langchain/docs/extras/integrations/chat/ernie.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ERNIE-Bot Chat\n",
    "\n",
    "This notebook covers how to get started with Ernie chat models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.chat_models import ErnieBotChat\n",
    "from langchain.schema import AIMessage, HumanMessage, SystemMessage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat = ErnieBotChat(ernie_client_id='YOUR_CLIENT_ID', ernie_client_secret='YOUR_CLIENT_SECRET')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or you can set `client_id` and `client_secret` in your environment variables\n",
    "```bash\n",
    "export ERNIE_CLIENT_ID=YOUR_CLIENT_ID\n",
    "export ERNIE_CLIENT_SECRET=YOUR_CLIENT_SECRET\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='Hello, I am an artificial intelligence language model. My purpose is to help users answer questions or provide information. What can I do for you?', additional_kwargs={}, example=False)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat([\n",
    "    HumanMessage(content='hello there, who are you?')\n",
    "])"
   ]
  }
 ],
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