From 3b66aa55c0d7b2a63841cc33ac31fdd142b6c3f4 Mon Sep 17 00:00:00 2001 From: Self Denial Date: Thu, 4 Apr 2024 11:01:23 -0600 Subject: [PATCH 01/13] Improve embedding model update & resolve network dependency * Add config variable RAG_EMBEDDING_MODEL_AUTO_UPDATE to control update behavior * Add RAG utils embedding_model_get_path() function to output the filesystem path in addition to update of the model using huggingface_hub * Update and utilize existing RAG functions in main: get_embedding_model() & update_embedding_model() * Add GUI setting to execute manual update process --- backend/apps/rag/main.py | 51 +++++++---- backend/apps/rag/utils.py | 35 ++++++++ backend/config.py | 3 + src/lib/apis/rag/index.ts | 61 +++++++++++++ .../documents/Settings/General.svelte | 87 ++++++++++++++++++- 5 files changed, 218 insertions(+), 19 deletions(-) diff --git a/backend/apps/rag/main.py b/backend/apps/rag/main.py index e7433f649..3d12084c8 100644 --- a/backend/apps/rag/main.py +++ b/backend/apps/rag/main.py @@ -13,7 +13,6 @@ import os, shutil, logging, re from pathlib import Path from typing import List -from sentence_transformers import SentenceTransformer from chromadb.utils import embedding_functions from langchain_community.document_loaders import ( @@ -45,7 +44,7 @@ from apps.web.models.documents import ( DocumentResponse, ) -from apps.rag.utils import query_doc, query_collection +from apps.rag.utils import query_doc, query_collection, embedding_model_get_path from utils.misc import ( calculate_sha256, @@ -60,6 +59,7 @@ from config import ( DOCS_DIR, RAG_EMBEDDING_MODEL, RAG_EMBEDDING_MODEL_DEVICE_TYPE, + RAG_EMBEDDING_MODEL_AUTO_UPDATE, CHROMA_CLIENT, CHUNK_SIZE, CHUNK_OVERLAP, @@ -71,15 +71,6 @@ from constants import ERROR_MESSAGES log = logging.getLogger(__name__) log.setLevel(SRC_LOG_LEVELS["RAG"]) -# -# if RAG_EMBEDDING_MODEL: -# sentence_transformer_ef = SentenceTransformer( -# model_name_or_path=RAG_EMBEDDING_MODEL, -# cache_folder=RAG_EMBEDDING_MODEL_DIR, -# device=RAG_EMBEDDING_MODEL_DEVICE_TYPE, -# ) - - app = FastAPI() app.state.PDF_EXTRACT_IMAGES = False @@ -87,11 +78,12 @@ app.state.CHUNK_SIZE = CHUNK_SIZE app.state.CHUNK_OVERLAP = CHUNK_OVERLAP app.state.RAG_TEMPLATE = RAG_TEMPLATE app.state.RAG_EMBEDDING_MODEL = RAG_EMBEDDING_MODEL +app.state.RAG_EMBEDDING_MODEL_PATH = embedding_model_get_path(app.state.RAG_EMBEDDING_MODEL, RAG_EMBEDDING_MODEL_AUTO_UPDATE) app.state.TOP_K = 4 app.state.sentence_transformer_ef = ( embedding_functions.SentenceTransformerEmbeddingFunction( - model_name=app.state.RAG_EMBEDDING_MODEL, + model_name=app.state.RAG_EMBEDDING_MODEL_PATH, device=RAG_EMBEDDING_MODEL_DEVICE_TYPE, ) ) @@ -132,6 +124,7 @@ async def get_embedding_model(user=Depends(get_admin_user)): return { "status": True, "embedding_model": app.state.RAG_EMBEDDING_MODEL, + "embedding_model_path": app.state.RAG_EMBEDDING_MODEL_PATH, } @@ -143,17 +136,39 @@ class EmbeddingModelUpdateForm(BaseModel): async def update_embedding_model( form_data: EmbeddingModelUpdateForm, user=Depends(get_admin_user) ): + status = True + old_model_path = app.state.RAG_EMBEDDING_MODEL_PATH app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model - app.state.sentence_transformer_ef = ( - embedding_functions.SentenceTransformerEmbeddingFunction( - model_name=app.state.RAG_EMBEDDING_MODEL, - device=RAG_EMBEDDING_MODEL_DEVICE_TYPE, + + log.debug(f"form_data.embedding_model: {form_data.embedding_model}") + log.info(f"Updating embedding model: {app.state.RAG_EMBEDDING_MODEL} to {form_data.embedding_model}") + + try: + app.state.RAG_EMBEDDING_MODEL_PATH = embedding_model_get_path(app.state.RAG_EMBEDDING_MODEL, True) + app.state.sentence_transformer_ef = ( + embedding_functions.SentenceTransformerEmbeddingFunction( + model_name=app.state.RAG_EMBEDDING_MODEL_PATH, + device=RAG_EMBEDDING_MODEL_DEVICE_TYPE, + ) ) - ) + except Exception as e: + log.exception(f"Problem updating embedding model: {e}") + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=e, + ) + + if app.state.RAG_EMBEDDING_MODEL_PATH == old_model_path: + status = False + + log.debug(f"app.state.RAG_EMBEDDING_MODEL_PATH: {app.state.RAG_EMBEDDING_MODEL_PATH}") + log.debug(f"old_model_path: {old_model_path}") + log.debug(f"status: {status}") return { - "status": True, + "status": status, "embedding_model": app.state.RAG_EMBEDDING_MODEL, + "embedding_model_path": app.state.RAG_EMBEDDING_MODEL_PATH, } diff --git a/backend/apps/rag/utils.py b/backend/apps/rag/utils.py index 7b9e6628c..249048b3e 100644 --- a/backend/apps/rag/utils.py +++ b/backend/apps/rag/utils.py @@ -1,6 +1,8 @@ +import os import re import logging from typing import List +from huggingface_hub import snapshot_download from config import SRC_LOG_LEVELS, CHROMA_CLIENT @@ -188,3 +190,36 @@ def rag_messages(docs, messages, template, k, embedding_function): messages[last_user_message_idx] = new_user_message return messages + +def embedding_model_get_path(embedding_model: str, update_embedding_model: bool = False): + # Construct huggingface_hub kwargs with local_files_only to return the snapshot path + cache_dir = os.getenv("SENTENCE_TRANSFORMERS_HOME") + local_files_only = not update_embedding_model + snapshot_kwargs = { + "cache_dir": cache_dir, + "local_files_only": local_files_only, + } + + log.debug(f"SENTENCE_TRANSFORMERS_HOME cache_dir: {cache_dir}") + log.debug(f"embedding_model: {embedding_model}") + log.debug(f"update_embedding_model: {update_embedding_model}") + log.debug(f"local_files_only: {local_files_only}") + + # Inspiration from upstream sentence_transformers + if (os.path.exists(embedding_model) or ("\\" in embedding_model or embedding_model.count("/") > 1) and local_files_only): + # If fully qualified path exists, return input, else set repo_id + return embedding_model + elif "/" not in embedding_model: + # Set valid repo_id for model short-name + embedding_model = "sentence-transformers" + "/" + embedding_model + + snapshot_kwargs["repo_id"] = embedding_model + + # Attempt to query the huggingface_hub library to determine the local path and/or to update + try: + embedding_model_repo_path = snapshot_download(**snapshot_kwargs) + log.debug(f"embedding_model_repo_path: {embedding_model_repo_path}") + return embedding_model_repo_path + except Exception as e: + log.exception(f"Cannot determine embedding model snapshot path: {e}") + return embedding_model diff --git a/backend/config.py b/backend/config.py index 39411d255..b3299a97f 100644 --- a/backend/config.py +++ b/backend/config.py @@ -395,6 +395,9 @@ RAG_EMBEDDING_MODEL = os.environ.get("RAG_EMBEDDING_MODEL", "all-MiniLM-L6-v2") RAG_EMBEDDING_MODEL_DEVICE_TYPE = os.environ.get( "RAG_EMBEDDING_MODEL_DEVICE_TYPE", "cpu" ) +RAG_EMBEDDING_MODEL_AUTO_UPDATE = False +if os.environ.get("RAG_EMBEDDING_MODEL_AUTO_UPDATE", "").lower() == "true": + RAG_EMBEDDING_MODEL_AUTO_UPDATE = True CHROMA_CLIENT = chromadb.PersistentClient( path=CHROMA_DATA_PATH, settings=Settings(allow_reset=True, anonymized_telemetry=False), diff --git a/src/lib/apis/rag/index.ts b/src/lib/apis/rag/index.ts index 668fe227b..33c70e2b1 100644 --- a/src/lib/apis/rag/index.ts +++ b/src/lib/apis/rag/index.ts @@ -345,3 +345,64 @@ export const resetVectorDB = async (token: string) => { return res; }; + +export const getEmbeddingModel = async (token: string) => { + let error = null; + + const res = await fetch(`${RAG_API_BASE_URL}/embedding/model`, { + method: 'GET', + headers: { + 'Content-Type': 'application/json', + Authorization: `Bearer ${token}` + } + }) + .then(async (res) => { + if (!res.ok) throw await res.json(); + return res.json(); + }) + .catch((err) => { + console.log(err); + error = err.detail; + return null; + }); + + if (error) { + throw error; + } + + return res; +}; + +type EmbeddingModelUpdateForm = { + embedding_model: string; +}; + +export const updateEmbeddingModel = async (token: string, payload: EmbeddingModelUpdateForm) => { + let error = null; + + const res = await fetch(`${RAG_API_BASE_URL}/embedding/model/update`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + Authorization: `Bearer ${token}` + }, + body: JSON.stringify({ + ...payload + }) + }) + .then(async (res) => { + if (!res.ok) throw await res.json(); + return res.json(); + }) + .catch((err) => { + console.log(err); + error = err.detail; + return null; + }); + + if (error) { + throw error; + } + + return res; +}; diff --git a/src/lib/components/documents/Settings/General.svelte b/src/lib/components/documents/Settings/General.svelte index f00038de4..c20f20422 100644 --- a/src/lib/components/documents/Settings/General.svelte +++ b/src/lib/components/documents/Settings/General.svelte @@ -6,7 +6,9 @@ getQuerySettings, scanDocs, updateQuerySettings, - resetVectorDB + resetVectorDB, + getEmbeddingModel, + updateEmbeddingModel } from '$lib/apis/rag'; import { documents } from '$lib/stores'; @@ -18,6 +20,7 @@ export let saveHandler: Function; let loading = false; + let loading1 = false; let showResetConfirm = false; @@ -30,6 +33,10 @@ k: 4 }; + let embeddingModel = { + embedding_model: '', + }; + const scanHandler = async () => { loading = true; const res = await scanDocs(localStorage.token); @@ -41,6 +48,21 @@ } }; + const embeddingModelUpdateHandler = async () => { + loading1 = true; + const res = await updateEmbeddingModel(localStorage.token, embeddingModel); + loading1 = false; + + if (res) { + console.log('embeddingModelUpdateHandler:', res); + if (res.status == true) { + toast.success($i18n.t('Model {{embedding_model}} update complete!', res)); + } else { + toast.error($i18n.t('Model {{embedding_model}} update failed or not required!', res)); + } + } + }; + const submitHandler = async () => { const res = await updateRAGConfig(localStorage.token, { pdf_extract_images: pdfExtractImages, @@ -62,6 +84,8 @@ chunkOverlap = res.chunk.chunk_overlap; } + embeddingModel = await getEmbeddingModel(localStorage.token); + querySettings = await getQuerySettings(localStorage.token); }); @@ -137,6 +161,67 @@ {/if} + +
+
+ {$i18n.t('Update embedding model {{embedding_model}}', embeddingModel)} +
+ + +
From bcf79c836652496c21015d5280a1048afdb5f0b8 Mon Sep 17 00:00:00 2001 From: Self Denial Date: Thu, 4 Apr 2024 12:02:48 -0600 Subject: [PATCH 02/13] Format fixes --- backend/apps/rag/utils.py | 10 ++++++++-- src/lib/components/documents/Settings/General.svelte | 2 +- 2 files changed, 9 insertions(+), 3 deletions(-) diff --git a/backend/apps/rag/utils.py b/backend/apps/rag/utils.py index 249048b3e..4222609f1 100644 --- a/backend/apps/rag/utils.py +++ b/backend/apps/rag/utils.py @@ -191,7 +191,9 @@ def rag_messages(docs, messages, template, k, embedding_function): return messages -def embedding_model_get_path(embedding_model: str, update_embedding_model: bool = False): +def embedding_model_get_path( + embedding_model: str, update_embedding_model: bool = False +): # Construct huggingface_hub kwargs with local_files_only to return the snapshot path cache_dir = os.getenv("SENTENCE_TRANSFORMERS_HOME") local_files_only = not update_embedding_model @@ -206,7 +208,11 @@ def embedding_model_get_path(embedding_model: str, update_embedding_model: bool log.debug(f"local_files_only: {local_files_only}") # Inspiration from upstream sentence_transformers - if (os.path.exists(embedding_model) or ("\\" in embedding_model or embedding_model.count("/") > 1) and local_files_only): + if ( + os.path.exists(embedding_model) + or ("\\" in embedding_model or embedding_model.count("/") > 1) + and local_files_only + ): # If fully qualified path exists, return input, else set repo_id return embedding_model elif "/" not in embedding_model: diff --git a/src/lib/components/documents/Settings/General.svelte b/src/lib/components/documents/Settings/General.svelte index c20f20422..02b813dea 100644 --- a/src/lib/components/documents/Settings/General.svelte +++ b/src/lib/components/documents/Settings/General.svelte @@ -34,7 +34,7 @@ }; let embeddingModel = { - embedding_model: '', + embedding_model: '' }; const scanHandler = async () => { From 075fbedb02c256843afd496db707c30be557d3e8 Mon Sep 17 00:00:00 2001 From: Self Denial Date: Thu, 4 Apr 2024 12:07:42 -0600 Subject: [PATCH 03/13] More format fixes --- backend/apps/rag/main.py | 16 +++++++++++----- backend/apps/rag/utils.py | 1 + 2 files changed, 12 insertions(+), 5 deletions(-) diff --git a/backend/apps/rag/main.py b/backend/apps/rag/main.py index 3d12084c8..7e3844476 100644 --- a/backend/apps/rag/main.py +++ b/backend/apps/rag/main.py @@ -141,17 +141,21 @@ async def update_embedding_model( app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model log.debug(f"form_data.embedding_model: {form_data.embedding_model}") - log.info(f"Updating embedding model: {app.state.RAG_EMBEDDING_MODEL} to {form_data.embedding_model}") + log.info( + f"Updating embedding model: {app.state.RAG_EMBEDDING_MODEL} to {form_data.embedding_model}" + ) try: - app.state.RAG_EMBEDDING_MODEL_PATH = embedding_model_get_path(app.state.RAG_EMBEDDING_MODEL, True) + app.state.RAG_EMBEDDING_MODEL_PATH = embedding_model_get_path( + app.state.RAG_EMBEDDING_MODEL, True + ) app.state.sentence_transformer_ef = ( embedding_functions.SentenceTransformerEmbeddingFunction( model_name=app.state.RAG_EMBEDDING_MODEL_PATH, device=RAG_EMBEDDING_MODEL_DEVICE_TYPE, ) ) - except Exception as e: + except Exception as e: log.exception(f"Problem updating embedding model: {e}") raise HTTPException( status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, @@ -159,9 +163,11 @@ async def update_embedding_model( ) if app.state.RAG_EMBEDDING_MODEL_PATH == old_model_path: - status = False + status = False - log.debug(f"app.state.RAG_EMBEDDING_MODEL_PATH: {app.state.RAG_EMBEDDING_MODEL_PATH}") + log.debug( + f"app.state.RAG_EMBEDDING_MODEL_PATH: {app.state.RAG_EMBEDDING_MODEL_PATH}" + ) log.debug(f"old_model_path: {old_model_path}") log.debug(f"status: {status}") diff --git a/backend/apps/rag/utils.py b/backend/apps/rag/utils.py index 4222609f1..866759d9c 100644 --- a/backend/apps/rag/utils.py +++ b/backend/apps/rag/utils.py @@ -191,6 +191,7 @@ def rag_messages(docs, messages, template, k, embedding_function): return messages + def embedding_model_get_path( embedding_model: str, update_embedding_model: bool = False ): From 9f82f5abbad3fef40352784d020c049bd84176c2 Mon Sep 17 00:00:00 2001 From: Self Denial Date: Thu, 4 Apr 2024 12:09:48 -0600 Subject: [PATCH 04/13] Formatting... --- backend/apps/rag/main.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/backend/apps/rag/main.py b/backend/apps/rag/main.py index 7e3844476..25e93110a 100644 --- a/backend/apps/rag/main.py +++ b/backend/apps/rag/main.py @@ -78,7 +78,9 @@ app.state.CHUNK_SIZE = CHUNK_SIZE app.state.CHUNK_OVERLAP = CHUNK_OVERLAP app.state.RAG_TEMPLATE = RAG_TEMPLATE app.state.RAG_EMBEDDING_MODEL = RAG_EMBEDDING_MODEL -app.state.RAG_EMBEDDING_MODEL_PATH = embedding_model_get_path(app.state.RAG_EMBEDDING_MODEL, RAG_EMBEDDING_MODEL_AUTO_UPDATE) +app.state.RAG_EMBEDDING_MODEL_PATH = embedding_model_get_path( + app.state.RAG_EMBEDDING_MODEL, RAG_EMBEDDING_MODEL_AUTO_UPDATE +) app.state.TOP_K = 4 app.state.sentence_transformer_ef = ( From 11741ea7f03fc2559c8107bcefa587e8d9d68da3 Mon Sep 17 00:00:00 2001 From: Self Denial Date: Sat, 6 Apr 2024 04:22:48 -0600 Subject: [PATCH 05/13] Tooltip info & warn. Detect file path during update. Add translation. * Tooltips added to show full model name and warning regarding vector storage * Send toast error and return early if more than a single front slash is detected * Extend toast duration for model update action * Add i18n en_US translation * Remove commented code copied from existing function --- .../documents/Settings/General.svelte | 132 ++++++++++-------- src/lib/i18n/locales/en-US/translation.json | 7 + 2 files changed, 83 insertions(+), 56 deletions(-) diff --git a/src/lib/components/documents/Settings/General.svelte b/src/lib/components/documents/Settings/General.svelte index 02b813dea..09ba93781 100644 --- a/src/lib/components/documents/Settings/General.svelte +++ b/src/lib/components/documents/Settings/General.svelte @@ -15,6 +15,8 @@ import { onMount, getContext } from 'svelte'; import { toast } from 'svelte-sonner'; + import Tooltip from '$lib/components/common/Tooltip.svelte'; + const i18n = getContext('i18n'); export let saveHandler: Function; @@ -49,16 +51,33 @@ }; const embeddingModelUpdateHandler = async () => { + if ((embeddingModel.embedding_model.split("/").length -1) > 1) { + toast.error($i18n.t('Model filesystem path detected. Model shortname is required for update, cannot continue.', )); + return; + } + + console.log('Update embedding model attempt:', embeddingModel.embedding_model); + loading1 = true; const res = await updateEmbeddingModel(localStorage.token, embeddingModel); loading1 = false; if (res) { console.log('embeddingModelUpdateHandler:', res); - if (res.status == true) { - toast.success($i18n.t('Model {{embedding_model}} update complete!', res)); + if (res.status === true) { + toast.success( + $i18n.t('Model {{embedding_model}} update complete!', res), + { + duration: 1000 * 10, + } + ); } else { - toast.error($i18n.t('Model {{embedding_model}} update failed or not required!', res)); + toast.error( + $i18n.t('Model {{embedding_model}} update failed or not required!', res), + { + duration: 1000 * 10, + } + ); } } }; @@ -162,65 +181,66 @@ + + +
+ +
-
- {$i18n.t('Update embedding model {{embedding_model}}', embeddingModel)} -
+ - + @keyframes spinner_AtaB { + 100% { + transform: rotate(360deg); + } + } +
+ {/if} + +
diff --git a/src/lib/i18n/locales/en-US/translation.json b/src/lib/i18n/locales/en-US/translation.json index 251834e00..6813f1719 100644 --- a/src/lib/i18n/locales/en-US/translation.json +++ b/src/lib/i18n/locales/en-US/translation.json @@ -120,6 +120,7 @@ "Edit Doc": "", "Edit User": "", "Email": "", + "Embedding model: {{embedding_model}}": "", "Enable Chat History": "", "Enable New Sign Ups": "", "Enabled": "", @@ -193,8 +194,11 @@ "MMMM DD, YYYY": "", "Model '{{modelName}}' has been successfully downloaded.": "", "Model '{{modelTag}}' is already in queue for downloading.": "", + "Model {{embedding_model}} update complete!": "", + "Model {{embedding_model}} update failed or not required!": "", "Model {{modelId}} not found": "", "Model {{modelName}} already exists.": "", + "Model filesystem path detected. Model shortname is required for update, cannot continue.": "", "Model Name": "", "Model not selected": "", "Model Tag Name": "", @@ -332,7 +336,10 @@ "TTS Settings": "", "Type Hugging Face Resolve (Download) URL": "", "Uh-oh! There was an issue connecting to {{provider}}.": "", + "Understand that updating or changing your embedding model requires reset of the vector database and re-import of all documents. You have been warned!": "", "Unknown File Type '{{file_type}}', but accepting and treating as plain text": "", + "Update": "", + "Update embedding model {{embedding_model}}": "", "Update password": "", "Upload a GGUF model": "", "Upload files": "", From ec530ac9f8a043232dc5ca2a72c96a9ea586b955 Mon Sep 17 00:00:00 2001 From: Self Denial Date: Sat, 6 Apr 2024 04:38:34 -0600 Subject: [PATCH 06/13] format fix --- .../documents/Settings/General.svelte | 46 +++++++++---------- 1 file changed, 21 insertions(+), 25 deletions(-) diff --git a/src/lib/components/documents/Settings/General.svelte b/src/lib/components/documents/Settings/General.svelte index 09ba93781..cacc593c5 100644 --- a/src/lib/components/documents/Settings/General.svelte +++ b/src/lib/components/documents/Settings/General.svelte @@ -51,8 +51,12 @@ }; const embeddingModelUpdateHandler = async () => { - if ((embeddingModel.embedding_model.split("/").length -1) > 1) { - toast.error($i18n.t('Model filesystem path detected. Model shortname is required for update, cannot continue.', )); + if (embeddingModel.embedding_model.split('/').length - 1 > 1) { + toast.error( + $i18n.t( + 'Model filesystem path detected. Model shortname is required for update, cannot continue.' + ) + ); return; } @@ -65,19 +69,13 @@ if (res) { console.log('embeddingModelUpdateHandler:', res); if (res.status === true) { - toast.success( - $i18n.t('Model {{embedding_model}} update complete!', res), - { - duration: 1000 * 10, - } - ); + toast.success($i18n.t('Model {{embedding_model}} update complete!', res), { + duration: 1000 * 10 + }); } else { - toast.error( - $i18n.t('Model {{embedding_model}} update failed or not required!', res), - { - duration: 1000 * 10, - } - ); + toast.error($i18n.t('Model {{embedding_model}} update failed or not required!', res), { + duration: 1000 * 10 + }); } } }; @@ -180,26 +178,24 @@ {/if} -
- - +
- {$i18n.t('Update embedding model {{embedding_model}}', { embedding_model: embeddingModel.embedding_model.slice(-40) })} + {$i18n.t('Update embedding model {{embedding_model}}', { + embedding_model: embeddingModel.embedding_model.slice(-40) + })}
- - - +
- -
- + -
+
+ {$i18n.t( + 'Warning: If you update or change your embedding model, you will need to re-import all documents.' + )} +
-
-
{$i18n.t('Chunk Params')}
+
-
-
-
{$i18n.t('Chunk Size')}
+
+
{$i18n.t('Chunk Params')}
-
- +
+
+
{$i18n.t('Chunk Size')}
+ +
+ +
+
+ +
+
+ {$i18n.t('Chunk Overlap')} +
+ +
+ +
+
+
+ +
+
+
{$i18n.t('PDF Extract Images (OCR)')}
+ + +
-
-
{$i18n.t('Chunk Overlap')}
+
+
{$i18n.t('Query Params')}
-
- -
-
-
+
+
+
{$i18n.t('Top K')}
-
-
-
{$i18n.t('PDF Extract Images (OCR)')}
+
+ +
+
- -
-
-
- -
-
{$i18n.t('Query Params')}
- -
-
-
{$i18n.t('Top K')}
- -
- -
-
- - +
+ +
+
{$i18n.t('RAG Template')}
+