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+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: Astra DB\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Astra DB\n",
+    "\n",
+    "DataStax [Astra DB](https://docs.datastax.com/en/astra/home/astra.html) is a serverless vector-capable database built on Cassandra and made conveniently available through an easy-to-use JSON API.\n",
+    "\n",
+    "`AstraDBStore` and `AstraDBByteStore` need the `astrapy` package to be installed:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "%pip install --upgrade --quiet  astrapy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The Store takes the following parameters:\n",
+    "\n",
+    "* `api_endpoint`: Astra DB API endpoint. Looks like `https://01234567-89ab-cdef-0123-456789abcdef-us-east1.apps.astra.datastax.com`\n",
+    "* `token`: Astra DB token. Looks like `AstraCS:6gBhNmsk135....`\n",
+    "* `collection_name` : Astra DB collection name\n",
+    "* `namespace`: (Optional) Astra DB namespace"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## AstraDBStore\n",
+    "\n",
+    "The `AstraDBStore` is an implementation of `BaseStore` that stores everything in your DataStax Astra DB instance.\n",
+    "The store keys must be strings and will be mapped to the `_id` field of the Astra DB document.\n",
+    "The store values can be any object that can be serialized by `json.dumps`.\n",
+    "In the database, entries will have the form:\n",
+    "\n",
+    "```json\n",
+    "{\n",
+    "  \"_id\": \"<key>\",\n",
+    "  \"value\": <value>\n",
+    "}\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.storage import AstraDBStore"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from getpass import getpass\n",
+    "\n",
+    "ASTRA_DB_API_ENDPOINT = input(\"ASTRA_DB_API_ENDPOINT = \")\n",
+    "ASTRA_DB_APPLICATION_TOKEN = getpass(\"ASTRA_DB_APPLICATION_TOKEN = \")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "store = AstraDBStore(\n",
+    "    api_endpoint=ASTRA_DB_API_ENDPOINT,\n",
+    "    token=ASTRA_DB_APPLICATION_TOKEN,\n",
+    "    collection_name=\"my_store\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['v1', [0.1, 0.2, 0.3]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "store.mset([(\"k1\", \"v1\"), (\"k2\", [0.1, 0.2, 0.3])])\n",
+    "print(store.mget([\"k1\", \"k2\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Usage with CacheBackedEmbeddings\n",
+    "\n",
+    "You may use the `AstraDBStore` in conjunction with a [`CacheBackedEmbeddings`](/docs/modules/data_connection/text_embedding/caching_embeddings) to cache the result of embeddings computations.\n",
+    "Note that `AstraDBStore` stores the embeddings as a list of floats without converting them first to bytes so we don't use `fromByteStore` there."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.embeddings import CacheBackedEmbeddings, OpenAIEmbeddings\n",
+    "\n",
+    "embeddings = CacheBackedEmbeddings(\n",
+    "    underlying_embeddings=OpenAIEmbeddings(), document_embedding_store=store\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## AstraDBByteStore\n",
+    "\n",
+    "The `AstraDBByteStore` is an implementation of `ByteStore` that stores everything in your DataStax Astra DB instance.\n",
+    "The store keys must be strings and will be mapped to the `_id` field of the Astra DB document.\n",
+    "The store `bytes` values are converted to base64 strings for storage into Astra DB.\n",
+    "In the database, entries will have the form:\n",
+    "\n",
+    "```json\n",
+    "{\n",
+    "  \"_id\": \"<key>\",\n",
+    "  \"value\": \"bytes encoded in base 64\"\n",
+    "}\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.storage import AstraDBByteStore"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from getpass import getpass\n",
+    "\n",
+    "ASTRA_DB_API_ENDPOINT = input(\"ASTRA_DB_API_ENDPOINT = \")\n",
+    "ASTRA_DB_APPLICATION_TOKEN = getpass(\"ASTRA_DB_APPLICATION_TOKEN = \")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "store = AstraDBByteStore(\n",
+    "    api_endpoint=ASTRA_DB_API_ENDPOINT,\n",
+    "    token=ASTRA_DB_APPLICATION_TOKEN,\n",
+    "    collection_name=\"my_store\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[b'v1', b'v2']\n"
+     ]
+    }
+   ],
+   "source": [
+    "store.mset([(\"k1\", b\"v1\"), (\"k2\", b\"v2\")])\n",
+    "print(store.mget([\"k1\", \"k2\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}