{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "## Get embeddings\n",
    "\n",
    "The function `get_embedding` will give us an embedding for an input text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1536"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import openai\n",
    "\n",
    "embedding = openai.Embedding.create(\n",
    "    input=\"Your text goes here\", model=\"text-embedding-ada-002\"\n",
    ")[\"data\"][0][\"embedding\"]\n",
    "len(embedding)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1536\n"
     ]
    }
   ],
   "source": [
    "import openai\n",
    "from tenacity import retry, wait_random_exponential, stop_after_attempt\n",
    "\n",
    "\n",
    "@retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))\n",
    "def get_embedding(text: str, model=\"text-embedding-ada-002\") -> list[float]:\n",
    "    return openai.Embedding.create(input=[text], model=model)[\"data\"][0][\"embedding\"]\n",
    "\n",
    "\n",
    "embedding = get_embedding(\"Your text goes here\", model=\"text-embedding-ada-002\")\n",
    "print(len(embedding))\n"
   ]
  }
 ],
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