{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "4d02ac4b-9cab-42bb-b8a3-123d53913471", "metadata": {}, "outputs": [], "source": [ "import os\n", "import requests\n", "from bs4 import BeautifulSoup\n", "from IPython.display import Markdown, display\n", "import ollama\n", "\n", "MODEL = \"llama3.2\"\n", "\n", "# Optional headers to avoid request blocks\n", "HEADERS = {\n", " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64)\"\n", "}\n", "\n", "\n", "class Website:\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", " if soup.body:\n", " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", " irrelevant.decompose()\n", " self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n", " else:\n", " self.text = \"\"\n", "\n", "\n", "system_prompt = \"\"\"You are an assistant that analyzes the contents of a website \n", "and provides a short summary, ignoring navigation text. Respond in markdown.\"\"\"\n", "\n", "\n", "def user_prompt_for(website):\n", " return f\"\"\"You are looking at a website titled {website.title}.\n", "The contents of this website are as follows. Please provide a short summary in markdown. \n", "If it includes news or announcements, summarize these too.\n", "\n", "{website.text}\n", "\"\"\"\n", "\n", "\n", "def summarize(url):\n", " website = Website(url)\n", " response = ollama.chat(\n", " model=MODEL,\n", " messages=[\n", " {\"role\": \"system\", \"content\": system_prompt},\n", " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", " ]\n", " )\n", " return response['message']['content']\n", "\n", "\n", "def display_summary(url):\n", " summary = summarize(url)\n", " display(Markdown(summary))\n", "\n", "\n", "# Example usage\n", "display_summary(\"https://edwarddonner.com\")\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 5 }