{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.agents import AgentType\n",
    "from langchain.chat_models import ChatOpenAI\n",
    "from langchain.agents import initialize_agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.agents.agent_toolkits import PlayWrightBrowserToolkit\n",
    "from langchain.tools.playwright.utils import (\n",
    "    create_async_playwright_browser,\n",
    "    create_sync_playwright_browser, # A synchronous browser is available, though it isn't compatible with jupyter.\n",
    ")\n",
    "\n",
    "# This import is required only for jupyter notebooks, since they have their own eventloop\n",
    "import nest_asyncio\n",
    "nest_asyncio.apply()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'playwright'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[3], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m async_browser \u001b[39m=\u001b[39m create_async_playwright_browser()\n\u001b[1;32m      2\u001b[0m browser_toolkit \u001b[39m=\u001b[39m PlayWrightBrowserToolkit\u001b[39m.\u001b[39mfrom_browser(async_browser\u001b[39m=\u001b[39masync_browser)\n\u001b[1;32m      3\u001b[0m tools \u001b[39m=\u001b[39m browser_toolkit\u001b[39m.\u001b[39mget_tools()\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/openai/lib/python3.10/site-packages/langchain/tools/playwright/utils.py:37\u001b[0m, in \u001b[0;36mcreate_async_playwright_browser\u001b[0;34m()\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcreate_async_playwright_browser\u001b[39m() \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m AsyncBrowser:\n\u001b[0;32m---> 37\u001b[0m     \u001b[39mfrom\u001b[39;00m \u001b[39mplaywright\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39masync_api\u001b[39;00m \u001b[39mimport\u001b[39;00m async_playwright\n\u001b[1;32m     39\u001b[0m     browser \u001b[39m=\u001b[39m run_async(async_playwright()\u001b[39m.\u001b[39mstart())\n\u001b[1;32m     40\u001b[0m     \u001b[39mreturn\u001b[39;00m run_async(browser\u001b[39m.\u001b[39mchromium\u001b[39m.\u001b[39mlaunch(headless\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m))\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'playwright'"
     ]
    }
   ],
   "source": [
    "async_browser = create_async_playwright_browser()\n",
    "browser_toolkit = PlayWrightBrowserToolkit.from_browser(async_browser=async_browser)\n",
    "tools = browser_toolkit.get_tools()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "llm = ChatOpenAI(temperature=0) # Also works well with Anthropic models\n",
    "agent_chain = initialize_agent(tools, llm, agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.callbacks import tracing_enabled # This is used to configure tracing for our runs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "link = \"https://ms.ro/ro/centrul-de-presa/autoriza%C5%A3ia-de-construire-a-spitalului-regional-de-urgen%C5%A3%C4%83-cluj-a-fost-semnat%C4%83/\"\n",
    "input = \"Browse to {{}} and summarize the text, please.\".format(link)\n",
    "with tracing_enabled(): \n",
    "    response = await agent_chain.arun(input=\"Browse to blog.langchain.dev and summarize the text, please.\")\n",
    "print(response)"
   ]
  }
 ],
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