{ "cells": [ { "cell_type": "markdown", "id": "786b2ed1-f82e-4ca4-8113-c4515b36e970", "metadata": {}, "source": [ "# Day 2 Exercise | Website Summarizer with Llama 3.2" ] }, { "cell_type": "code", "execution_count": null, "id": "b88bf233-29e0-4c01-a4da-8a16896a95e3", "metadata": {}, "outputs": [], "source": [ "import requests\n", "from bs4 import BeautifulSoup\n", "from IPython.display import Markdown, display" ] }, { "cell_type": "markdown", "id": "f66f620e-ebf6-45d3-a710-2bb931cac841", "metadata": {}, "source": [ "### 1. Scraping info from website:" ] }, { "cell_type": "code", "execution_count": null, "id": "4e300303-02ac-4d60-9c8c-044a4627be9e", "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": null, "id": "137714b9-24eb-4541-8f24-507dbcd09279", "metadata": {}, "outputs": [], "source": [ "ed = Website(\"https://edwarddonner.com\")" ] }, { "cell_type": "markdown", "id": "77ba1b4b-fc4c-4e3c-bef7-c4d4281d8263", "metadata": {}, "source": [ "### 2. Ollama configuration:" ] }, { "cell_type": "code", "execution_count": null, "id": "97811fcb-1ceb-49a8-bfb9-2e610605c406", "metadata": {}, "outputs": [], "source": [ "OLLAMA_API = \"http://localhost:11434/api/chat\"\n", "HEADERS = {\"Content-Type\": \"application/json\"}\n", "MODEL = \"llama3.2\"" ] }, { "cell_type": "code", "execution_count": null, "id": "392326b8-ad0f-4bc9-b055-6220f8bcc57c", "metadata": {}, "outputs": [], "source": [ "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", "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", "user_prompt = user_prompt_for(ed)" ] }, { "cell_type": "code", "execution_count": null, "id": "8caa94ff-5ace-4f9b-b2f0-beb6ff550636", "metadata": {}, "outputs": [], "source": [ "messages = [\n", " {\"role\": \"system\", \"content\": system_prompt},\n", " {\"role\": \"user\", \"content\": user_prompt}\n", "]\n", "\n", "payload = {\n", " \"model\": MODEL,\n", " \"messages\": messages,\n", " \"stream\": False\n", "}" ] }, { "cell_type": "markdown", "id": "f5f856bc-0437-4607-9204-5390d2dfd8db", "metadata": {}, "source": [ "### 3. Get & display summary:" ] }, { "cell_type": "code", "execution_count": null, "id": "a7fd6f93-92ae-419f-b8b6-ee8214e0d93f", "metadata": {}, "outputs": [], "source": [ "response = requests.post(OLLAMA_API, json=payload, headers=HEADERS)\n", "summary = response.json()['message']['content']" ] }, { "cell_type": "code", "execution_count": null, "id": "78e4a433-b974-463f-82d0-b4696c63e0ab", "metadata": {}, "outputs": [], "source": [ "def display_summary(summary_text: str):\n", " cleaned = summary_text.encode('utf-8').decode('unicode_escape')\n", " cleaned = cleaned.strip()\n", " display(Markdown(cleaned))" ] }, { "cell_type": "code", "execution_count": null, "id": "dc408f1d-fe26-4bd6-859f-d18118f74ca6", "metadata": {}, "outputs": [], "source": [ "display_summary(summary)" ] } ], "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 }