langchain/docs/docs/integrations/text_embedding/gigachat.ipynb

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  {
   "cell_type": "markdown",
   "source": [
    "# GigaChat\n",
    "This notebook shows how to use LangChain with [GigaChat embeddings](https://developers.sber.ru/portal/products/gigachat).\n",
    "To use you need to install ```gigachat``` python package."
   ],
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%pip install --upgrade --quiet  gigachat"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
    "\n",
    "## Example"
   ],
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   "source": [
    "import os\n",
    "from getpass import getpass\n",
    "\n",
    "os.environ[\"GIGACHAT_CREDENTIALS\"] = getpass()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [],
   "source": [
    "from langchain_community.embeddings import GigaChatEmbeddings\n",
    "\n",
    "embeddings = GigaChatEmbeddings(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "query_result = embeddings.embed_query(\"The quick brown fox jumps over the lazy dog\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "[0.8398333191871643,\n -0.14180311560630798,\n -0.6161925792694092,\n -0.17103666067123413,\n 1.2884578704833984]"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "query_result[:5]"
   ],
   "metadata": {
    "collapsed": false
   }
  }
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