Added SingleStoreDB Vector Store (#5619)

- Added `SingleStoreDB` vector store, which is a wrapper over the
SingleStore DB database, that can be used as a vector storage and has an
efficient similarity search.
- Added integration tests for the vector store
- Added jupyter notebook with the example

@dev2049

---------

Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

docs/modules/indexes/vectorstores/examples/singlestoredb.ipynb

@@ -0,0 +1,139 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2b9582dc",
+   "metadata": {},
+   "source": [
+    "# SingleStoreDB vector search\n",
+    "[SingleStore DB](https://singlestore.com) is a high-performance distributed database that supports deployment both in the [cloud](https://www.singlestore.com/cloud/) and on-premises. For a significant duration, it has provided support for vector functions such as [dot_product](https://docs.singlestore.com/managed-service/en/reference/sql-reference/vector-functions/dot_product.html), thereby positioning itself as an ideal solution for AI applications that require text similarity matching. \n",
+    "This tutorial illustrates how to utilize the features of the SingleStore DB Vector Store."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e4a61a4d",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Establishing a connection to the database is facilitated through the singlestoredb Python connector.\n",
+    "# Please ensure that this connector is installed in your working environment.\n",
+    "!pip install singlestoredb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "39a0132a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import getpass\n",
+    "\n",
+    "# We want to use OpenAIEmbeddings so we have to get the OpenAI API Key.\n",
+    "os.environ['OPENAI_API_KEY'] = getpass.getpass('OpenAI API Key:')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6104fde8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
+    "from langchain.text_splitter import CharacterTextSplitter\n",
+    "from langchain.vectorstores import SingleStoreDB\n",
+    "from langchain.document_loaders import TextLoader"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7b45113c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load text samples \n",
+    "from langchain.document_loaders import TextLoader\n",
+    "loader = TextLoader('../../../state_of_the_union.txt')\n",
+    "documents = loader.load()\n",
+    "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
+    "docs = text_splitter.split_documents(documents)\n",
+    "\n",
+    "embeddings = OpenAIEmbeddings()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "535b2687",
+   "metadata": {},
+   "source": [
+    "There are several ways to establish a [connection](https://singlestoredb-python.labs.singlestore.com/generated/singlestoredb.connect.html) to the database. You can either set up environment variables or pass named parameters to the `SingleStoreDB constructor`. Alternatively, you may provide these parameters to the `from_documents` and `from_texts` methods."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d0b316bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setup connection url as environment variable\n",
+    "os.environ['SINGLESTOREDB_URL'] = 'root:pass@localhost:3306/db'\n",
+    "\n",
+    "# Load documents to the store\n",
+    "docsearch = SingleStoreDB.from_documents(\n",
+    "    docs,\n",
+    "    embeddings,\n",
+    "    table_name = \"noteook\", # use table with a custom name \n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0eaa4297",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = \"What did the president say about Ketanji Brown Jackson\"\n",
+    "docs = docsearch.similarity_search(query) # Find documents that correspond to the query\n",
+    "print(docs[0].page_content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "86efff90",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.9.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}