{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2c80b652-eadd-4d48-a512-d5945c0365d3",
   "metadata": {},
   "source": [
    "# Compare websites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e2a9393-7767-488e-a8bf-27c12dca35bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports\n",
    "\n",
    "import os\n",
    "import requests\n",
    "from dotenv import load_dotenv\n",
    "from bs4 import BeautifulSoup\n",
    "from IPython.display import Markdown, display\n",
    "from openai import OpenAI\n",
    "\n",
    "# If you get an error running this cell, then please head over to the troubleshooting notebook!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b87cadb-d513-4303-baee-a37b6f938e4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load environment variables \n",
    "\n",
    "load_dotenv(override=True)\n",
    "api_key = os.getenv('OPENAI_API_KEY')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "019974d9-f3ad-4a8a-b5f9-0a3719aea2d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "openai = OpenAI()\n",
    "\n",
    "# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
    "# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2aa190e5-cb31-456a-96cc-db109919cd78",
   "metadata": {},
   "source": [
    "## Website class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5e793b2-6775-426a-a139-4848291d0463",
   "metadata": {},
   "outputs": [],
   "source": [
    "# A class to represent a Webpage\n",
    "# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n",
    "\n",
    "# Some websites need you to use proper headers when fetching them:\n",
    "headers = {\n",
    " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
    "}\n",
    "\n",
    "class Website:\n",
    "\n",
    "    def __init__(self, url):\n",
    "        \"\"\"\n",
    "        Create this Website object from the given url using the BeautifulSoup library\n",
    "        \"\"\"\n",
    "        self.url = url\n",
    "        response = requests.get(url, headers=headers)\n",
    "        soup = BeautifulSoup(response.content, 'html.parser')\n",
    "        self.title = soup.title.string if soup.title else \"No title found\"\n",
    "        for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
    "            irrelevant.decompose()\n",
    "        self.text = soup.body.get_text(separator=\"\\n\", strip=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abdb8417-c5dc-44bc-9bee-2e059d162699",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\n",
    "\n",
    "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
    "and provides a short summary, ignoring text that might be navigation related. \\\n",
    "Respond in markdown.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0275b1b-7cfe-4f9d-abfa-7650d378da0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# A function that writes a User Prompt that asks for summaries of websites:\n",
    "\n",
    "def user_prompt_for(website):\n",
    "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
    "    user_prompt += \"\\nThe contents of this website is as follows; \\\n",
    "please provide a short summary of this website in markdown. \\\n",
    "If it includes news or announcements, then summarize these too.\\n\\n\"\n",
    "    user_prompt += website.text\n",
    "    return user_prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d06e8d78-ce4c-4b05-aa8e-17050c82bb47",
   "metadata": {},
   "source": [
    "## Website messages function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0134dfa4-8299-48b5-b444-f2a8c3403c88",
   "metadata": {},
   "outputs": [],
   "source": [
    "# See how this function creates exactly the format above\n",
    "\n",
    "def messages_for(website):\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_prompt},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
    "    ]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16f49d46-bf55-4c3e-928f-68fc0bf715b0",
   "metadata": {},
   "source": [
    "## Website summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "905b9919-aba7-45b5-ae65-81b3d1d78e34",
   "metadata": {},
   "outputs": [],
   "source": [
    "# And now: call the OpenAI API. You will get very familiar with this!\n",
    "\n",
    "def summarize(url):\n",
    "    website = Website(url)\n",
    "    response = openai.chat.completions.create(\n",
    "        model = \"gpt-4o-mini\",\n",
    "        messages = messages_for(website)\n",
    "    )\n",
    "    return response.choices[0].message.content\n",
    "\n",
    "# A function to display this nicely in the Jupyter output, using markdown\n",
    "\n",
    "def display_summary(summary):    \n",
    "    display(Markdown(summary))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d926d59-450e-4609-92ba-2d6f244f1342",
   "metadata": {},
   "outputs": [],
   "source": [
    "w1 = \"https://cnn.com\"\n",
    "summary1 = summarize(w1)\n",
    "display_summary(summary1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45d83403-a24c-44b5-84ac-961449b4008f",
   "metadata": {},
   "outputs": [],
   "source": [
    "w2 = \"https://www.foxnews.com\"\n",
    "summary2 = summarize(w2)\n",
    "display_summary(summary2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a51b45c-f3a6-4b0b-acfe-52957c04fd94",
   "metadata": {},
   "source": [
    "## Comparison between two websites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b30d5a5-bbe5-499c-9392-0896440f80c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_prompt_compare = \"\"\"You are a weblsite analyst that compares the summaries of two websites\n",
    "and provides a compare and contrast bewtween the two. \n",
    "Respond in markdown.\"\"\"\n",
    "\n",
    "def user_prompt_for_compare(summary1, summary2):\n",
    "    user_prompt = f\"You are asked to compare this summary of a website {summary1}\\n\\n\"\n",
    "    user_prompt += f\"\\nWith the summary of this second website {summary2}\\n\\n\"\n",
    "    user_prompt += \"please provide a short comparison of the two websites. \\\n",
    "List the similarities and differences in bullet point format.\\n\\n\"    \n",
    "    return user_prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5c9c955-840f-4c31-a1a7-b4872f77f3b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def messages_for_compare():\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_prompt_compare},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for_compare(summary1, summary2)}\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56307d77-f207-48f1-b59a-e97f6a2a37dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compare():    \n",
    "    response = openai.chat.completions.create(\n",
    "        model = \"gpt-4o-mini\",\n",
    "        messages = messages_for_compare()\n",
    "    )\n",
    "    return response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae3140bb-ddad-43e2-b697-6d05ae541544",
   "metadata": {},
   "outputs": [],
   "source": [
    "display_summary(compare())"
   ]
  }
 ],
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