diff --git a/docs/docs/integrations/chat/naver.ipynb b/docs/docs/integrations/chat/naver.ipynb
index f3366d7239477..834f34cfddb8b 100644
--- a/docs/docs/integrations/chat/naver.ipynb
+++ b/docs/docs/integrations/chat/naver.ipynb
@@ -1,14 +1,14 @@
 {
  "cells": [
   {
-   "metadata": {},
    "cell_type": "raw",
+   "id": "afaf8039",
+   "metadata": {},
    "source": [
     "---\n",
     "sidebar_label: Naver\n",
     "---"
-   ],
-   "id": "f0e6bc10e127ff6c"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -17,7 +17,7 @@
    "source": [
     "# ChatClovaX\n",
     "\n",
-    "This notebook provides a quick overview for getting started with Naver’s HyperCLOVA X [chat models](https://python.langchain.com/v0.2/docs/concepts/#chat-models) via CLOVA Studio. For detailed documentation of all ChatClovaX features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.naver.ChatClovaX.html).\n",
+    "This notebook provides a quick overview for getting started with Naver’s HyperCLOVA X [chat models](https://python.langchain.com/v0.2/docs/concepts/#chat-models) via CLOVA Studio. For detailed documentation of all ChatClovaX features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/community/chat_models/langchain_community.chat_models.naver.ChatClovaX.html).\n",
     "\n",
     "CLOVA Studio has several chat models. You can find information about latest models and their costs, context windows, and supported input types in the CLOVA Studio API Guide [documentation](https://api.ncloud-docs.com/docs/clovastudio-chatcompletions).\n",
     "\n",
@@ -45,28 +45,28 @@
     "\n",
     "CLOVA Studio requires 2 keys (`NCP_CLOVASTUDIO_API_KEY` and `NCP_APIGW_API_KEY`).\n",
     "  - `NCP_CLOVASTUDIO_API_KEY` is issued per Test App or Service App\n",
-    "  - `NCP_APIGW_API_KEY` is issued per account\n",
+    "  - `NCP_APIGW_API_KEY` is issued per account, could be optional depending on the region you are using\n",
     "\n",
     "The two API Keys could be found by clicking `App Request Status` > `Service App, Test App List` > `‘Details’ button for each app` in [CLOVA Studio](https://clovastudio.ncloud.com/studio-application/service-app)"
    ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "2def81b5-b023-4f40-a97b-b2c5ca59d6a9",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
     "\n",
     "os.environ[\"NCP_CLOVASTUDIO_API_KEY\"] = getpass.getpass(\"NCP CLOVA Studio API Key: \")\n",
     "os.environ[\"NCP_APIGW_API_KEY\"] = getpass.getpass(\"NCP API Gateway API Key: \")"
-   ],
-   "id": "bcc89bab8951dbe1"
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "0730d6a1-c893-4840-9817-5e5251676d5d",
+   "id": "17bf9053-90c5-4955-b239-55a35cb07566",
    "metadata": {},
    "source": [
     "### Installation\n",
@@ -77,7 +77,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
+   "id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -97,7 +97,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
    "metadata": {},
    "outputs": [],
@@ -109,10 +109,10 @@
     "    temperature=0.5,\n",
     "    max_tokens=None,\n",
     "    max_retries=2,\n",
-    "    # clovastudio_api_key=\"...\"  # if you prefer to pass api key in directly instead of using env vars\n",
-    "    # task_id=\"...\"  # if you want to use fine-tuned model\n",
-    "    # service_app=False (default)  # True if using service app\n",
-    "    # include_ai_filters=False (default) ## True if you want to detect inappropriate content\n",
+    "    # clovastudio_api_key=\"...\"    # if you prefer to pass api key in directly instead of using env vars\n",
+    "    # task_id=\"...\"    # if you want to use fine-tuned model\n",
+    "    # service_app=False    # True if using Service App. Default value is False (means using Test App)\n",
+    "    # include_ai_filters=False     # True if you want to detect inappropriate content. Default value is False\n",
     "    # other params...\n",
     ")"
    ]
@@ -128,10 +128,13 @@
    ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
+   "execution_count": 14,
+   "id": "62e0dbc3",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
-   "execution_count": null,
    "source": [
     "messages = [\n",
     "    (\n",
@@ -140,42 +143,74 @@
     "    ),\n",
     "    (\"human\", \"I love using NAVER AI.\"),\n",
     "]"
-   ],
-   "id": "b1e9edff909a9705"
+   ]
   },
   {
+   "cell_type": "markdown",
+   "id": "47752b59",
    "metadata": {},
+   "source": [
+    "## Invocation\n",
+    "\n",
+    "In addition to invoke, we also support batch and stream functionalities."
+   ]
+  },
+  {
    "cell_type": "code",
-   "outputs": [],
-   "execution_count": null,
+   "execution_count": 15,
+   "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='저는 NAVER AI를 사용하는 것이 너무 좋아요.', response_metadata={'stop_reason': 'stop_before', 'input_length': 25, 'output_length': 15, 'seed': 1655372866, 'ai_filter': None}, id='run-412be878-f8a2-4917-ad71-f23ee250771a-0')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "#using invoke\n",
     "chat.invoke(messages)"
-   ],
-   "id": "c7769b0eaf9ffcd6"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
-   "execution_count": null,
+   "execution_count": 13,
+   "id": "876d2c2a-1b29-4b9e-92ed-381223c9439f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[AIMessage(content='나는 NAVER AI를 사용하는 것이 좋아요.', response_metadata={'stop_reason': 'stop_before', 'input_length': 25, 'output_length': 13, 'seed': 1938804380, 'ai_filter': None}, id='run-b5349497-a959-4ab9-a3b0-28483b0f223d-0'),\n",
+       " AIMessage(content='나는 NAVER AI를 사용하는 것이 좋아요.', response_metadata={'stop_reason': 'stop_before', 'input_length': 25, 'output_length': 13, 'seed': 2603129649, 'ai_filter': None}, id='run-ab428833-d6b4-43d8-8342-d034ed6c6447-0')]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "#using batch\n",
     "chat.batch([messages, messages])"
-   ],
-   "id": "1d116306fa105a00"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "2c07af21-dda5-4514-b4de-1f214c2cebcd",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "#using stream\n",
     "for chunk in chat.stream(messages):\n",
     "    print(chunk.content, end=\"\", flush=True)"
-   ],
-   "id": "3f09503abaf56a8f"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -189,10 +224,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='나는 NAVER AI를 사용하는 것이 좋아요.', response_metadata={'stop_reason': 'stop_before', 'input_length': 25, 'output_length': 13, 'seed': 4065547179, 'ai_filter': None}, id='run-2662b461-382e-4aac-a59f-8cb824b8cc51-0', usage_metadata={'input_tokens': 25, 'output_tokens': 13, 'total_tokens': 38})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from langchain_core.prompts import ChatPromptTemplate\n",
     "\n",
@@ -220,8 +266,9 @@
    ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "d1ee55bc-ffc8-4cfa-801c-993953a08cfd",
+   "metadata": {},
    "source": [
     "## Additional functionalities\n",
     "\n",
@@ -230,14 +277,14 @@
     "You can call fine-tuned CLOVA X models by passing in your corresponding `task_id` parameter. (You don’t need to specify the model_name parameter when calling fine-tuned model.)\n",
     "\n",
     "You can check `task_id` from corresponding Test App or Service App details."
-   ],
-   "id": "b17f1745ecca4559"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "cb436788",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "fine_tuned_model = ChatClovaX(\n",
     "    task_id='abcd123e',\n",
@@ -245,43 +292,42 @@
     ")\n",
     "\n",
     "fine_tuned_model.invoke(messages)"
-   ],
-   "id": "955392044d4c967"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "f428deaf",
+   "metadata": {},
    "source": [
     "### Service App\n",
     "\n",
     "When going live with production-level application using CLOVA Studio, you should apply for and use Service App. (See [here](https://guide.ncloud-docs.com/docs/en/clovastudio-playground01#서비스앱신청).)\n",
     "\n",
     "For a Service App, a corresponding `NCP_CLOVASTUDIO_API_KEY` is issued and can only be called with the API Key."
-   ],
-   "id": "60f993c25f29f615"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "dcf566df",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "#### Update environment variables\n",
     "\n",
     "os.environ[\"NCP_CLOVASTUDIO_API_KEY\"] = getpass.getpass(\"NCP CLOVA Studio API Key for Service App: \")"
-   ],
-   "id": "10afeeff7b96a826"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
+   "execution_count": 8,
+   "id": "cebe27ae",
+   "metadata": {},
    "outputs": [],
-   "execution_count": null,
    "source": [
     "chat = ChatClovaX(\n",
     "    service_app=True, # True if you want to use your service app, default value is False.\n",
     "    # clovastudio_api_key=\"...\"  # if you prefer to pass api key in directly instead of using env vars\n",
-    "    # apigw_api_key=\"...\"  # if you prefer to pass gateway key in directly instead of using env vars\n",
     "    model=\"HCX-DASH-001\",\n",
     "    temperature=0.5,\n",
     "    max_tokens=None,\n",
@@ -289,24 +335,24 @@
     "    # other params...\n",
     ")\n",
     "ai_msg = chat.invoke(messages)"
-   ],
-   "id": "79a8b75e0f3c62cf"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "d73e7140",
+   "metadata": {},
    "source": [
     "### AI Filter\n",
     "\n",
     "AI Filter detects inappropriate output such as profanity from the test app (or service app included) created in Playground and informs the user. See [here](https://guide.ncloud-docs.com/docs/en/clovastudio-playground01#AIFilter) for details. "
-   ],
-   "id": "a44107dc538a570c"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "32bfbc93",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "chat = ChatClovaX(\n",
     "    model=\"HCX-DASH-001\",\n",
@@ -318,26 +364,27 @@
     ")\n",
     "\n",
     "ai_msg = chat.invoke(messages)"
-   ],
-   "id": "23d40ddcc3ad428"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
-   "source": "print(ai_msg.response_metadata['ai_filter'])",
-   "id": "2f0ac38b0d6f4473"
+   "id": "7bd9e179",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(ai_msg.response_metadata['ai_filter'])"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
+   "metadata": {},
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all ChatClovaX features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.naver.ChatClovaX.html"
-   ],
-   "id": "fb21a159a74f9dad"
+    "For detailed documentation of all ChatNaver features and configurations head to the API reference: https://api.python.langchain.com/en/latest/community/chat_models/langchain_community.chat_models.naver.ChatClovaX.html"
+   ]
   }
  ],
  "metadata": {
@@ -356,7 +403,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,
diff --git a/docs/docs/integrations/text_embedding/naver.ipynb b/docs/docs/integrations/text_embedding/naver.ipynb
index 16a8e1b130e83..f0cd61edd448c 100644
--- a/docs/docs/integrations/text_embedding/naver.ipynb
+++ b/docs/docs/integrations/text_embedding/naver.ipynb
@@ -1,78 +1,105 @@
 {
  "cells": [
   {
-   "metadata": {},
    "cell_type": "raw",
+   "id": "afaf8039",
+   "metadata": {},
    "source": [
     "---\n",
     "sidebar_label: Naver\n",
     "---"
-   ],
-   "id": "e12128533632650f"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "e49f1e0d",
+   "metadata": {},
    "source": [
     "# ClovaXEmbeddings\n",
     "\n",
-    "This notebook covers how to get started with embedding models provided by CLOVA Studio.\n",
+    "This notebook covers how to get started with embedding models provided by CLOVA Studio. For detailed documentation on `ClovaXEmbeddings` features and configuration options, please refer to the [API reference](https://python.langchain.com/latest/api_reference/community/embeddings/langchain_community.embeddings.naver.ClovaXEmbeddings.html).\n",
+    "\n",
+    "## Overview\n",
+    "### Integration details\n",
+    "\n",
+    "| Provider | Package |\n",
+    "|:--------:|:-------:|\n",
+    "| [Naver](/docs/integrations/providers/naver.mdx) | [ClovaXEmbeddings](https://python.langchain.com/latest/api_reference/community/embeddings/langchain_community.embeddings.naver.ClovaXEmbeddings.html) |\n",
+    "\n",
+    "## Setup\n",
     "\n",
-    "## Installation"
-   ],
-   "id": "f90236718398be30"
+    "Before using embedding models provided by CLOVA Studio, you must go through the three steps below.\n",
+    "\n",
+    "1. Creating [NAVER Cloud Platform](https://www.ncloud.com/) account \n",
+    "2. Apply to use [CLOVA Studio](https://www.ncloud.com/product/aiService/clovaStudio)\n",
+    "3. Find API Keys after creating CLOVA Studio Test App or Service App (See [here](https://guide.ncloud-docs.com/docs/en/clovastudio-playground01#테스트앱생성).)\n",
+    "\n",
+    "### Credentials\n",
+    "\n",
+    "CLOVA Studio requires 3 keys (`NCP_CLOVASTUDIO_API_KEY`, `NCP_APIGW_API_KEY` and `NCP_CLOVASTUDIO_APP_ID`) for embeddings.\n",
+    "- `NCP_CLOVASTUDIO_API_KEY` and `NCP_CLOVASTUDIO_APP_ID` is issued per serviceApp or testApp\n",
+    "- `NCP_APIGW_API_KEY` is issued per account\n",
+    "\n",
+    "The two API Keys could be found by clicking `App Request Status` > `Service App, Test App List` > `‘Details’ button for each app` in [CLOVA Studio](https://clovastudio.ncloud.com/studio-application/service-app)."
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4c3bef91",
+   "id": "c52e8a50-3e67-4272-bc80-3954d98f8dea",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# install package\n",
-    "!pip install -U langchain-community"
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "os.environ[\"NCP_CLOVASTUDIO_API_KEY\"] = getpass.getpass(\"NCP CLOVA Studio API Key: \")\n",
+    "os.environ[\"NCP_APIGW_API_KEY\"] = getpass.getpass(\"NCP API Gateway API Key: \")"
    ]
   },
   {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83520d8e-ecf8-4e47-b3bc-1ac205b3a2ab",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.environ[\"NCP_CLOVASTUDIO_APP_ID\"] = input(\"NCP CLOVA Studio App ID: \")"
+   ]
+  },
+  {
    "cell_type": "markdown",
+   "id": "ff00653e",
+   "metadata": {},
    "source": [
-    "## Environment Setup\n",
-    "\n",
-    "CLOVA Studio requires 3 keys (`NCP_CLOVASTUDIO_API_KEY`, `NCP_APIGW_API_KEY` and `NCP_CLOVASTUDIO_APP_ID`) for embeddings.\n",
-    "- `NCP_CLOVASTUDIO_API_KEY` and `NCP_CLOVASTUDIO_APP_ID` is issued per serviceApp or testApp\n",
-    "- `NCP_APIGW_API_KEY` is issued per account\n",
+    "### Installation\n",
     "\n",
-    "The two API Keys could be found by clicking `App Request Status` > `Service App, Test App List` > `‘Details’ button for each app` in [CLOVA Studio](https://clovastudio.ncloud.com/studio-application/service-app)."
-   ],
-   "id": "5fbc16fa0bc03aa4"
+    "ClovaXEmbeddings integration lives in the `langchain_community` package:"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "99400c9b",
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "import getpass\n",
-    "import os\n",
-    "\n",
-    "os.environ[\"NCP_CLOVASTUDIO_API_KEY\"] = getpass.getpass(\"NCP CLOVA Studio API Key: \")\n",
-    "os.environ[\"NCP_APIGW_API_KEY\"] = getpass.getpass(\"NCP API Gateway API Key: \")"
-   ],
-   "id": "2924b3b804d36837"
+    "# install package\n",
+    "!pip install -U langchain-community"
+   ]
   },
   {
+   "cell_type": "markdown",
+   "id": "2651e611-9d5b-4315-9bbd-f99f56be4e19",
    "metadata": {},
-   "cell_type": "code",
-   "outputs": [],
-   "execution_count": null,
    "source": [
-    "os.environ[\"NCP_CLOVASTUDIO_APP_ID\"] = input(\"NCP CLOVA Studio App ID: \")\n",
-    "## Usage\n",
+    "## Instantiation\n",
     "\n",
-    "- There are several embeddings models available in CLOVA Studio. Please refer [here](https://guide.ncloud-docs.com/docs/en/clovastudio-explorer03#임베딩API) for further details."
-   ],
-   "id": "fb35b89f27117b14"
+    "Now we can instantiate our embeddings object and embed query or document:\n",
+    "\n",
+    "- There are several embedding models available in CLOVA Studio. Please refer [here](https://guide.ncloud-docs.com/docs/en/clovastudio-explorer03#임베딩API) for further details.\n",
+    "- Note that you might need to normalize the embeddings depending on your specific use case."
+   ]
   },
   {
    "cell_type": "code",
@@ -90,6 +117,61 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0493b4a8",
+   "metadata": {},
+   "source": [
+    "## Indexing and Retrieval\n",
+    "\n",
+    "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our RAG tutorials under the [working with external knowledge tutorials](/docs/tutorials/#working-with-external-knowledge).\n",
+    "\n",
+    "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4d59653",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a vector store with a sample text\n",
+    "from langchain_core.vectorstores import InMemoryVectorStore\n",
+    "\n",
+    "text = \"CLOVA Studio is an AI development tool that allows you to customize your own HyperCLOVA X models.\"\n",
+    "\n",
+    "vectorstore = InMemoryVectorStore.from_texts(\n",
+    "    [text],\n",
+    "    embedding=embeddings,\n",
+    ")\n",
+    "\n",
+    "# Use the vectorstore as a retriever\n",
+    "retriever = vectorstore.as_retriever()\n",
+    "\n",
+    "# Retrieve the most similar text\n",
+    "retrieved_documents = retriever.invoke(\"What is CLOVA Studio?\")\n",
+    "\n",
+    "# show the retrieved document's content\n",
+    "retrieved_documents[0].page_content"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1a249e1",
+   "metadata": {},
+   "source": [
+    "## Direct Usage\n",
+    "\n",
+    "Under the hood, the vectorstore and retriever implementations are calling `embeddings.embed_documents(...)` and `embeddings.embed_query(...)` to create embeddings for the text(s) used in `from_texts` and retrieval `invoke` operations, respectively.\n",
+    "\n",
+    "You can directly call these methods to get embeddings for your own use cases.\n",
+    "\n",
+    "### Embed single texts\n",
+    "\n",
+    "You can embed single texts or documents with `embed_query`:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -100,6 +182,16 @@
     "embeddings.embed_query(\"My query to look up\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "8b383b53",
+   "metadata": {},
+   "source": [
+    "### Embed multiple texts\n",
+    "\n",
+    "You can embed multiple texts with `embed_documents`:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -112,6 +204,16 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "464a4aae",
+   "metadata": {},
+   "source": [
+    "### Embed with async\n",
+    "\n",
+    "There are also async functionalities:\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -137,8 +239,9 @@
    ]
   },
   {
-   "metadata": {},
    "cell_type": "markdown",
+   "id": "eee40d32367cc5c4",
+   "metadata": {},
    "source": [
     "## Additional functionalities\n",
     "\n",
@@ -147,29 +250,40 @@
     "When going live with production-level application using CLOVA Studio, you should apply for and use Service App. (See [here](https://guide.ncloud-docs.com/docs/en/clovastudio-playground01#서비스앱신청).)\n",
     "\n",
     "For a Service App, corresponding `NCP_CLOVASTUDIO_API_KEY` and `NCP_CLOVASTUDIO_APP_ID` are issued and can only be called with the API Keys."
-   ],
-   "id": "eee40d32367cc5c4"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
+   "id": "08f9f44e-c6a4-4163-8caf-27a0cda345b7",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "#### Update environment variables\n",
     "\n",
     "os.environ[\"NCP_CLOVASTUDIO_API_KEY\"] = getpass.getpass(\"NCP CLOVA Studio API Key for Service App: \")\n",
     "os.environ[\"NCP_CLOVASTUDIO_APP_ID\"] = input(\"NCP CLOVA Studio Service App ID: \")"
-   ],
-   "id": "c5964e008e2562e9"
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
-   "outputs": [],
    "execution_count": null,
-   "source": "embeddings = ClovaXEmbeddings(service_app=True)",
-   "id": "b81408aac235e83b"
+   "id": "86f59698-b3f4-4b19-a9d4-4facfcea304b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embeddings = ClovaXEmbeddings(service_app=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ddeaee9",
+   "metadata": {},
+   "source": [
+    "## API Reference\n",
+    "\n",
+    "For detailed documentation on `ClovaXEmbeddings` features and configuration options, please refer to the [API reference](https://python.langchain.com/latest/api_reference/community/embeddings/langchain_community.embeddings.naver.ClovaXEmbeddings.html)."
+   ]
   }
  ],
  "metadata": {
@@ -188,7 +302,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,