
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{#if RAG_EMBEDDING_ENGINE === 'ollama' || RAG_EMBEDDING_ENGINE === 'openai' || RAG_EMBEDDING_ENGINE === 'azure_openai'}
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<div class=" mb-2.5 flex w-full justify-between">
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<div class=" self-center text-xs font-medium">
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{$i18n.t('Embedding Batch Size')}
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@ -922,7 +927,7 @@
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<div class="">
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<input
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bind:value={embeddingBatchSize}
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bind:value={RAG_EMBEDDING_BATCH_SIZE}
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type="number"
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class=" bg-transparent text-center w-14 outline-none"
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min="-2"
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