{ "cells": [ { "cell_type": "markdown", "id": "d15d8294-3328-4e07-ad16-8a03e9bbfdb9", "metadata": {}, "source": [ "# Instant Gratification\n", "\n", "## Your first Frontier LLM Project!\n", "\n", "Let's build a useful LLM solution - in a matter of minutes.\n", "\n", "By the end of this course, you will have built an autonomous Agentic AI solution with 7 agents that collaborate to solve a business problem. All in good time! We will start with something smaller...\n", "\n", "Our goal is to code a new kind of Web Browser. Give it a URL, and it will respond with a summary. The Reader's Digest of the internet!!\n", "\n", "Before starting, you should have completed the setup for [PC](../SETUP-PC.md) or [Mac](../SETUP-mac.md) and you hopefully launched this jupyter lab from within the project root directory, with your environment activated.\n", "\n", "## If you're new to Jupyter Lab\n", "\n", "Welcome to the wonderful world of Data Science experimentation! Once you've used Jupyter Lab, you'll wonder how you ever lived without it. Simply click in each \"cell\" with code in it, such as the cell immediately below this text, and hit Shift+Return to execute that cell. As you wish, you can add a cell with the + button in the toolbar, and print values of variables, or try out variations. \n", "\n", "I've written a notebook called [Guide to Jupyter](Guide%20to%20Jupyter.ipynb) to help you get more familiar with Jupyter Labs, including adding Markdown comments, using `!` to run shell commands, and `tqdm` to show progress.\n", "\n", "If you prefer to work in IDEs like VSCode or Pycharm, they both work great with these lab notebooks too. \n", "\n", "## If you'd like to brush up your Python\n", "\n", "I've added a notebook called [Intermediate Python](Intermediate%20Python.ipynb) to get you up to speed. But you should give it a miss if you already have a good idea what this code does: \n", "`yield from {book.get(\"author\") for book in books if book.get(\"author\")}`\n", "\n", "## I am here to help\n", "\n", "If you have any problems at all, please do reach out. \n", "I'm available through the platform, or at ed@edwarddonner.com, or at https://www.linkedin.com/in/eddonner/ if you'd like to connect (and I love connecting!)\n", "\n", "## More troubleshooting\n", "\n", "Please see the [troubleshooting](troubleshooting.ipynb) notebook in this folder to diagnose and fix common problems. At the very end of it is a diagnostics script with some useful debug info.\n", "\n", "## If this is old hat!\n", "\n", "If you're already comfortable with today's material, please hang in there; you can move swiftly through the first few labs - we will get much more in depth as the weeks progress.\n", "\n", "\n", " \n", " \n", " \n", " \n", "
\n", " \n", " \n", "

Please read - important note

\n", " The way I collaborate with you may be different to other courses you've taken. I prefer not to type code while you watch. Rather, I execute Jupyter Labs, like this, and give you an intuition for what's going on. My suggestion is that you do this with me, either at the same time, or (perhaps better) right afterwards. Add print statements to understand what's going on, and then come up with your own variations. If you have a Github account, use this to showcase your variations. Not only is this essential practice, but it demonstrates your skills to others, including perhaps future clients or employers...\n", "
\n", "\n", " \n", " \n", " \n", " \n", "
\n", " \n", " \n", "

Business value of these exercises

\n", " A final thought. While I've designed these notebooks to be educational, I've also tried to make them enjoyable. We'll do fun things like have LLMs tell jokes and argue with each other. But fundamentally, my goal is to teach skills you can apply in business. I'll explain business implications as we go, and it's worth keeping this in mind: as you build experience with models and techniques, think of ways you could put this into action at work today. Please do contact me if you'd like to discuss more or if you have ideas to bounce off me.\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "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": "markdown", "id": "6900b2a8-6384-4316-8aaa-5e519fca4254", "metadata": {}, "source": [ "# Connecting to OpenAI\n", "\n", "The next cell is where we load in the environment variables in your `.env` file and connect to OpenAI.\n", "\n", "## Troubleshooting if you have problems:\n", "\n", "Head over to the [troubleshooting](troubleshooting.ipynb) notebook in this folder for step by step code to identify the root cause and fix it!\n", "\n", "If you make a change, try restarting the \"Kernel\" (the python process sitting behind this notebook) by Kernel menu >> Restart Kernel and Clear Outputs of All Cells. Then try this notebook again, starting at the top.\n", "\n", "Or, contact me! Message me or email ed@edwarddonner.com and we will get this to work.\n", "\n", "Any concerns about API costs? See my notes in the README - costs should be minimal, and you can control it at every point. You can also use Ollama as a free alternative, which we discuss during Day 2." ] }, { "cell_type": "code", "execution_count": 2, "id": "7b87cadb-d513-4303-baee-a37b6f938e4d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "API key found and looks good so far!\n" ] } ], "source": [ "# Load environment variables in a file called .env\n", "\n", "load_dotenv()\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": 4, "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, or try the below line instead:\n", "# openai = OpenAI(api_key=\"your-key-here-starting-sk-proj-\")" ] }, { "cell_type": "markdown", "id": "442fc84b-0815-4f40-99ab-d9a5da6bda91", "metadata": {}, "source": [ "# Let's make a quick call to a Frontier model to get started, as a preview!" ] }, { "cell_type": "code", "execution_count": 5, "id": "a58394bf-1e45-46af-9bfd-01e24da6f49a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Hello! Welcome! I'm glad to be chatting with you. How can I assist you today?\n" ] } ], "source": [ "# To give you a preview -- calling OpenAI with these messages is this easy:\n", "\n", "message = \"Hello, GPT! This is my first ever message to you! Hi!\"\n", "response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=[{\"role\":\"user\", \"content\":message}])\n", "print(response.choices[0].message.content)" ] }, { "cell_type": "markdown", "id": "2aa190e5-cb31-456a-96cc-db109919cd78", "metadata": {}, "source": [ "## OK onwards with our first project" ] }, { "cell_type": "code", "execution_count": 6, "id": "c5e793b2-6775-426a-a139-4848291d0463", "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", "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": 7, "id": "2ef960cf-6dc2-4cda-afb3-b38be12f4c97", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Home - Edward Donner\n", "Home\n", "Outsmart\n", "An arena that pits LLMs against each other in a battle of diplomacy and deviousness\n", "About\n", "Posts\n", "Well, hi there.\n", "I’m Ed. I like writing code and experimenting with LLMs, and hopefully you’re here because you do too. I also enjoy DJing (but I’m badly out of practice), amateur electronic music production (\n", "very\n", "amateur) and losing myself in\n", "Hacker News\n", ", nodding my head sagely to things I only half understand.\n", "I’m the co-founder and CTO of\n", "Nebula.io\n", ". We’re applying AI to a field where it can make a massive, positive impact: helping people discover their potential and pursue their reason for being. Recruiters use our product today to source, understand, engage and manage talent. I’m previously the founder and CEO of AI startup untapt,\n", "acquired in 2021\n", ".\n", "We work with groundbreaking, proprietary LLMs verticalized for talent, we’ve\n", "patented\n", "our matching model, and our award-winning platform has happy customers and tons of press coverage.\n", "Connect\n", "with me for more!\n", "November 13, 2024\n", "Mastering AI and LLM Engineering – Resources\n", "October 16, 2024\n", "From Software Engineer to AI Data Scientist – resources\n", "August 6, 2024\n", "Outsmart LLM Arena – a battle of diplomacy and deviousness\n", "June 26, 2024\n", "Choosing the Right LLM: Toolkit and Resources\n", "Navigation\n", "Home\n", "Outsmart\n", "An arena that pits LLMs against each other in a battle of diplomacy and deviousness\n", "About\n", "Posts\n", "Get in touch\n", "ed [at] edwarddonner [dot] com\n", "www.edwarddonner.com\n", "Follow me\n", "LinkedIn\n", "Twitter\n", "Facebook\n", "Subscribe to newsletter\n", "Type your email…\n", "Subscribe\n" ] } ], "source": [ "# Let's try one out. Change the website and add print statements to follow along.\n", "\n", "ed = Website(\"https://edwarddonner.com\")\n", "print(ed.title)\n", "print(ed.text)" ] }, { "cell_type": "markdown", "id": "6a478a0c-2c53-48ff-869c-4d08199931e1", "metadata": {}, "source": [ "## Types of prompts\n", "\n", "You may know this already - but if not, you will get very familiar with it!\n", "\n", "Models like GPT4o have been trained to receive instructions in a particular way.\n", "\n", "They expect to receive:\n", "\n", "**A system prompt** that tells them what task they are performing and what tone they should use\n", "\n", "**A user prompt** -- the conversation starter that they should reply to" ] }, { "cell_type": "code", "execution_count": 8, "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": 9, "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": 10, "id": "26448ec4-5c00-4204-baec-7df91d11ff2e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "You are looking at a website titled Home - Edward Donner\n", "The contents of this website is as follows; please provide a short summary of this website in markdown. If it includes news or announcements, then summarize these too.\n", "\n", "Home\n", "Outsmart\n", "An arena that pits LLMs against each other in a battle of diplomacy and deviousness\n", "About\n", "Posts\n", "Well, hi there.\n", "I’m Ed. I like writing code and experimenting with LLMs, and hopefully you’re here because you do too. I also enjoy DJing (but I’m badly out of practice), amateur electronic music production (\n", "very\n", "amateur) and losing myself in\n", "Hacker News\n", ", nodding my head sagely to things I only half understand.\n", "I’m the co-founder and CTO of\n", "Nebula.io\n", ". We’re applying AI to a field where it can make a massive, positive impact: helping people discover their potential and pursue their reason for being. Recruiters use our product today to source, understand, engage and manage talent. I’m previously the founder and CEO of AI startup untapt,\n", "acquired in 2021\n", ".\n", "We work with groundbreaking, proprietary LLMs verticalized for talent, we’ve\n", "patented\n", "our matching model, and our award-winning platform has happy customers and tons of press coverage.\n", "Connect\n", "with me for more!\n", "November 13, 2024\n", "Mastering AI and LLM Engineering – Resources\n", "October 16, 2024\n", "From Software Engineer to AI Data Scientist – resources\n", "August 6, 2024\n", "Outsmart LLM Arena – a battle of diplomacy and deviousness\n", "June 26, 2024\n", "Choosing the Right LLM: Toolkit and Resources\n", "Navigation\n", "Home\n", "Outsmart\n", "An arena that pits LLMs against each other in a battle of diplomacy and deviousness\n", "About\n", "Posts\n", "Get in touch\n", "ed [at] edwarddonner [dot] com\n", "www.edwarddonner.com\n", "Follow me\n", "LinkedIn\n", "Twitter\n", "Facebook\n", "Subscribe to newsletter\n", "Type your email…\n", "Subscribe\n" ] } ], "source": [ "print(user_prompt_for(ed))" ] }, { "cell_type": "markdown", "id": "ea211b5f-28e1-4a86-8e52-c0b7677cadcc", "metadata": {}, "source": [ "## Messages\n", "\n", "The API from OpenAI expects to receive messages in a particular structure.\n", "Many of the other APIs share this structure:\n", "\n", "```\n", "[\n", " {\"role\": \"system\", \"content\": \"system message goes here\"},\n", " {\"role\": \"user\", \"content\": \"user message goes here\"}\n", "]\n", "\n", "To give you a preview, the next 2 cells make a rather simple call - we won't stretch the might GPT (yet!)" ] }, { "cell_type": "code", "execution_count": 11, "id": "f25dcd35-0cd0-4235-9f64-ac37ed9eaaa5", "metadata": {}, "outputs": [], "source": [ "messages = [\n", " {\"role\": \"system\", \"content\": \"You are a snarky assistant\"},\n", " {\"role\": \"user\", \"content\": \"What is 2 + 2?\"}\n", "]" ] }, { "cell_type": "code", "execution_count": 12, "id": "21ed95c5-7001-47de-a36d-1d6673b403ce", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Oh, a real brain teaser! The answer is 4. But if you’re looking for something more challenging, I’m all ears!\n" ] } ], "source": [ "# To give you a preview -- calling OpenAI with system and user messages:\n", "\n", "response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=messages)\n", "print(response.choices[0].message.content)" ] }, { "cell_type": "markdown", "id": "d06e8d78-ce4c-4b05-aa8e-17050c82bb47", "metadata": {}, "source": [ "## And now let's build useful messages for GPT-4o-mini, using a function" ] }, { "cell_type": "code", "execution_count": 13, "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": "code", "execution_count": 14, "id": "36478464-39ee-485c-9f3f-6a4e458dbc9c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'role': 'system',\n", " 'content': 'You are an assistant that analyzes the contents of a website and provides a short summary, ignoring text that might be navigation related. Respond in markdown.'},\n", " {'role': 'user',\n", " 'content': 'You are looking at a website titled Home - Edward Donner\\nThe contents of this website is as follows; please provide a short summary of this website in markdown. If it includes news or announcements, then summarize these too.\\n\\nHome\\nOutsmart\\nAn arena that pits LLMs against each other in a battle of diplomacy and deviousness\\nAbout\\nPosts\\nWell, hi there.\\nI’m Ed. I like writing code and experimenting with LLMs, and hopefully you’re here because you do too. I also enjoy DJing (but I’m badly out of practice), amateur electronic music production (\\nvery\\namateur) and losing myself in\\nHacker News\\n, nodding my head sagely to things I only half understand.\\nI’m the co-founder and CTO of\\nNebula.io\\n. We’re applying AI to a field where it can make a massive, positive impact: helping people discover their potential and pursue their reason for being. Recruiters use our product today to source, understand, engage and manage talent. I’m previously the founder and CEO of AI startup untapt,\\nacquired in 2021\\n.\\nWe work with groundbreaking, proprietary LLMs verticalized for talent, we’ve\\npatented\\nour matching model, and our award-winning platform has happy customers and tons of press coverage.\\nConnect\\nwith me for more!\\nNovember 13, 2024\\nMastering AI and LLM Engineering – Resources\\nOctober 16, 2024\\nFrom Software Engineer to AI Data Scientist – resources\\nAugust 6, 2024\\nOutsmart LLM Arena – a battle of diplomacy and deviousness\\nJune 26, 2024\\nChoosing the Right LLM: Toolkit and Resources\\nNavigation\\nHome\\nOutsmart\\nAn arena that pits LLMs against each other in a battle of diplomacy and deviousness\\nAbout\\nPosts\\nGet in touch\\ned [at] edwarddonner [dot] com\\nwww.edwarddonner.com\\nFollow me\\nLinkedIn\\nTwitter\\nFacebook\\nSubscribe to newsletter\\nType your email…\\nSubscribe'}]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Try this out, and then try for a few more websites\n", "\n", "messages_for(ed)" ] }, { "cell_type": "markdown", "id": "16f49d46-bf55-4c3e-928f-68fc0bf715b0", "metadata": {}, "source": [ "## Time to bring it together - the API for OpenAI is very simple!" ] }, { "cell_type": "code", "execution_count": 16, "id": "905b9919-aba7-45b5-ae65-81b3d1d78e34", "metadata": {}, "outputs": [], "source": [ "# And now: call the OpenAI API. You will get very familiar with this!\n", "\n", "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": 17, "id": "05e38d41-dfa4-4b20-9c96-c46ea75d9fb5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'# Summary of Edward Donner\\'s Website\\n\\nEdward Donner\\'s website features content focused on his interests in coding, experimenting with large language models (LLMs), and his professional work in AI. As the co-founder and CTO of Nebula.io, he emphasizes the positive impact of AI in helping individuals discover their potential and improve talent management. He previously founded and led an AI startup, untapt, which was acquired in 2021.\\n\\n## Recent News and Announcements\\n\\n- **November 13, 2024**: Shared resources for mastering AI and LLM engineering.\\n- **October 16, 2024**: Provided resources for transitioning from a software engineer to an AI data scientist.\\n- **August 6, 2024**: Announced the \"Outsmart LLM Arena,\" an initiative to engage LLMs in a competitive format.\\n- **June 26, 2024**: Offered a toolkit and resources for selecting the right LLM. \\n\\nThe website invites visitors to connect with Edward Donner for further engagement.'" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summarize(\"https://edwarddonner.com\")" ] }, { "cell_type": "code", "execution_count": 18, "id": "3d926d59-450e-4609-92ba-2d6f244f1342", "metadata": {}, "outputs": [], "source": [ "# A function to display this nicely in the Jupyter output, using markdown\n", "\n", "def display_summary(url):\n", " summary = summarize(url)\n", " display(Markdown(summary))" ] }, { "cell_type": "code", "execution_count": 19, "id": "3018853a-445f-41ff-9560-d925d1774b2f", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "# Summary of Edward Donner's Website\n", "\n", "The website is a personal platform belonging to Edward Donner, a co-founder and CTO of Nebula.io, a company focused on utilizing AI to assist individuals in discovering their potential and managing talent. Edward expresses his interests in coding, experimenting with large language models (LLMs), and DJing, along with occasional contributions to Hacker News.\n", "\n", "## Key Features:\n", "- **Outsmart**: A unique arena designed to challenge LLMs in a competition of diplomacy and strategy.\n", "- **About**: Edward shares his background in tech and his experiences, including his previous venture, untapt, which was acquired in 2021.\n", "- **Posts**: The blog section features various resources and announcements related to AI and LLMs.\n", "\n", "## Recent Announcements:\n", "1. **November 13, 2024**: Post on \"Mastering AI and LLM Engineering – Resources\".\n", "2. **October 16, 2024**: Article titled \"From Software Engineer to AI Data Scientist – resources\".\n", "3. **August 6, 2024**: Introduction of \"Outsmart LLM Arena – a battle of diplomacy and deviousness\".\n", "4. **June 26, 2024**: Guide on \"Choosing the Right LLM: Toolkit and Resources\". \n", "\n", "Overall, the website serves as a hub for Edward's thoughts and contributions in the field of AI and LLMs, offering resources for those interested in these topics." ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display_summary(\"https://edwarddonner.com\")" ] }, { "cell_type": "markdown", "id": "b3bcf6f4-adce-45e9-97ad-d9a5d7a3a624", "metadata": {}, "source": [ "# Let's try more websites\n", "\n", "Note that this will only work on websites that can be scraped using this simplistic approach.\n", "\n", "Websites that are rendered with Javascript, like React apps, won't show up. See the community-contributions folder for a Selenium implementation that gets around this. You'll need to read up on installing Selenium (ask ChatGPT!)\n", "\n", "Also Websites protected with CloudFront (and similar) may give 403 errors - many thanks Andy J for pointing this out.\n", "\n", "But many websites will work just fine!" ] }, { "cell_type": "code", "execution_count": 20, "id": "45d83403-a24c-44b5-84ac-961449b4008f", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "## Summary of CNN\n", "\n", "CNN is an extensive news platform offering breaking news, video content, and in-depth analysis across a variety of categories such as US and world news, politics, business, health, entertainment, sports, and lifestyle topics. \n", "\n", "### Key News Highlights\n", "- **Ukraine-Russia War:** Continuous updates and analyses concerning the conflict.\n", "- **Israel-Hamas War:** Ongoing coverage on developments related to the conflict.\n", "- **US Politics:** Coverage includes the actions of former President Trump in relation to immigration and election matters, and discussions surrounding the current political landscape.\n", "- **Global Events:** Notable stories include the aftermath of the Syrian civil war and the implications of the regime change in Syria.\n", "\n", "### Noteworthy Headlines\n", "- **Strikes in Damascus:** Reports indicate strikes heard as rebel forces gain control in Syria.\n", "- **Juan Soto's Contract:** Sports news highlights the record-breaking contract signed by baseball player Juan Soto.\n", "- **Health Insurance CEO's Death:** Coverage includes public reactions to the death of a prominent health insurance CEO.\n", "- **Natural Disasters:** Reports about extreme weather conditions affecting various regions, particularly in Southern California.\n", "\n", "CNN also emphasizes reader engagement, providing options for feedback on its advertisements and service quality, showcasing its commitment to user experience. The platform offers a wide array of resources including live updates, videos, and podcasts, making it a comprehensive source for current events." ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display_summary(\"https://cnn.com\")" ] }, { "cell_type": "code", "execution_count": 21, "id": "75e9fd40-b354-4341-991e-863ef2e59db7", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "# Summary of Anthropic Website\n", "\n", "Anthropic is an AI research company focused on developing reliable and safe AI systems. The site showcases the company's commitment to building AI models that align with human intentions and values. Key features of the website include:\n", "\n", "- **Mission and Values**: Anthropic emphasizes its dedication to research that prioritizes safety and alignment in artificial intelligence development.\n", "- **AI Models**: The company highlights its work on advanced AI models, detailing their capabilities and the ethical considerations involved in their deployment.\n", "- **Research Publications**: Anthropic shares insights from its research efforts, offering access to various papers and findings relating to AI safety and alignment methodologies.\n", "\n", "### News and Announcements\n", "- The website may feature recent developments or updates in AI research, partnerships, or new model releases. Specific announcements may include ongoing initiatives or collaborations in the AI safety field, as well as insights into future projects aimed at enhancing AI's alignment with human values.\n", "\n", "For specific news items and detailed announcements, further exploration of the website is suggested." ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display_summary(\"https://anthropic.com\")" ] }, { "cell_type": "markdown", "id": "c951be1a-7f1b-448f-af1f-845978e47e2c", "metadata": {}, "source": [ "\n", " \n", " \n", " \n", " \n", "
\n", " \n", " \n", "

Business applications

\n", " In this exercise, you experienced calling the Cloud API of a Frontier Model (a leading model at the frontier of AI) for the first time. We will be using APIs like OpenAI at many stages in the course, in addition to building our own LLMs.\n", "\n", "More specifically, we've applied this to Summarization - a classic Gen AI use case to make a summary. This can be applied to any business vertical - summarizing the news, summarizing financial performance, summarizing a resume in a cover letter - the applications are limitless. Consider how you could apply Summarization in your business, and try prototyping a solution.\n", "
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Before you continue - now try yourself

\n", " Use the cell below to make your own simple commercial example. Stick with the summarization use case for now. Here's an idea: write something that will take the contents of an email, and will suggest an appropriate short subject line for the email. That's the kind of feature that might be built into a commercial email tool.\n", "
" ] }, { "cell_type": "code", "execution_count": null, "id": "00743dac-0e70-45b7-879a-d7293a6f68a6", "metadata": {}, "outputs": [], "source": [ "# Step 1: Create your prompts\n", "\n", "system_prompt = \"something here\"\n", "user_prompt = \"\"\"\n", " Lots of text\n", " Can be pasted here\n", "\"\"\"\n", "\n", "# Step 2: Make the messages list\n", "\n", "messages = [] # fill this in\n", "\n", "# Step 3: Call OpenAI\n", "\n", "response =\n", "\n", "# Step 4: print the result\n", "\n", "print(" ] }, { "cell_type": "markdown", "id": "36ed9f14-b349-40e9-a42c-b367e77f8bda", "metadata": {}, "source": [ "## An extra exercise for those who enjoy web scraping\n", "\n", "You may notice that if you try `display_summary(\"https://openai.com\")` - it doesn't work! That's because OpenAI has a fancy website that uses Javascript. There are many ways around this that some of you might be familiar with. For example, Selenium is a hugely popular framework that runs a browser behind the scenes, renders the page, and allows you to query it. If you have experience with Selenium, Playwright or similar, then feel free to improve the Website class to use them. In the community-contributions folder, you'll find an example Selenium solution from a student (thank you!)" ] }, { "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", "PR instructions courtesy of an AI friend: https://chatgpt.com/share/670145d5-e8a8-8012-8f93-39ee4e248b4c" ] }, { "cell_type": "code", "execution_count": null, "id": "682eff74-55c4-4d4b-b267-703edbc293c7", "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": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 5 }