From 5b6402534bd23e0b0330e6f0d1ff5201f6a43a53 Mon Sep 17 00:00:00 2001 From: Dheeraj Maddi Date: Wed, 16 Apr 2025 18:55:58 -0500 Subject: [PATCH] Completed Exercise-1 on Day-2: Implementation for web scraping summarization using Ollama --- ...xercise_ollama_website_summarization.ipynb | 266 ++++++++++++++++++ 1 file changed, 266 insertions(+) create mode 100644 week1/community-contributions/day2_exercise_ollama_website_summarization.ipynb diff --git a/week1/community-contributions/day2_exercise_ollama_website_summarization.ipynb b/week1/community-contributions/day2_exercise_ollama_website_summarization.ipynb new file mode 100644 index 0000000..f9d4ebc --- /dev/null +++ b/week1/community-contributions/day2_exercise_ollama_website_summarization.ipynb @@ -0,0 +1,266 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d15d8294-3328-4e07-ad16-8a03e9bbfdb9", + "metadata": {}, + "source": [ + "# Welcome to your first assignment!\n", + "\n", + "Instructions are below. Please give this a try, and look in the solutions folder if you get stuck (or feel free to ask me!)" + ] + }, + { + "cell_type": "markdown", + "id": "ada885d9-4d42-4d9b-97f0-74fbbbfe93a9", + "metadata": {}, + "source": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Just before we get to the assignment --

\n", + " I thought I'd take a second to point you at this page of useful resources for the course. This includes links to all the slides.
\n", + " https://edwarddonner.com/2024/11/13/llm-engineering-resources/
\n", + " Please keep this bookmarked, and I'll continue to add more useful links there over time.\n", + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9cc85216-f6e4-436e-b6c1-976c8f2d1152", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install webdriver-manager\n", + "!pip install selenium" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4e2a9393-7767-488e-a8bf-27c12dca35bd", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display\n", + "import ollama\n", + "from openai import OpenAI\n", + "from selenium import webdriver\n", + "from selenium.webdriver.chrome.options import Options\n", + "from selenium.webdriver.chrome.service import Service\n", + "from webdriver_manager.chrome import ChromeDriverManager\n", + "import time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "29ddd15d-a3c5-4f4e-a678-873f56162724", + "metadata": {}, + "outputs": [], + "source": [ + "# Constants\n", + "MODEL = \"llama3.2\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "479ff514-e8bd-4985-a572-2ea28bb4fa40", + "metadata": {}, + "outputs": [], + "source": [ + "# Let's just make sure the model is loaded\n", + "\n", + "!ollama pull llama3.2" + ] + }, + { + "cell_type": "markdown", + "id": "6a021f13-d6a1-4b96-8e18-4eae49d876fe", + "metadata": {}, + "source": [ + "# Introducing the ollama package\n", + "\n", + "And now we'll do the same thing, but using the elegant ollama python package instead of a direct HTTP call.\n", + "\n", + "Under the hood, it's making the same call as above to the ollama server running at localhost:11434" + ] + }, + { + "cell_type": "markdown", + "id": "a4704e10-f5fb-4c15-a935-f046c06fb13d", + "metadata": {}, + "source": [ + "## Alternative approach - using OpenAI python library to connect to Ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23057e00-b6fc-4678-93a9-6b31cb704bff", + "metadata": {}, + "outputs": [], + "source": [ + "# There's actually an alternative approach that some people might prefer\n", + "# You can use the OpenAI client python library to call Ollama:\n", + "\n", + "\n", + "ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')" + ] + }, + { + "cell_type": "markdown", + "id": "1622d9bb-5c68-4d4e-9ca4-b492c751f898", + "metadata": {}, + "source": [ + "# NOW the exercise for you\n", + "\n", + "Take the code from day1 and incorporate it here, to build a website summarizer that uses Llama 3.2 running locally instead of OpenAI; use either of the above approaches." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8251b6a5-7b43-42b9-84a9-4a94b6bdb933", + "metadata": {}, + "outputs": [], + "source": [ + "# A class to represent a Webpage\n", + "class ScrapeWebsite:\n", + " def __init__(self, url):\n", + " \"\"\"\n", + " Create this Website object from the given URL using Selenium + BeautifulSoup\n", + " Supports JavaScript-heavy and normal websites uniformly.\n", + " \"\"\"\n", + " self.url = url\n", + "\n", + " # Configure headless Chrome\n", + " options = Options()\n", + " options.add_argument('--headless')\n", + " options.add_argument('--no-sandbox')\n", + " options.add_argument('--disable-dev-shm-usage')\n", + "\n", + " # Use webdriver-manager to manage ChromeDriver\n", + " service = Service(ChromeDriverManager().install())\n", + "\n", + " # Initialize the Chrome WebDriver with the service and options\n", + " driver = webdriver.Chrome(service=service, options=options)\n", + "\n", + " # Start Selenium WebDriver\n", + " driver.get(url)\n", + "\n", + " # Wait for JS to load (adjust as needed)\n", + " time.sleep(3)\n", + "\n", + " # Fetch the page source after JS execution\n", + " page_source = driver.page_source\n", + " driver.quit()\n", + "\n", + " # Parse the HTML content with BeautifulSoup\n", + " soup = BeautifulSoup(page_source, 'html.parser')\n", + "\n", + " # Extract title\n", + " self.title = soup.title.string if soup.title else \"No title found\"\n", + "\n", + " # Remove unnecessary elements\n", + " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", + " irrelevant.decompose()\n", + "\n", + " # Extract the main text\n", + " self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6de38216-6d1c-48c4-877b-86d403f4e0f8", + "metadata": {}, + "outputs": [], + "source": [ + "# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\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", + "\n", + "# 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 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", + "def messages_for(website):\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", + " ]\n", + "\n", + "# And now: call the OpenAI API. You will get very familiar with this!\n", + "\n", + "def summarize(url):\n", + " website = ScrapeWebsite(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" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5dbf8d5c-a42a-4a72-b3a4-c75865b841bb", + "metadata": {}, + "outputs": [], + "source": [ + "summary = summarize(\"https://edwarddonner.com/2024/11/13/llm-engineering-resources/\")\n", + "display(Markdown(summary))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4ddfacdc-b16a-4999-9ff2-93ed19600d24", + "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": "3.11.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}