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Merge 5b6402534b into abb462e53c

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Dheeraj Maddi 3 weeks ago committed by GitHub
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  1. 271
      week1/community-contributions/day1_selenium_implementation.ipynb
  2. 266
      week1/community-contributions/day2_exercise_ollama_website_summarization.ipynb

271
week1/community-contributions/day1_selenium_implementation.ipynb

@ -0,0 +1,271 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "4e2a9393-7767-488e-a8bf-27c12dca35bd",
"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\n",
"\n",
"# If you get an error running this cell, then please head over to the troubleshooting notebook!"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7b87cadb-d513-4303-baee-a37b6f938e4d",
"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!\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "019974d9-f3ad-4a8a-b5f9-0a3719aea2d3",
"metadata": {},
"outputs": [],
"source": [
"openai = OpenAI()\n",
"\n",
"# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
"# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "abdb8417-c5dc-44bc-9bee-2e059d162699",
"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.\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f0275b1b-7cfe-4f9d-abfa-7650d378da0c",
"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 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"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0134dfa4-8299-48b5-b444-f2a8c3403c88",
"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": "markdown",
"id": "eeab24dc-5f90-4570-b542-b0585aca3eb6",
"metadata": {},
"source": [
"# Sharing your code\n",
"\n",
"I'd love it if you share your code afterwards so I can share it with others! You'll notice that some students have already made changes (including a Selenium implementation) which you will find in the community-contributions folder. If you'd like add your changes to that folder, submit a Pull Request with your new versions in that folder and I'll merge your changes.\n",
"\n",
"If you're not an expert with git (and I am not!) then GPT has given some nice instructions on how to submit a Pull Request. It's a bit of an involved process, but once you've done it once it's pretty clear. As a pro-tip: it's best if you clear the outputs of your Jupyter notebooks (Edit >> Clean outputs of all cells, and then Save) for clean notebooks\n",
"\n",
"Here are good instructions courtesy of an AI friend: \n",
"https://chatgpt.com/share/677a9cb5-c64c-8012-99e0-e06e88afd293"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "acbb92b2-b625-4a37-b03a-09dc8f06b222",
"metadata": {},
"outputs": [],
"source": [
"!pip install selenium"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d6448a12-6aa1-4dd1-aaf1-c8a3a3c3ecb0",
"metadata": {},
"outputs": [],
"source": [
"!pip install webdriver-manager"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f4484fcf-8b39-4c3f-9674-37970ed71988",
"metadata": {},
"outputs": [],
"source": [
"# A class to represent a Webpage\n",
"# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n",
"\n",
"# Some websites need you to use proper headers when fetching them:\n",
"# Import necessary modules\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",
"from bs4 import BeautifulSoup\n",
"import time\n",
"\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": "f576f485-60c0-4539-bfb3-79d821ebefa4",
"metadata": {},
"outputs": [],
"source": [
"def summarize_js_website(url):\n",
" website = ScrapeWebsite(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": "00ac3659-e4f0-4b64-8041-ba35bfa2c4c9",
"metadata": {},
"outputs": [],
"source": [
"summary = summarize_js_website(\"https://dheerajmaddi.netlify.app/\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d526136e-9960-4f09-aad0-32f8c11de0ac",
"metadata": {},
"outputs": [],
"source": [
"display(Markdown(summary))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bcf1fd75-9964-4223-bcda-f2794bc9f7af",
"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
}

266
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": [
"<table style=\"margin: 0; text-align: left;\">\n",
" <tr>\n",
" <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
" <img src=\"../resources.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
" </td>\n",
" <td>\n",
" <h2 style=\"color:#f71;\">Just before we get to the assignment --</h2>\n",
" <span style=\"color:#f71;\">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.<br/>\n",
" <a href=\"https://edwarddonner.com/2024/11/13/llm-engineering-resources/\">https://edwarddonner.com/2024/11/13/llm-engineering-resources/</a><br/>\n",
" Please keep this bookmarked, and I'll continue to add more useful links there over time.\n",
" </span>\n",
" </td>\n",
" </tr>\n",
"</table>"
]
},
{
"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
}
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