{ "cells": [ { "cell_type": "markdown", "id": "032a76d2-a112-4c49-bd32-fe6c87f6ec19", "metadata": {}, "source": [ "## Dota Game Assistant\n", "\n", "This script retrieves and summarizes information about a specified hero from `dotabuff.com` website" ] }, { "cell_type": "code", "execution_count": null, "id": "04b24159-55d1-4eaf-bc19-474cec71cc3b", "metadata": {}, "outputs": [], "source": [ "!pip install selenium\n", "!pip install webdriver-manager" ] }, { "cell_type": "code", "execution_count": null, "id": "14d26510-6613-4c1a-a346-159d906d111c", "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": "f9c8ea1e-8881-4f50-953d-ca7f462d8a32", "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": "02febcac-9a21-4322-b2ea-748972312165", "metadata": {}, "outputs": [], "source": [ "openai = OpenAI()" ] }, { "cell_type": "code", "execution_count": null, "id": "bb7dd822-962e-4b34-a743-c14809764e4a", "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", "from selenium import webdriver\n", "from selenium.webdriver.chrome.service import Service\n", "from selenium.webdriver.chrome.options import Options\n", "from selenium.webdriver.common.by import By\n", "from selenium.webdriver.support.ui import WebDriverWait\n", "from selenium.webdriver.support import expected_conditions as EC\n", "from webdriver_manager.chrome import ChromeDriverManager\n", "from bs4 import BeautifulSoup\n", "\n", "class Website:\n", " def __init__(self, url, wait_time=10):\n", " \"\"\"\n", " Create this Website object from the given URL using Selenium and BeautifulSoup.\n", " Uses headless Chrome to load JavaScript content.\n", " \"\"\"\n", " self.url = url\n", "\n", " # Configure headless Chrome\n", " options = Options()\n", " options.headless = True\n", " options.add_argument(\"--disable-gpu\")\n", " options.add_argument(\"--no-sandbox\")\n", "\n", " # Start the driver\n", " service = Service(ChromeDriverManager().install())\n", " driver = webdriver.Chrome(service=service, options=options)\n", "\n", " try:\n", " driver.get(url)\n", "\n", " # Wait until body is loaded (you can tweak the wait condition)\n", " WebDriverWait(driver, wait_time).until(\n", " EC.presence_of_element_located((By.TAG_NAME, \"body\"))\n", " )\n", "\n", " html = driver.page_source\n", " soup = BeautifulSoup(html, \"html.parser\")\n", "\n", " self.title = soup.title.string.strip() if soup.title else \"No title found\"\n", "\n", " # Remove unwanted tags\n", " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", " irrelevant.decompose()\n", "\n", " self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n", "\n", " finally:\n", " driver.quit()\n" ] }, { "cell_type": "code", "execution_count": null, "id": "9d833fbb-0115-4d99-a4e9-464f27900eab", "metadata": {}, "outputs": [], "source": [ "class DotaWebsite:\n", " def __init__(self, hero):\n", " web = Website(\"https://www.dotabuff.com/heroes\" + \"/\" + hero)\n", " self.title = web.title\n", " self.text = web.text" ] }, { "cell_type": "code", "execution_count": null, "id": "a0a42c2b-c837-4d1b-b8f8-b2dbb8592a1a", "metadata": {}, "outputs": [], "source": [ "system_prompt = \"You are an game assistant that analyzes the contents of a website \\\n", "and provides a short summary about facet selection, ability building, item building, best versus and worst versus, ignoring text that might be navigation related. \\\n", "Respond in markdown.\"" ] }, { "cell_type": "code", "execution_count": null, "id": "7c05843d-6373-4a76-8cca-9c716a6ca13a", "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 provides a short summary about facet selection, ability building, item building, best versus and worst versus 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": "code", "execution_count": null, "id": "0145eee1-39e2-4f00-89ec-7acc6e375972", "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": "code", "execution_count": null, "id": "76f389c0-572a-476b-9b4e-719c0ef10abb", "metadata": {}, "outputs": [], "source": [ "# And now: call the OpenAI API. You will get very familiar with this!\n", "\n", "def summarize(hero):\n", " website = DotaWebsite(hero)\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": "fcb046b7-52a9-49ff-b7bc-d8f6c279df4c", "metadata": {}, "outputs": [], "source": [ "# A function to display this nicely in the Jupyter output, using markdown\n", "\n", "def display_summary(hero):\n", " summary = summarize(hero)\n", " display(Markdown(summary))" ] }, { "cell_type": "code", "execution_count": null, "id": "9befb685-2912-41a9-b2d9-ae33001494c0", "metadata": {}, "outputs": [], "source": [ "display_summary(\"axe\")" ] }, { "cell_type": "code", "execution_count": null, "id": "bf1bb1d9-0351-44fc-8ebf-91aa47a81b42", "metadata": {}, "outputs": [], "source": [] } ], "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 }