{ "cells": [ { "cell_type": "markdown", "id": "56c86bae-1d3c-4c01-b5d6-c8879fec1954", "metadata": {}, "source": [ "# Wiki Summarizer\n", "\n", "This Project takes the name of a topic as input, and checks if the corresponding wiki-page exists. If it does, it parses the web page, and outputs a summary created using the GPT-4o-mini model. \n", "\n", "Concepts used: \n", "- Web Scraping via Beautiful Soup\n", "- User and System Prompts\n", "- Use of Open AI GPT-4o-mini via API key" ] }, { "cell_type": "code", "execution_count": null, "id": "4820830e-b3b4-426e-b1a2-518e7c7f6c1a", "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" ] }, { "cell_type": "code", "execution_count": null, "id": "2cd7ad51-396c-45c5-9089-f7b21a19da50", "metadata": {}, "outputs": [], "source": [ "# Load environment variables in a file called .env\n", "\n", "load_dotenv(override=True)\n", "api_key = os.getenv('OPENAI_API_KEY')\n", "\n", "# Check the key\n", "\n", "if not api_key:\n", " print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n", "elif not api_key.startswith(\"sk-proj-\"):\n", " print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n", "elif api_key.strip() != api_key:\n", " print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n", "else:\n", " print(\"API key found and looks good so far!\")" ] }, { "cell_type": "code", "execution_count": null, "id": "689421a0-20a1-428b-a8b8-fa239fa6f633", "metadata": {}, "outputs": [], "source": [ "# creating an instance\n", "openai = OpenAI()" ] }, { "cell_type": "code", "execution_count": null, "id": "401901ae-7639-4190-98fd-e69374084723", "metadata": {}, "outputs": [], "source": [ "def isWiki(url):\n", " \"\"\"\n", " Check whether a Wikipedia page exists for a given topic, and \n", " returns a Boolean value.\n", " \"\"\"\n", " response = requests.get(url)\n", "\n", " if response.status_code != 200:\n", " return False\n", " \n", " return True" ] }, { "cell_type": "code", "execution_count": null, "id": "7cdb14d3-05ea-4de2-a475-d49a5731692e", "metadata": {}, "outputs": [], "source": [ "# A class to represent a Webpage\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": "7f6ed50e-0fb5-479e-9845-f62cf25980f7", "metadata": {}, "outputs": [], "source": [ "system_prompt = \"You are an educational assistant tasked with helping users understand topics\\\n", "by providing succinct and clear summaries of requested data. Ignore navigation-related text\\\n", "and provide answers in markdown format\"" ] }, { "cell_type": "code", "execution_count": null, "id": "b2d77dd9-a94f-49c1-a1be-11d157bd37fb", "metadata": {}, "outputs": [], "source": [ "# A function that writes a User Prompt that asks for summaries of wiki pages:\n", "\n", "def user_prompt_for(wiki):\n", " user_prompt = f\"You are looking at a Wikipedia page titled {wiki.title}\"\n", " user_prompt += \"\\nThe contents of this page is as follows; \\\n", "please provide a short summary of this website in markdown.\\n\"\n", " user_prompt += wiki.text\n", " return user_prompt" ] }, { "cell_type": "code", "execution_count": null, "id": "0d23bcc4-1d89-4bd4-9809-d3a1819aa919", "metadata": {}, "outputs": [], "source": [ "def messages_for(wiki):\n", " return [\n", " {\"role\": \"system\", \"content\": system_prompt},\n", " {\"role\": \"user\", \"content\": user_prompt_for(wiki)}\n", " ]" ] }, { "cell_type": "code", "execution_count": null, "id": "971bd7fb-2ff8-4494-b386-de69a39c24ff", "metadata": {}, "outputs": [], "source": [ "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" ] }, { "cell_type": "code", "execution_count": null, "id": "a8fdf9f2-f49e-4d06-ac9e-dfcb8da33d60", "metadata": {}, "outputs": [], "source": [ "def display_summary(topic):\n", " url = f\"https://en.wikipedia.org/wiki/{topic}\"\n", " if isWiki(url):\n", " summary = summarize(url)\n", " display(Markdown(summary))\n", " else:\n", " print('A Wikipedia page does not exist for this topic')\n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "f4758ef0-9b7c-4d3e-9131-e3284dc76b6b", "metadata": { "scrolled": true }, "outputs": [], "source": [ "topic = input('Enter the name of Wikipedia page for which you would like a summary: ').strip()\n", "display_summary(topic)" ] } ], "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": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 5 }