diff --git a/docs/chat_message_history.ipynb b/docs/chat_message_history.ipynb
index 7473785..0ec6baf 100644
--- a/docs/chat_message_history.ipynb
+++ b/docs/chat_message_history.ipynb
@@ -6,123 +6,167 @@
     "id": "6-0_o3DxsFGi"
    },
    "source": [
-    "Google Database\n",
+    "# Google Memorystore for Redis\n",
     "\n",
-    "Use [Google Memorystore for Redis](https://cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview) to store chat message history for LangChain."
+    "> [Google Memorystore for Redis](https://cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview) is a fully-managed service that is powered by the Redis in-memory data store to build application caches that provide sub-millisecond data access. Extend your database application to build AI-powered experiences leveraging Memorystore for Redis's Langchain integrations.\n",
+    "\n",
+    "This notebook goes over how to use [Memorystore for Redis](https://cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview) to store chat message history with the `MemorystoreChatMessageHistory` class.\n",
+    "\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/googleapis/langchain-google-memorystore-redis-python/blob/main/docs/chat_message_history.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "dWakBoPnsFGj"
-   },
+   "metadata": {},
    "source": [
-    "## Pre-reqs"
+    "## Before You Begin\n",
+    "\n",
+    "To run this notebook, you will need to do the following:\n",
+    "* [Create a Google Cloud Project](https://developers.google.com/workspace/guides/create-project)\n",
+    "* [Create a Memorystore for Redis instance](https://cloud.google.com/memorystore/docs/redis/create-instance-console). Ensure that the version is greater than or equal to 5.0.\n",
+    "\n",
+    "After confirmed access to database in the runtime environment of this notebook, filling the following values and run the cell before running example scripts."
    ]
   },
   {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "EudfLv_UsFGk"
-   },
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "### Setting Up a Memorystore for Redis Instance\n",
-    "\n",
-    "Before proceeding, an active Memorystore for Redis instance is needed to store chat message history:\n",
-    "\n",
-    "* Create a Memorystore for Redis Instance (>= 5.0): If an instance doesn't exist, follow the instructions at https://cloud.google.com/memorystore/docs/redis/create-instance-console to create a new one. Ensure the version is greater than or equal to 5.0.\n",
-    "* Obtain Endpoint: Note the endpoint associated with the instance."
+    "# @markdown Please specify an endpoint associated with the instance or demo purpose.\n",
+    "ENDPOINT = \"redis://127.0.0.1:6379\"  # @param {type:\"string\"}"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "J5nxjYxHsFGk"
-   },
+   "metadata": {},
    "source": [
-    "### Installing the LangChain Memorystore for Redis Module\n",
+    "### 🦜🔗 Library Installation\n",
     "\n",
-    "Interaction with the Memorystore for Redis instance from LangChain requires installing the necessary module:"
+    "The integration lives in its own `langchain-google-memorystore-redis` package, so we need to install it."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "tags": [],
-    "id": "iLwVMVkYsFGk"
+    "id": "iLwVMVkYsFGk",
+    "tags": []
    },
    "outputs": [],
    "source": [
-    "# Install Memorystore for Redis for LangChain module\n",
-    "%pip install langchain_google_memorystore_redis"
+    "%pip install -upgrade --quiet langchain-google-memorystore-redis"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "2L7kMu__sFGl"
-   },
+   "metadata": {},
    "source": [
-    "## Basic Usage"
+    "**Colab only:** Uncomment the following cell to restart the kernel or use the button to restart the kernel. For Vertex AI Workbench you can restart the terminal using the button on top."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Automatically restart kernel after installs so that your environment can access the new packages\n",
+    "# import IPython\n",
+    "\n",
+    "# app = IPython.Application.instance()\n",
+    "# app.kernel.do_shutdown(True)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "A2fT1iEhsFGl"
-   },
+   "metadata": {},
    "source": [
-    "### Initialize a MemorystoreChatMessageHistory\n",
+    "### ☁ Set Your Google Cloud Project\n",
+    "Set your Google Cloud project so that you can leverage Google Cloud resources within this notebook.\n",
     "\n",
-    "Each chat message history object must have a unique session ID. If the session ID already has messages stored in Redis, they will can be retrieved."
+    "If you don't know your project ID, try the following:\n",
+    "\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "id": "YEDKWR6asFGl"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "import redis\n",
-    "from langchain_google_memorystore_redis import MemorystoreChatMessageHistory\n",
+    "# @markdown Please fill in the value below with your Google Cloud project ID and then run the cell.\n",
     "\n",
-    "# Connect to a Memorystore for Redis instance\n",
-    "redis_client = redis.from_url(\"redis://127.0.0.1:6379\")\n",
+    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
     "\n",
-    "message_history = MemorystoreChatMessageHistory(redis_client, session_id=\"session1\")"
+    "# Set the project id\n",
+    "!gcloud config set project {PROJECT_ID}"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "EmoJcTgosFGl"
-   },
+   "metadata": {},
    "source": [
-    "### Add Messages"
+    "### 🔐 Authentication\n",
+    "Authenticate to Google Cloud as the IAM user logged into this notebook in order to access your Google Cloud Project.\n",
+    "\n",
+    "* If you are using Colab to run this notebook, use the cell below and continue.\n",
+    "* If you are using Vertex AI Workbench, check out the setup instructions [here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/setup-env)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from google.colab import auth\n",
+    "\n",
+    "auth.authenticate_user()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {
-    "id": "gB1PGe6wsFGm"
+    "id": "2L7kMu__sFGl"
    },
-   "outputs": [],
    "source": [
-    "message_history.add_ai_message(\"Hey! I am AI!\")\n",
-    "message_history.add_user_message(\"Hey! I am human!\")"
+    "## Basic Usage"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "02xxvmzTsFGm"
+    "id": "A2fT1iEhsFGl"
+   },
+   "source": [
+    "### MemorystoreChatMessageHistory\n",
+    "\n",
+    "To initialize the `MemorystoreMessageHistory` class you need to provide only 2 things:\n",
+    "\n",
+    "1. `redis_client` - An instance of a Memorystore Redis.\n",
+    "1. `session_id` - Each chat message history object must have a unique session ID. If the session ID already has messages stored in Redis, they will can be retrieved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YEDKWR6asFGl"
    },
+   "outputs": [],
    "source": [
-    "### Retrieve All Messages Stored in the Session"
+    "import redis\n",
+    "from langchain_google_memorystore_redis import MemorystoreChatMessageHistory\n",
+    "\n",
+    "# Connect to a Memorystore for Redis instance\n",
+    "redis_client = redis.from_url(\"redis://127.0.0.1:6379\")\n",
+    "\n",
+    "message_history = MemorystoreChatMessageHistory(redis_client, session_id=\"session1\")"
    ]
   },
   {
@@ -142,7 +186,11 @@
     "id": "sFJdt3ubsFGo"
    },
    "source": [
-    "### Clear Messages"
+    "#### Cleaning up\n",
+    "\n",
+    "When the history of a specific session is obsolete and can be deleted, it can be done the following way.\n",
+    "\n",
+    "**Note:** Once deleted, the data is no longer stored in Memorystore for Redis and is gone forever."
    ]
   },
   {
@@ -158,6 +206,9 @@
   }
  ],
  "metadata": {
+  "colab": {
+   "provenance": []
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
@@ -174,9 +225,6 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.11.6"
-  },
-  "colab": {
-   "provenance": []
   }
  },
  "nbformat": 4,
diff --git a/docs/document_loader.ipynb b/docs/document_loader.ipynb
index 0fe4e31..3ad4cd5 100644
--- a/docs/document_loader.ipynb
+++ b/docs/document_loader.ipynb
@@ -6,233 +6,290 @@
     "id": "6-0_o3DxsFGi"
    },
    "source": [
-    "Google Database\n",
+    "# Google Memorystore for Redis\n",
     "\n",
-    "Use [Google Memorystore for Redis](https://cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview) to store Documents for LangChain."
+    "> [Google Memorystore for Redis](https://cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview) is a fully-managed service that is powered by the Redis in-memory data store to build application caches that provide sub-millisecond data access. Extend your database application to build AI-powered experiences leveraging Memorystore for Redis's Langchain integrations.\n",
+    "\n",
+    "This notebook goes over how to use [Memorystore for Redis](https://cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview) to [save, load and delete langchain documents](https://python.langchain.com/docs/modules/data_connection/document_loaders/) with `MemorystoreDocumentLoader` and `MemorystoreDocumentSaver`.\n",
+    "\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/googleapis/langchain-google-memorystore-redis-python/blob/main/docs/document_loader.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "dWakBoPnsFGj"
-   },
+   "metadata": {},
    "source": [
-    "## Pre-reqs"
+    "## Before You Begin\n",
+    "\n",
+    "To run this notebook, you will need to do the following:\n",
+    "* [Create a Google Cloud Project](https://developers.google.com/workspace/guides/create-project)\n",
+    "* [Create a Memorystore for Redis instance](https://cloud.google.com/memorystore/docs/redis/create-instance-console). Ensure that the version is greater than or equal to 5.0.\n",
+    "\n",
+    "After confirmed access to database in the runtime environment of this notebook, filling the following values and run the cell before running example scripts."
    ]
   },
   {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "EudfLv_UsFGk"
-   },
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "### Setting Up a Memorystore for Redis Instance\n",
-    "\n",
-    "Before proceeding, an active Memorystore for Redis instance is needed to store chat message history:\n",
-    "\n",
-    "* Create a Memorystore for Redis Instance (>= 5.0): If an instance doesn't exist, follow the instructions at https://cloud.google.com/memorystore/docs/redis/create-instance-console to create a new one. Ensure the version is greater than or equal to 5.0.\n",
-    "* Obtain Endpoint: Note the endpoint associated with the instance."
+    "# @markdown Please specify an endpoint associated with the instance and a key prefix for demo purpose.\n",
+    "ENDPOINT = \"redis://127.0.0.1:6379\"  # @param {type:\"string\"}\n",
+    "KEY_PREFIX = \"doc:\"  # @param {type:\"string\"}"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "J5nxjYxHsFGk"
-   },
+   "metadata": {},
    "source": [
-    "### Installing the LangChain Memorystore for Redis Module\n",
+    "### 🦜🔗 Library Installation\n",
     "\n",
-    "Interaction with the Memorystore for Redis instance from LangChain requires installing the necessary module:"
+    "The integration lives in its own `langchain-google-memorystore-redis` package, so we need to install it."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": [],
-    "id": "iLwVMVkYsFGk"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Install Memorystore for Redis for LangChain module\n",
-    "%pip install langchain_google_memorystore_redis"
+    "%pip install -upgrade --quiet langchain-google-memorystore-redis"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "2L7kMu__sFGl"
-   },
+   "metadata": {},
    "source": [
-    "## Basic Usage"
+    "**Colab only**: Uncomment the following cell to restart the kernel or use the button to restart the kernel. For Vertex AI Workbench you can restart the terminal using the button on top."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Automatically restart kernel after installs so that your environment can access the new packages\n",
+    "# import IPython\n",
+    "\n",
+    "# app = IPython.Application.instance()\n",
+    "# app.kernel.do_shutdown(True)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "A2fT1iEhsFGl"
-   },
+   "metadata": {},
    "source": [
-    "### Initialize a MemorystoreDocumentLoader\n",
+    "### ☁ Set Your Google Cloud Project\n",
+    "Set your Google Cloud project so that you can leverage Google Cloud resources within this notebook.\n",
     "\n",
-    "Initialize a loader that loads all documents stored in the Memorystore for Redis instance with a specific prefix."
+    "If you don't know your project ID, try the following:\n",
+    "\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "id": "YEDKWR6asFGl"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "import redis\n",
-    "from langchain_google_memorystore_redis import MemorystoreDocumentLoader\n",
+    "# @markdown Please fill in the value below with your Google Cloud project ID and then run the cell.\n",
     "\n",
-    "# Connect to a Memorystore for Redis instance\n",
-    "redis_client = redis.from_url(\"redis://127.0.0.1:6379\")\n",
-    "prefix = \"doc:\"\n",
+    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
     "\n",
-    "loader = MemorystoreDocumentLoader(\n",
-    "    client=redis_client,\n",
-    "    key_prefix=prefix,\n",
-    "    content_fields=set([\"page_content\"]),\n",
-    ")"
+    "# Set the project id\n",
+    "!gcloud config set project {PROJECT_ID}"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "EmoJcTgosFGl"
-   },
+   "metadata": {},
    "source": [
-    "### Load Documents\n",
+    "### 🔐 Authentication\n",
+    "\n",
+    "Authenticate to Google Cloud as the IAM user logged into this notebook in order to access your Google Cloud Project.\n",
     "\n",
-    "Load all documents stored in the Memorystore for Redis instance at once."
+    "- If you are using Colab to run this notebook, use the cell below and continue.\n",
+    "- If you are using Vertex AI Workbench, check out the setup instructions [here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/setup-env)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from google.colab import auth\n",
+    "\n",
+    "auth.authenticate_user()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {
-    "id": "gB1PGe6wsFGm"
+    "id": "2L7kMu__sFGl"
    },
-   "outputs": [],
    "source": [
-    "documents = loader.load()"
+    "## Basic Usage"
    ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "### Lazy Load Documents\n",
+    "### Save documents\n",
     "\n",
-    "Load the document one-by-one with lazy_load generator."
-   ],
-   "metadata": {
-    "id": "Vbs8gIa24YvJ"
-   }
+    "Save langchain documents with `MemorystoreDocumentSaver.add_documents(<documents>)`. To initialize `MemorystoreDocumentSaver` class you need to provide 2 things:\n",
+    "1. `client` - A `redis.Redis` client object.\n",
+    "1. `key_prefix` - A prefix for the keys to store Documents in Redis.\n",
+    "\n",
+    "The Documents will be stored into randomly generated keys with the specified prefix of `key_prefix`. Alternatively, you can designate the suffixes of the keys by specifying `ids` in the `add_documents` method."
+   ]
   },
   {
    "cell_type": "code",
-   "source": [
-    "for document in loader.lazy_load():\n",
-    "    # Do something\n",
-    "    print(document)"
-   ],
-   "metadata": {
-    "id": "nPhpvLtA4kBM"
-   },
    "execution_count": null,
-   "outputs": []
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_google_memorystore_redis import MemorystoreDocumentSaver\n",
+    "\n",
+    "test_docs = [\n",
+    "    Document(\n",
+    "        page_content=\"Apple Granny Smith 150 0.99 1\",\n",
+    "        metadata={\"fruit_id\": 1},\n",
+    "    ),\n",
+    "    Document(\n",
+    "        page_content=\"Banana Cavendish 200 0.59 0\",\n",
+    "        metadata={\"fruit_id\": 2},\n",
+    "    ),\n",
+    "    Document(\n",
+    "        page_content=\"Orange Navel 80 1.29 1\",\n",
+    "        metadata={\"fruit_id\": 3},\n",
+    "    ),\n",
+    "]\n",
+    "doc_ids = [f\"{i}\" for i in range(len(test_docs))]\n",
+    "\n",
+    "redis_client = redis.from_url(ENDPOINT)\n",
+    "saver = MemorystoreDocumentSaver(\n",
+    "    client=redis_client,\n",
+    "    key_prefix=KEY_PREFIX,\n",
+    "    content_field=\"page_content\",\n",
+    ")\n",
+    "saver.add_documents(test_docs, ids=docs_ids)"
+   ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "02xxvmzTsFGm"
+    "id": "A2fT1iEhsFGl"
    },
    "source": [
-    "## Customize Document Page Content & Metadata\n",
+    "### Load documents\n",
     "\n",
-    "When initializing a loader with more than 1 content field, the `page_content` of the loaded Documents will contain a JSON-encoded string with top level fields equal to the specified fields in `content_fields`.\n",
+    "Initialize a loader that loads all documents stored in the Memorystore for Redis instance with a specific prefix.\n",
     "\n",
-    "If the `metadata_fields` are specified, the `metadata` field of the loaded Documents will only have the top level fields equal to the specified `metadata_fields`. If any of the values of the metadata fields is stored as a JSON-encoded string, it will be decoded prior to being loaded to the metadata fields."
+    "Load langchain documents with `MemorystoreDocumentLoader.load()` or `MemorystoreDocumentLoader.lazy_load()`. `lazy_load` returns a generator that only queries database during the iteration. To initialize `MemorystoreDocumentLoader` class you need to provide:\n",
+    "1. `client` - A `redis.Redis` client object.\n",
+    "1. `key_prefix` - A prefix for the keys to store Documents in Redis."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "BvS3UFsysFGm"
+    "id": "YEDKWR6asFGl"
    },
    "outputs": [],
    "source": [
+    "import redis\n",
+    "from langchain_google_memorystore_redis import MemorystoreDocumentLoader\n",
+    "\n",
+    "redis_client = redis.from_url(ENDPOINT)\n",
     "loader = MemorystoreDocumentLoader(\n",
     "    client=redis_client,\n",
-    "    key_prefix=prefix,\n",
-    "    content_fields=set([\"content_field_1\", \"content_field_2\"]),\n",
-    "    metadata_fields=set([\"title\", \"author\"]),\n",
-    ")"
+    "    key_prefix=KEY_PREFIX,\n",
+    "    content_fields=set([\"page_content\"]),\n",
+    ")\n",
+    "for doc in loader.lazy_load():\n",
+    "    print(\"Loaded documents:\", doc)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "sFJdt3ubsFGo"
-   },
+   "metadata": {},
    "source": [
-    "## Save Documents\n",
+    "### Delete documents\n",
     "\n",
-    "You can save a list of Documents into Memorystore for Redis instance like below. The Documents will be stored into randomly generated keys with the specified prefix of `key_prefix`. Alternatively, you can designate the suffixes of the keys by specifying `ids` in the `add_documents` method."
+    "Delete all of keys with the specified prefix in the Memorystore for Redis instance with `MemorystoreDocumentSaver.delete()`. You can also specify the suffixes of the keys if you know."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "id": "H5I7K3MTsFGo"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_google_memorystore_redis import MemorystoreDocumentSaver\n",
+    "docs = loader.load()\n",
+    "print(\"Documents before delete:\", docs)\n",
     "\n",
-    "# Connect to a Memorystore for Redis instance\n",
-    "redis_client = redis.from_url(\"redis://127.0.0.1:6379\")\n",
-    "prefix = \"doc:\"\n",
+    "saver.delete(ids=[0])\n",
+    "print(\"Documents after delete:\", loader.load())\n",
     "\n",
-    "saver = MemorystoreDocumentSaver(\n",
-    "    client=redis_client,\n",
-    "    key_prefix=prefix,\n",
-    "    content_field=\"page_content\",\n",
-    ")\n",
-    "saver.add_documents(documents)"
+    "saver.delete()\n",
+    "print(\"Documents after delete all:\", loader.load())"
    ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "### Clean up Saved Documents\n",
-    "\n",
-    "Delete all of keys with the specified prefix in the Memorystore for Redis instance. You can also specify the suffixes of the keys if you know.\n",
-    "\n"
-   ],
+    "## Advanced Usage"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {
-    "id": "FLVI7Kp7mhL-"
-   }
+    "id": "02xxvmzTsFGm"
+   },
+   "source": [
+    "### Customize Document Page Content & Metadata\n",
+    "\n",
+    "When initializing a loader with more than 1 content field, the `page_content` of the loaded Documents will contain a JSON-encoded string with top level fields equal to the specified fields in `content_fields`.\n",
+    "\n",
+    "If the `metadata_fields` are specified, the `metadata` field of the loaded Documents will only have the top level fields equal to the specified `metadata_fields`. If any of the values of the metadata fields is stored as a JSON-encoded string, it will be decoded prior to being loaded to the metadata fields."
+   ]
   },
   {
    "cell_type": "code",
-   "source": [
-    "saver.delete()"
-   ],
+   "execution_count": null,
    "metadata": {
-    "id": "1ArfDYUGmrP3"
+    "id": "BvS3UFsysFGm"
    },
-   "execution_count": null,
-   "outputs": []
+   "outputs": [],
+   "source": [
+    "loader = MemorystoreDocumentLoader(\n",
+    "    client=redis_client,\n",
+    "    key_prefix=prefix,\n",
+    "    content_fields=set([\"content_field_1\", \"content_field_2\"]),\n",
+    "    metadata_fields=set([\"title\", \"author\"]),\n",
+    ")"
+   ]
   }
  ],
  "metadata": {
+  "colab": {
+   "provenance": [
+    {
+     "file_id": "1kuFhDfyzOdzS1apxQ--1efXB1pJ79yVY",
+     "timestamp": 1708033015250
+    }
+   ]
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
@@ -249,14 +306,6 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.11.6"
-  },
-  "colab": {
-   "provenance": [
-    {
-     "file_id": "1kuFhDfyzOdzS1apxQ--1efXB1pJ79yVY",
-     "timestamp": 1708033015250
-    }
-   ]
   }
  },
  "nbformat": 4,