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  {
   "cell_type": "markdown",
   "id": "a68b1042-558a-4051-85e2-9ffd7a31a871",
   "metadata": {},
   "source": [
    "# Website Summarization Using llama\n",
    "### Week 1 Day 2 Exercise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "176fcb2f-9ac7-460b-9fad-415e89c4920e",
   "metadata": {},
   "outputs": [],
   "source": [
    "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b9c63761-c904-491b-92c7-e41eb319c3e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants\n",
    "\n",
    "# OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
    "# HEADERS = {\"Content-Type\": \"application/json\"}\n",
    "MODEL = \"llama3.2\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "afe29712-751c-4322-a4c6-aed01e6acf26",
   "metadata": {},
   "outputs": [],
   "source": [
    "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": 5,
   "id": "be3eeb3f-aec5-4ef8-9427-3b80b2dce919",
   "metadata": {},
   "outputs": [],
   "source": [
    "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.\"\n",
    "\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\n",
    "    \n",
    "\n",
    "def messages_for(website):\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_prompt},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
    "    ]\n",
    "\n",
    "ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n",
    "\n",
    "def summarize(url):\n",
    "    website = Website(url)\n",
    "    response = ollama_via_openai.chat.completions.create(\n",
    "        model = MODEL,\n",
    "        messages = messages_for(website)\n",
    "    )\n",
    "    return response.choices[0].message.content\n",
    "\n",
    "\n",
    "def display_summary(url):\n",
    "    summary = summarize(url)\n",
    "    display(Markdown(summary))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a78b587d-3a75-45a8-9ac5-f78dcddfa822",
   "metadata": {},
   "outputs": [],
   "source": [
    "display_summary(\"https://cnn.com\")"
   ]
  }
 ],
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