{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2c591a6a42ac7f0",
   "metadata": {},
   "source": [
    "# Bookend AI\n",
    "\n",
    "Let's load the Bookend AI Embeddings class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d94c62b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_community.embeddings import BookendEmbeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "523a09e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "embeddings = BookendEmbeddings(\n",
    "    domain=\"your_domain\",\n",
    "    api_token=\"your_api_token\",\n",
    "    model_id=\"your_embeddings_model_id\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b212bd5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "text = \"This is a test document.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "57db66bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "query_result = embeddings.embed_query(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b790fd09",
   "metadata": {},
   "outputs": [],
   "source": [
    "doc_result = embeddings.embed_documents([text])"
   ]
  }
 ],
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   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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