{
 "cells": [
  {
   "cell_type": "markdown",
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   },
   "source": [
    "# GigaChat\n",
    "This notebook shows how to use LangChain with [GigaChat](https://developers.sber.ru/portal/products/gigachat).\n",
    "To use you need to install ```gigachat``` python package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%pip install --upgrade --quiet  gigachat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "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/api/integration)\n",
    "## Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from getpass import getpass\n",
    "\n",
    "os.environ[\"GIGACHAT_CREDENTIALS\"] = getpass()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from langchain_community.llms import GigaChat\n",
    "\n",
    "llm = GigaChat(verify_ssl_certs=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The capital of Russia is Moscow.\n"
     ]
    }
   ],
   "source": [
    "from langchain.chains import LLMChain\n",
    "from langchain.prompts import PromptTemplate\n",
    "\n",
    "template = \"What is capital of {country}?\"\n",
    "\n",
    "prompt = PromptTemplate(template=template, input_variables=[\"country\"])\n",
    "\n",
    "llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
    "\n",
    "generated = llm_chain.run(country=\"Russia\")\n",
    "print(generated)"
   ]
  }
 ],
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