diff --git a/examples/chatgpt/rag-quickstart/gcp/Getting_started_with_bigquery_vector_search_and_openai.ipynb b/examples/chatgpt/rag-quickstart/gcp/Getting_started_with_bigquery_vector_search_and_openai.ipynb
new file mode 100644
index 0000000..fa464f1
--- /dev/null
+++ b/examples/chatgpt/rag-quickstart/gcp/Getting_started_with_bigquery_vector_search_and_openai.ipynb
@@ -0,0 +1,945 @@
+{
+ "cells": [
+  {
+   "attachments": {
+    "c398ab3a-cfcf-4061-bb6f-3e498478527c.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# GCP Bigquery with GCP Functions and GPT actions in ChatGPT\n",
+    "\n",
+    "This notebook provides step-by-step instructions on using Google Cloud BigQuery as a database with vector search capabilities, with OpenAI embeddings, then creating a Google Cloud Function on top to plug into a Custom GPT in ChatGPT.\n",
+    "\n",
+    "This can be a solution for customers looking to set up RAG infrastructure contained within Google Cloud Platform (GCP), and exposing it as an endpoint to integrate that with other platforms such as ChatGPT.\n",
+    "\n",
+    "Google Cloud BigQuery is a fully-managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google's infrastructure. It allows developers to store and analyze massive datasets with ease.\n",
+    "\n",
+    "Google Cloud Functions is a lightweight, event-based, asynchronous compute solution that allows you to create small, single-purpose functions that respond to cloud events without managing servers or runtime environments.\n",
+    "\n",
+    "## Pre-requisites:\n",
+    "\n",
+    "To run this cookbook, you must have:\n",
+    "- A GCP project you have access to\n",
+    "- GCP user with permission to create a BigQuery dataset and Google Cloud Function\n",
+    "- [GCP CLI](https://cloud.google.com/sdk/docs/downloads-interactive) installed and connected\n",
+    "- OpenAI API key\n",
+    "- ChatGPT Plus, Teams or Enterprise subscription\n",
+    "\n",
+    "\n",
+    "## Architecture\n",
+    "\n",
+    "Below is a diagram of the architecture of this solution, which we'll walk through step-by-step:\n",
+    "\n",
+    "![image.png](attachment:c398ab3a-cfcf-4061-bb6f-3e498478527c.png)\n",
+    "\n",
+    "## Table of Contents\n",
+    "\n",
+    "1. **[Setup of Environment](#set-up-environment)** Setup environment by installing and importing the required libraries and configuring our GCP settings. Includes:\n",
+    "- [Install and Import Required Libraries](#install-and-import-required-libraries)\n",
+    "- [Configure GCP project](#configure-gcp-project)\n",
+    "- [Configure OpenAI Settings](#configure-openai-settings)\n",
+    "\n",
+    "\n",
+    "2. **[Prepare Data](#prepare-data)** Prepare the data for uploading by embedding the documents, as well as capturing additional metadata. We will use a subset of OpenAI's docs as example data for this.\n",
+    "\n",
+    "3. **[Create BigQuery Table with Vector search](#create-bigquery-table-with-vector-search)**  \n",
+    "Create a BigQuery table and upload the data we've prepared. Includes:\n",
+    "\n",
+    "- [Create Dataset](#create-bigquery-dataset): Steps to create a dataset in BigQuery.\n",
+    "- [Create Table and upload data](#creating-table-and-upload-data): Instructions to create a table in BigQuery.\n",
+    "\n",
+    "4. **[Create GCP Function](#create-gcp-function)** using gcloud CLI and environment variables computed previously\n",
+    "\n",
+    "5. **[Input in a Custom GPT in ChatGPT](#input-in-a-custom-gpt-in-chatgpt)** Perform searches on the embedded data in BigQuery:\n",
+    "\n",
+    "- [Vector Search](#test-search): Steps to perform vector-based search queries.\n",
+    "- [Metadata filtering Search](#perform-search-with-metadata-filtering): Instructions for performing metadata filtering."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Set up environment"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Install and import required libraries\n",
+    "The below libraries can be categorized as standard Python libraries, third-party libraries, and GCP-related libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q google-auth\n",
+    "! pip install -q openai\n",
+    "! pip install -q pandas\n",
+    "! pip install -q google-cloud-functions\n",
+    "! pip install -q python-dotenv\n",
+    "! pip install -q pyperclip\n",
+    "! pip install -q PyPDF2\n",
+    "! pip install -q tiktoken\n",
+    "! pip install -q google-cloud-bigquery\n",
+    "! pip install -q pyyaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Standard Libraries\n",
+    "import json  \n",
+    "import os\n",
+    "import csv\n",
+    "import shutil\n",
+    "from itertools import islice\n",
+    "import concurrent.futures\n",
+    "import yaml\n",
+    "\n",
+    "# Third-Party Libraries\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from PyPDF2 import PdfReader\n",
+    "import tiktoken\n",
+    "from dotenv import load_dotenv\n",
+    "import pyperclip\n",
+    "\n",
+    "# OpenAI Libraries\n",
+    "from openai import OpenAI\n",
+    "\n",
+    "# Google Cloud Identity and Credentials\n",
+    "from google.auth import default\n",
+    "from google.cloud import bigquery\n",
+    "from google.cloud import functions_v1\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Configure GCP project\n",
+    "\n",
+    "If not already set-up, we'll install GCP CLI's, authenticate to GCP and set your default project."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Add gcloud to PATH\n",
+    "os.environ['PATH'] += os.pathsep + os.path.expanduser('~/google-cloud-sdk/bin')\n",
+    "\n",
+    "# Verify gcloud is in PATH\n",
+    "! gcloud --version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! gcloud auth application-default login"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "project_id = \"<insert_project_id>\"  # Replace with your actual project ID\n",
+    "! gcloud config set project {project_id}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! gcloud services enable cloudfunctions.googleapis.com\n",
+    "! gcloud services enable cloudbuild.googleapis.com\n",
+    "! gcloud services enable bigquery.googleapis.com"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Configure OpenAI settings\n",
+    "\n",
+    "This section guides you through setting up authentication for  OpenAI. Before going through this section, make sure you have your OpenAI API key."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "openai_api_key = os.environ.get(\"OPENAI_API_KEY\", \"<your OpenAI API key if not set as an env var>\") # Saving this as a variable to reference in function app in later step\n",
+    "openai_client = OpenAI(api_key=openai_api_key)\n",
+    "embeddings_model = \"text-embedding-3-small\" # We'll use this by default, but you can change to your text-embedding-3-large if desired"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Configure GCP BigQuery with Vector Search capabilities\n",
+    "\n",
+    "This section explains how to create a dataset in BigQuery and store vectors of float, used for embeddings & vector search."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from google.auth import default\n",
+    "\n",
+    "# Use default credentials\n",
+    "credentials, project_id = default()\n",
+    "region = \"us-central1\" # e.g: \"us-central1\"\n",
+    "print(\"Default Project ID:\", project_id)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Prepare data\n",
+    "We're going to embed and store a few pages of the OpenAI docs in the oai_docs folder. We'll first embed each, add it to a CSV, and then use that CSV to upload to the index."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We are going to use some techniques highlighted in [this cookbook](khttps://github.com/openai/openai-cookbook/blob/main/examples/Embedding_long_inputs.ipynb). This is a quick way to embed text, without taking into account variables like sections, using our vision model to describe images/graphs/diagrams, overlapping text between chunks for longer documents, etc. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to handle longer text files beyond the context of 8191 tokens, we can either use the chunk embeddings separately, or combine them in some way, such as averaging (weighted by the size of each chunk).\n",
+    "\n",
+    "We will take a function from Python's own cookbook that breaks up a sequence into chunks."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def batched(iterable, n):\n",
+    "    \"\"\"Batch data into tuples of length n. The last batch may be shorter.\"\"\"\n",
+    "    # batched('ABCDEFG', 3) --> ABC DEF G\n",
+    "    if n < 1:\n",
+    "        raise ValueError('n must be at least one')\n",
+    "    it = iter(iterable)\n",
+    "    while (batch := tuple(islice(it, n))):\n",
+    "        yield batch\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we define a function that encodes a string into tokens and then breaks it up into chunks. We'll use tiktoken, a fast open-source tokenizer by OpenAI.\n",
+    "\n",
+    "To read more about counting tokens with Tiktoken, check out [this cookbook](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken). \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chunked_tokens(text, chunk_length, encoding_name='cl100k_base'):\n",
+    "    # Get the encoding object for the specified encoding name. OpenAI's tiktoken library, which is used in this notebook, currently supports two encodings: 'bpe' and 'cl100k_base'. The 'bpe' encoding is used for GPT-3 and earlier models, while 'cl100k_base' is used for newer models like GPT-4.\n",
+    "    encoding = tiktoken.get_encoding(encoding_name)\n",
+    "    # Encode the input text into tokens\n",
+    "    tokens = encoding.encode(text)\n",
+    "    # Create an iterator that yields chunks of tokens of the specified length\n",
+    "    chunks_iterator = batched(tokens, chunk_length)\n",
+    "    # Yield each chunk from the iterator\n",
+    "    yield from chunks_iterator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, we can write a function that safely handles embedding requests, even when the input text is longer than the maximum context length, by chunking the input tokens and embedding each chunk individually. The average flag can be set to True to return the weighted average of the chunk embeddings, or False to simply return the unmodified list of chunk embeddings.\n",
+    "\n",
+    "> Note: there are other techniques you can take here, including:\n",
+    "> - using GPT-4o to capture images/chart descriptions for embedding\n",
+    "> - chunking based on paragraphs or sections\n",
+    "> - adding more descriptive metadata about each article."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "EMBEDDING_CTX_LENGTH = 8191\n",
+    "EMBEDDING_ENCODING='cl100k_base'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_embeddings(text, model):\n",
+    "    # Generate embeddings for the provided text using the specified model\n",
+    "    embeddings_response = openai_client.embeddings.create(model=model, input=text)\n",
+    "    # Extract the embedding data from the response\n",
+    "    embedding = embeddings_response.data[0].embedding\n",
+    "    return embedding\n",
+    "\n",
+    "def len_safe_get_embedding(text, model=embeddings_model, max_tokens=EMBEDDING_CTX_LENGTH, encoding_name=EMBEDDING_ENCODING):\n",
+    "    # Initialize lists to store embeddings and corresponding text chunks\n",
+    "    chunk_embeddings = []\n",
+    "    chunk_texts = []\n",
+    "    # Iterate over chunks of tokens from the input text\n",
+    "    for chunk in chunked_tokens(text, chunk_length=max_tokens, encoding_name=encoding_name):\n",
+    "        # Generate embeddings for each chunk and append to the list\n",
+    "        chunk_embeddings.append(generate_embeddings(chunk, model=model))\n",
+    "        # Decode the chunk back to text and append to the list\n",
+    "        chunk_texts.append(tiktoken.get_encoding(encoding_name).decode(chunk))\n",
+    "    # Return the list of chunk embeddings and the corresponding text chunks\n",
+    "    return chunk_embeddings, chunk_texts"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we can define a helper function that will capture additional metadata about the documents. In this example, I'll choose from a list of categories to use later on in a metadata filter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "categories = ['authentication','models','techniques','tools','setup','billing_limits','other']\n",
+    "\n",
+    "def categorize_text(text, categories):\n",
+    "\n",
+    "    # Create a prompt for categorization\n",
+    "    messages = [\n",
+    "        {\"role\": \"system\", \"content\": f\"\"\"You are an expert in LLMs, and you will be given text that corresponds to an article in OpenAI's documentation.\n",
+    "         Categorize the document into one of these categories: {', '.join(categories)}. Only respond with the category name and nothing else.\"\"\"},\n",
+    "        {\"role\": \"user\", \"content\": text}\n",
+    "    ]\n",
+    "    try:\n",
+    "        # Call the OpenAI API to categorize the text\n",
+    "        response = openai_client.chat.completions.create(\n",
+    "            model=\"gpt-4o\",\n",
+    "            messages=messages\n",
+    "        )\n",
+    "\n",
+    "        # Extract the category from the response\n",
+    "        category = response.choices[0].message.content\n",
+    "        return category\n",
+    "    except Exception as e:\n",
+    "        print(f\"Error categorizing text: {str(e)}\")\n",
+    "        return None\n",
+    "\n",
+    "# Example usage"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we can define some helper functions to process the .txt files in the oai_docs folder. Feel free to use this on your own data, this supports both .txt and .pdf files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def extract_text_from_pdf(pdf_path):\n",
+    "    # Initialize the PDF reader\n",
+    "    reader = PdfReader(pdf_path)\n",
+    "    text = \"\"\n",
+    "    # Iterate through each page in the PDF and extract text\n",
+    "    for page in reader.pages:\n",
+    "        text += page.extract_text()\n",
+    "    return text\n",
+    "\n",
+    "def process_file(file_path, idx, categories, embeddings_model):\n",
+    "    file_name = os.path.basename(file_path)\n",
+    "    print(f\"Processing file {idx + 1}: {file_name}\")\n",
+    "    \n",
+    "    # Read text content from .txt files\n",
+    "    if file_name.endswith('.txt'):\n",
+    "        with open(file_path, 'r', encoding='utf-8') as file:\n",
+    "            text = file.read()\n",
+    "    # Extract text content from .pdf files\n",
+    "    elif file_name.endswith('.pdf'):\n",
+    "        text = extract_text_from_pdf(file_path)\n",
+    "    \n",
+    "    title = file_name\n",
+    "    # Generate embeddings for the title\n",
+    "    title_vectors, title_text = len_safe_get_embedding(title, embeddings_model)\n",
+    "    print(f\"Generated title embeddings for {file_name}\")\n",
+    "    \n",
+    "    # Generate embeddings for the content\n",
+    "    content_vectors, content_text = len_safe_get_embedding(text, embeddings_model)\n",
+    "    print(f\"Generated content embeddings for {file_name}\")\n",
+    "    \n",
+    "    category = categorize_text(' '.join(content_text), categories)\n",
+    "    print(f\"Categorized {file_name} as {category}\")\n",
+    "    \n",
+    "    # Prepare the data to be appended\n",
+    "    data = []\n",
+    "    for i, content_vector in enumerate(content_vectors):\n",
+    "        data.append({\n",
+    "            \"id\": f\"{idx}_{i}\",\n",
+    "            \"vector_id\": f\"{idx}_{i}\",\n",
+    "            \"title\": title_text[0],\n",
+    "            \"text\": content_text[i],\n",
+    "            \"title_vector\": json.dumps(title_vectors[0]),  # Assuming title is short and has only one chunk\n",
+    "            \"content_vector\": json.dumps(content_vector),\n",
+    "            \"category\": category\n",
+    "        })\n",
+    "        print(f\"Appended data for chunk {i + 1}/{len(content_vectors)} of {file_name}\")\n",
+    "    \n",
+    "    return data\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We'll now use this helper function to process our OpenAI documentation. Feel free to update this to use your own data by changing the folder in process_files below.\n",
+    "\n",
+    "Note that this will process the documents in chosen folder concurrently, so this should take <30 seconds if using txt files, and slightly longer if using PDFs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Customize the location below if you are using different data besides the OpenAI documentation. Note that if you are using a different dataset, you will need to update the categories list as well.\n",
+    "folder_name = \"../../../data/oai_docs\"\n",
+    "\n",
+    "files = [os.path.join(folder_name, f) for f in os.listdir(folder_name) if f.endswith('.txt') or f.endswith('.pdf')]\n",
+    "data = []\n",
+    "\n",
+    "# Process each file concurrently\n",
+    "with concurrent.futures.ThreadPoolExecutor() as executor:\n",
+    "    futures = {executor.submit(process_file, file_path, idx, categories, embeddings_model): idx for idx, file_path in enumerate(files)}\n",
+    "    for future in concurrent.futures.as_completed(futures):\n",
+    "        try:\n",
+    "            result = future.result()\n",
+    "            data.extend(result)\n",
+    "        except Exception as e:\n",
+    "            print(f\"Error processing file: {str(e)}\")\n",
+    "\n",
+    "# Write the data to a CSV file\n",
+    "csv_file = os.path.join(\"..\", \"embedded_data.csv\")\n",
+    "with open(csv_file, 'w', newline='', encoding='utf-8') as csvfile:\n",
+    "    fieldnames = [\"id\", \"vector_id\", \"title\", \"text\", \"title_vector\", \"content_vector\",\"category\"]\n",
+    "    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)\n",
+    "    writer.writeheader()\n",
+    "    for row in data:\n",
+    "        writer.writerow(row)\n",
+    "        print(f\"Wrote row with id {row['id']} to CSV\")\n",
+    "\n",
+    "# Convert the CSV file to a Dataframe\n",
+    "article_df = pd.read_csv(\"../embedded_data.csv\")\n",
+    "# Read vectors from strings back into a list using json.loads\n",
+    "article_df[\"title_vector\"] = article_df.title_vector.apply(json.loads)\n",
+    "article_df[\"content_vector\"] = article_df.content_vector.apply(json.loads)\n",
+    "article_df[\"vector_id\"] = article_df[\"vector_id\"].apply(str)\n",
+    "article_df[\"category\"] = article_df[\"category\"].apply(str)\n",
+    "article_df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now have an `embedded_data.csv` file with six columns that we can upload to our vector database! "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Create BigQuery table with Vector Search\n",
+    "\n",
+    "## Create BigQuery dataset\n",
+    "\n",
+    "We'll leverage Google SDK and create a dataset named \"oai_docs\" with a table name of \"embedded_data\", but feel free to change those variables (you can also change regions).\n",
+    "\n",
+    "*PS: We won't create a BigQuery index, that could improve the performance of the vector search, because such index requires more than 1k rows in our dataset which we don't have in our example, but feel free to leverage that for your own use-case.*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create bigquery table\n",
+    "\n",
+    "from google.cloud import bigquery\n",
+    "from google.api_core.exceptions import Conflict\n",
+    "\n",
+    "# Define the dataset ID (project_id.dataset_id)\n",
+    "raw_dataset_id = 'oai_docs'\n",
+    "dataset_id = project_id + '.' + raw_dataset_id\n",
+    "\n",
+    "client = bigquery.Client(credentials=credentials, project=project_id)\n",
+    "\n",
+    "# Construct a full Dataset object to send to the API\n",
+    "dataset = bigquery.Dataset(dataset_id)\n",
+    "\n",
+    "# Specify the geographic location where the dataset should reside\n",
+    "dataset.location = \"US\"\n",
+    "\n",
+    "# Send the dataset to the API for creation\n",
+    "try:\n",
+    "    dataset = client.create_dataset(dataset, timeout=30)\n",
+    "    print(f\"Created dataset {client.project}.{dataset.dataset_id}\")\n",
+    "except Conflict:\n",
+    "    print(f\"dataset {dataset.dataset_id } already exists\")\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read the CSV file, properly handling multiline fields\n",
+    "csv_file_path = \"../embedded_data.csv\"\n",
+    "df = pd.read_csv(csv_file_path, engine='python', quotechar='\"', quoting=1)\n",
+    "\n",
+    "# Display the first few rows of the dataframe\n",
+    "df.head()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Creating table and upload data\n",
+    "\n",
+    "We'll create the table with the attribute name and types. Note the 'content_vector' attribute that allows to store a vector of float for a single row, which we'll use for our vector search.\n",
+    "\n",
+    "This code will then loop on our CSVs previously created to insert the rows into Bigquery. \n",
+    "If you run this code multiple time, multiple identical rows will be inserted which will give less accurate results when doing search (you could put uniqueness on IDs or clean the DB each time)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read the CSV file, properly handling multiline fields\n",
+    "dataset_id = project_id + '.' + raw_dataset_id\n",
+    "client = bigquery.Client(credentials=credentials, project=project_id)\n",
+    "csv_file_path = \"../embedded_data.csv\"\n",
+    "df = pd.read_csv(csv_file_path, engine='python', quotechar='\"', quoting=1)\n",
+    "\n",
+    "# Preprocess the data to ensure content_vector is correctly formatted\n",
+    "# removing last and first character which are brackets [], comma splitting and converting to float\n",
+    "def preprocess_content_vector(row):\n",
+    "    row['content_vector'] = [float(x) for x in row['content_vector'][1:-1].split(',')]\n",
+    "    return row\n",
+    "\n",
+    "# Apply preprocessing to the dataframe\n",
+    "df = df.apply(preprocess_content_vector, axis=1)\n",
+    "\n",
+    "# Define the schema of the final table\n",
+    "final_schema = [\n",
+    "    bigquery.SchemaField(\"id\", \"STRING\"),\n",
+    "    bigquery.SchemaField(\"vector_id\", \"STRING\"),\n",
+    "    bigquery.SchemaField(\"title\", \"STRING\"),\n",
+    "    bigquery.SchemaField(\"text\", \"STRING\"),\n",
+    "    bigquery.SchemaField(\"title_vector\", \"STRING\"),\n",
+    "    bigquery.SchemaField(\"content_vector\", \"FLOAT64\", mode=\"REPEATED\"),\n",
+    "    bigquery.SchemaField(\"category\", \"STRING\"),\n",
+    "]\n",
+    "\n",
+    "# Define the final table ID\n",
+    "raw_table_id = 'embedded_data'\n",
+    "final_table_id = f'{dataset_id}.' + raw_table_id\n",
+    "\n",
+    "# Create the final table object\n",
+    "final_table = bigquery.Table(final_table_id, schema=final_schema)\n",
+    "\n",
+    "# Send the table to the API for creation\n",
+    "final_table = client.create_table(final_table, exists_ok=True)  # API request\n",
+    "print(f\"Created final table {project_id}.{final_table.dataset_id}.{final_table.table_id}\")\n",
+    "\n",
+    "# Convert DataFrame to list of dictionaries for BigQuery insertion\n",
+    "rows_to_insert = df.to_dict(orient='records')\n",
+    "\n",
+    "# Upload data to the final table\n",
+    "errors = client.insert_rows_json(f\"{final_table.dataset_id}.{final_table.table_id}\", rows_to_insert)  # API request\n",
+    "\n",
+    "if errors:\n",
+    "    print(f\"Encountered errors while inserting rows: {errors}\")\n",
+    "else:\n",
+    "    print(f\"Successfully loaded data into {dataset_id}:{final_table_id}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test search\n",
+    "Now that the data is uploaded, we'll test both pure vector similarity search and with metadata filtering locally below to make sure it is working as expected.\n",
+    "\n",
+    "You can test both a pure vector search and metadata filtering.\n",
+    "\n",
+    "The query below is pure vector search, where we don't filter out on category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = \"What model should I use to embed?\"\n",
+    "category = \"models\"\n",
+    "\n",
+    "embedding_query = generate_embeddings(query, embeddings_model)\n",
+    "embedding_query_list = ', '.join(map(str, embedding_query))\n",
+    "\n",
+    "query = f\"\"\"\n",
+    "WITH search_results AS (\n",
+    "  SELECT query.id AS query_id, base.id AS base_id, distance\n",
+    "  FROM VECTOR_SEARCH(\n",
+    "    TABLE oai_docs.embedded_data, 'content_vector',\n",
+    "    (SELECT ARRAY[{embedding_query_list}] AS content_vector, 'query_vector' AS id),\n",
+    "    top_k => 2, distance_type => 'COSINE', options => '{{\"use_brute_force\": true}}')\n",
+    ")\n",
+    "SELECT sr.query_id, sr.base_id, sr.distance, ed.text, ed.title\n",
+    "FROM search_results sr\n",
+    "JOIN oai_docs.embedded_data ed ON sr.base_id = ed.id\n",
+    "ORDER BY sr.distance ASC\n",
+    "\"\"\"\n",
+    "\n",
+    "query_job = client.query(query)\n",
+    "results = query_job.result()  # Wait for the job to complete\n",
+    "\n",
+    "for row in results:\n",
+    "    print(f\"query_id: {row['query_id']}, base_id: {row['base_id']}, distance: {row['distance']}, text_truncated: {row['text'][0:100]}\")\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Perform search with metadata filtering\n",
+    "Metadata filtering allows to restrict findings that have certain attributes on top of having the closest semantic findings of vector search.\n",
+    "\n",
+    "The provided code snippet demonstrates how to execute a query with metadata filtering:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "query = \"What model should I use to embed?\"\n",
+    "category = \"models\"\n",
+    "\n",
+    "embedding_query = generate_embeddings(query, embeddings_model)\n",
+    "embedding_query_list = ', '.join(map(str, embedding_query))\n",
+    "\n",
+    "\n",
+    "query = f\"\"\"\n",
+    "WITH search_results AS (\n",
+    "  SELECT query.id AS query_id, base.id AS base_id, distance\n",
+    "  FROM VECTOR_SEARCH(\n",
+    "    (SELECT * FROM oai_docs.embedded_data WHERE category = '{category}'), \n",
+    "    'content_vector',\n",
+    "    (SELECT ARRAY[{embedding_query_list}] AS content_vector, 'query_vector' AS id),\n",
+    "    top_k => 4, distance_type => 'COSINE', options => '{{\"use_brute_force\": true}}')\n",
+    ")\n",
+    "SELECT sr.query_id, sr.base_id, sr.distance, ed.text, ed.title, ed.category\n",
+    "FROM search_results sr\n",
+    "JOIN oai_docs.embedded_data ed ON sr.base_id = ed.id\n",
+    "ORDER BY sr.distance ASC\n",
+    "\"\"\"\n",
+    "\n",
+    "\n",
+    "query_job = client.query(query)\n",
+    "results = query_job.result()  # Wait for the job to complete\n",
+    "\n",
+    "for row in results:\n",
+    "    print(f\"category: {row['category']}, title: {row['title']}, base_id: {row['base_id']}, distance: {row['distance']}, text_truncated: {row['text'][0:100]}\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Create GCP function\n",
+    "\n",
+    "## Exporting variables\n",
+    "\n",
+    "We'll deploy the function in `main.py` in this folder (also available [here](https://github.com/openai/openai-cookbook/blob/main/examples/chatgpt/rag-quickstart/gcp/main.py)).\n",
+    "\n",
+    "In a first step, we'll export the variables to target our table/dataset as well as to generate Embeddings using OpenAI's API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a dictionary to store the environment variables (they were used previously and are just retrieved)\n",
+    "env_variables = {\n",
+    "    'OPENAI_API_KEY': openai_api_key,\n",
+    "    'EMBEDDINGS_MODEL': embeddings_model,\n",
+    "    'PROJECT_ID': project_id,\n",
+    "    'DATASET_ID': raw_dataset_id,\n",
+    "    'TABLE_ID': raw_table_id\n",
+    "}\n",
+    "\n",
+    "# Write the environment variables to a YAML file\n",
+    "with open('env.yml', 'w') as yaml_file:\n",
+    "    yaml.dump(env_variables, yaml_file, default_flow_style=False)\n",
+    "\n",
+    "print(\"env.yml file created successfully.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Deploying the function\n",
+    "\n",
+    "We will now create a google function called \"openai_docs_search\" for our current project, for that we'll launch the CLI command below, leveraging the previously created environment variables. Note that this function can be called from everywhere without authentication, do not use that for production or add additional authentication mechanism."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! gcloud functions deploy openai_docs_search \\\n",
+    "  --runtime python39 \\\n",
+    "  --trigger-http \\\n",
+    "  --allow-unauthenticated \\\n",
+    "  --env-vars-file env.yml"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Input in a Custom GPT in ChatGPT\n",
+    "\n",
+    "Now that we have a GCP Function that queries this Vector Search Index, let's put it as a GPT Action!\n",
+    "\n",
+    "See documentation [here](https://openai.com/index/introducing-gpts/) on GPTs and [here](https://platform.openai.com/docs/actions) on GPT Actions. Use the below as the instructions for the GPT and as the OpenAPI spec for the GPT Action.\n",
+    "\n",
+    "## Create OpenAPI Spec\n",
+    "\n",
+    "Below is a sample OpenAPI spec. When we run the block below, a functional spec should be copied to the clipboard to paste in the GPT Action.\n",
+    "\n",
+    "Note that this does not have any authentication by default, but you can set up GCP Functions with Auth by following GCP's docs [here](https://cloud.google.com/functions/docs/securing/authenticating)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "spec = f\"\"\"\n",
+    "openapi: 3.1.0\n",
+    "info:\n",
+    "  title: OpenAI API documentation search\n",
+    "  description: API to perform a semantic search over OpenAI APIs\n",
+    "  version: 1.0.0\n",
+    "servers:\n",
+    "  - url: https://{region}-{project_id}.cloudfunctions.net\n",
+    "    description: Main (production) server\n",
+    "paths:\n",
+    "  /openai_docs_search:\n",
+    "    post:\n",
+    "      operationId: openai_docs_search\n",
+    "      summary: Perform a search\n",
+    "      description: Returns search results for the given query parameters.\n",
+    "      requestBody:\n",
+    "        required: true\n",
+    "        content:\n",
+    "          application/json:\n",
+    "            schema:\n",
+    "              type: object\n",
+    "              properties:\n",
+    "                query:\n",
+    "                  type: string\n",
+    "                  description: The search query string\n",
+    "                top_k:\n",
+    "                  type: integer\n",
+    "                  description: Number of top results to return. Maximum is 3.\n",
+    "                category:\n",
+    "                  type: string\n",
+    "                  description: The category to filter on, on top of similarity search (used for metadata filtering). Possible values are {categories}.\n",
+    "      responses:\n",
+    "        '200':\n",
+    "          description: A JSON response with the search results\n",
+    "          content:\n",
+    "            application/json:\n",
+    "              schema:\n",
+    "                type: object\n",
+    "                properties:\n",
+    "                  items:\n",
+    "                    type: array\n",
+    "                    items:\n",
+    "                      type: object\n",
+    "                      properties:\n",
+    "                        text:\n",
+    "                          type: string\n",
+    "                          example: \"Learn how to turn text into numbers, unlocking use cases like search...\"\n",
+    "                        title:\n",
+    "                          type: string\n",
+    "                          example: \"embeddings.txt\"\n",
+    "                        distance:\n",
+    "                          type: number\n",
+    "                          format: float\n",
+    "                          example: 0.484939891778730\n",
+    "                        category:\n",
+    "                          type: string\n",
+    "                          example: \"models\"\n",
+    "\"\"\"\n",
+    "print(spec)\n",
+    "pyperclip.copy(spec)\n",
+    "print(\"OpenAPI spec copied to clipboard\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create GPT Instructions\n",
+    "\n",
+    "Feel free to modify instructions as you see fit. Check out our docs [here](https://platform.openai.com/docs/guides/prompt-engineering) for some tips on prompt engineering."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "instructions = f'''\n",
+    "You are an OpenAI docs assistant. You have an action in your knowledge base where you can make a POST request to search for information. The POST request should always include: {{\n",
+    "    \"query\": \"<user_query>\",\n",
+    "    \"k_\": <integer>,\n",
+    "    \"category\": <string, but optional>\n",
+    "}}. Your goal is to assist users by performing searches using this POST request and providing them with relevant information based on the query.\n",
+    "\n",
+    "You must only include knowledge you get from your action in your response.\n",
+    "The category must be from the following list: {categories}, which you should determine based on the user's query. If you cannot determine, then do not include the category in the POST request.\n",
+    "'''\n",
+    "pyperclip.copy(instructions)\n",
+    "print(\"GPT Instructions copied to clipboard\")\n",
+    "print(instructions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Recap\n",
+    "\n",
+    "We've now succesfully integrated GCP BigQuery Vector Search with GPT Actions in ChatGPT by doing the following:\n",
+    "1. Embedded docs using OpenAI's embeddings, while adding some additional metadata using gpt-4o.\n",
+    "2. Uploaded that data to GCP BigQuery (raw data and vectors of embeddings)\n",
+    "3. Created an endpoint on GCP Functions to retrieve those\n",
+    "4. Incorporated it into a custom GPT.\n",
+    "\n",
+    "Our GPT can now retrieve informaiton to help answer user queries, making it much more accurate and customized to our data. Here's the GPT in action:"
+   ]
+  },
+  {
+   "attachments": {
+    "b7ce9891-c0f4-4e45-a3c1-168098de250e.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:b7ce9891-c0f4-4e45-a3c1-168098de250e.png)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/examples/chatgpt/rag-quickstart/gcp/main.py b/examples/chatgpt/rag-quickstart/gcp/main.py
new file mode 100644
index 0000000..b1630dc
--- /dev/null
+++ b/examples/chatgpt/rag-quickstart/gcp/main.py
@@ -0,0 +1,77 @@
+from google.cloud import bigquery
+import functions_framework
+import os
+from openai import OpenAI
+import json
+
+openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+embeddings_model = os.getenv('EMBEDDINGS_MODEL')
+project_id = os.getenv('PROJECT_ID')
+dataset_id = os.getenv('DATASET_ID')
+table_id = os.getenv('TABLE_ID')
+
+def generate_embeddings(text, model):
+    print(f'Generating embedding for: {text}')
+    # Generate embeddings for the provided text using the specified model
+    embeddings_response = openai_client.embeddings.create(model=model, input=text)
+    # Extract the embedding data from the response
+    embedding = embeddings_response.data[0].embedding
+    return embedding
+
+@functions_framework.http
+def openai_docs_search(request):
+    print('received a request')
+    client = bigquery.Client()
+    
+    request_json = request.get_json(silent=True)
+    print(request_json)
+    
+    if not request_json:
+        return json.dumps({"error": "Invalid JSON in request"}), 400, {'Content-Type': 'application/json'}
+    
+    query = request_json.get('query')
+    top_k = request_json.get('top_k', 3)
+    category = request_json.get('category', '')
+
+    if not query:
+        return json.dumps({"error": "Query parameter is required"}), 400, {'Content-Type': 'application/json'}
+    
+    embedding_query = generate_embeddings(query, embeddings_model)
+    embedding_query_list = ', '.join(map(str, embedding_query))
+    
+    sql_query = f"""
+    WITH search_results AS (
+        SELECT query.id AS query_id, base.id AS base_id, distance
+        FROM VECTOR_SEARCH(
+            TABLE `{project_id}.{dataset_id}.{table_id}`, 'content_vector',
+            (SELECT ARRAY[{embedding_query_list}] AS content_vector, 'query_vector' AS id),
+            top_k => {top_k}, distance_type => 'COSINE', options => '{{"use_brute_force": true}}')
+    )
+    SELECT sr.query_id, sr.base_id, sr.distance, ed.text, ed.title, ed.category
+    FROM search_results sr
+    JOIN `{project_id}.{dataset_id}.{table_id}` ed ON sr.base_id = ed.id
+    """
+    
+    if category:
+        sql_query += f" WHERE ed.category = '{category}'"
+
+    sql_query += " ORDER BY sr.distance;"
+    
+    query_job = client.query(sql_query)  # Make an API request.
+    
+    rows = []
+    for row in query_job:
+        print(row.title)
+        rows.append({
+            "text": row.text,
+            "title": row.title,
+            "distance": row.distance,
+            "category": row.category
+        })
+
+    response = {
+        "items": rows
+    }
+    print('sending response')
+    print(len(rows))
+    return json.dumps(response), 200
\ No newline at end of file
diff --git a/examples/chatgpt/rag-quickstart/gcp/requirements.txt b/examples/chatgpt/rag-quickstart/gcp/requirements.txt
new file mode 100644
index 0000000..142fb22
--- /dev/null
+++ b/examples/chatgpt/rag-quickstart/gcp/requirements.txt
@@ -0,0 +1,3 @@
+google-cloud-bigquery
+functions-framework
+openai
\ No newline at end of file
diff --git a/registry.yaml b/registry.yaml
index 72bb853..790d918 100644
--- a/registry.yaml
+++ b/registry.yaml
@@ -1457,6 +1457,18 @@
     - gpt-actions-library
     - chatgpt
 
+- title: GCP BigQuery Vector Search with GCP Functions and GPT Actions in ChatGPT
+  path: examples/chatgpt/rag-quickstart/gcp/Getting_started_with_bigquery_vector_search_and_openai.ipynb
+  date: 2024-08-02
+  authors:
+    - pap-openai
+    - maxreid-openai
+  tags:
+    - embeddings
+    - chatgpt
+    - tiktoken
+    - completions
+
 - title: GPT Actions library - Zapier
   path: examples/chatgpt/gpt_actions_library/gpt_action_zapier.ipynb
   date: 2024-08-05