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+{
+ "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",
+ " 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",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6e9fa1fc-eac5-4d1d-9be4-541b3f2b3458",
+ "metadata": {},
+ "source": [
+ "# HOMEWORK EXERCISE ASSIGNMENT\n",
+ "\n",
+ "Upgrade the day 1 project to summarize a webpage to use an Open Source model running locally via Ollama rather than OpenAI\n",
+ "\n",
+ "You'll be able to use this technique for all subsequent projects if you'd prefer not to use paid APIs.\n",
+ "\n",
+ "**Benefits:**\n",
+ "1. No API charges - open-source\n",
+ "2. Data doesn't leave your box\n",
+ "\n",
+ "**Disadvantages:**\n",
+ "1. Significantly less power than Frontier Model\n",
+ "\n",
+ "## Recap on installation of Ollama\n",
+ "\n",
+ "Simply visit [ollama.com](https://ollama.com) and install!\n",
+ "\n",
+ "Once complete, the ollama server should already be running locally. \n",
+ "If you visit: \n",
+ "[http://localhost:11434/](http://localhost:11434/)\n",
+ "\n",
+ "You should see the message `Ollama is running`. \n",
+ "\n",
+ "If not, bring up a new Terminal (Mac) or Powershell (Windows) and enter `ollama serve` \n",
+ "And in another Terminal (Mac) or Powershell (Windows), enter `ollama pull llama3.2` \n",
+ "Then try [http://localhost:11434/](http://localhost:11434/) again.\n",
+ "\n",
+ "If Ollama is slow on your machine, try using `llama3.2:1b` as an alternative. Run `ollama pull llama3.2:1b` from a Terminal or Powershell, and change the code below from `MODEL = \"llama3.2\"` to `MODEL = \"llama3.2:1b\"`"
+ ]
+ },
+ {
+ "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"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "29ddd15d-a3c5-4f4e-a678-873f56162724",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Constants\n",
+ "\n",
+ "OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
+ "HEADERS = {\"Content-Type\": \"application/json\"}\n",
+ "MODEL = \"llama3.2\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dac0a679-599c-441f-9bf2-ddc73d35b940",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a messages list using the same format that we used for OpenAI\n",
+ "\n",
+ "messages = [\n",
+ " {\"role\": \"user\", \"content\": \"Describe some of the business applications of Generative AI\"}\n",
+ "]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7bb9c624-14f0-4945-a719-8ddb64f66f47",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "payload = {\n",
+ " \"model\": MODEL,\n",
+ " \"messages\": messages,\n",
+ " \"stream\": False\n",
+ " }"
+ ]
+ },
+ {
+ "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": "code",
+ "execution_count": null,
+ "id": "42b9f644-522d-4e05-a691-56e7658c0ea9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# If this doesn't work for any reason, try the 2 versions in the following cells\n",
+ "# And double check the instructions in the 'Recap on installation of Ollama' at the top of this lab\n",
+ "# And if none of that works - contact me!\n",
+ "\n",
+ "response = requests.post(OLLAMA_API, json=payload, headers=HEADERS)\n",
+ "print(response.json()['message']['content'])"
+ ]
+ },
+ {
+ "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": "code",
+ "execution_count": null,
+ "id": "7745b9c4-57dc-4867-9180-61fa5db55eb8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import ollama\n",
+ "\n",
+ "response = ollama.chat(model=MODEL, messages=messages)\n",
+ "print(response['message']['content'])"
+ ]
+ },
+ {
+ "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",
+ "from openai import OpenAI\n",
+ "ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n",
+ "\n",
+ "response = ollama_via_openai.chat.completions.create(\n",
+ " model=MODEL,\n",
+ " messages=messages\n",
+ ")\n",
+ "\n",
+ "print(response.choices[0].message.content)"
+ ]
+ },
+ {
+ "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": "ef76cfc2-c519-4cb2-947a-64948517913d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# imports\n",
+ "\n",
+ "import requests\n",
+ "from bs4 import BeautifulSoup\n",
+ "from IPython.display import Markdown, display"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a151a8de-1e90-4190-b68e-b44b25a2cdd7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Constants\n",
+ "\n",
+ "OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
+ "HEADERS = {\"Content-Type\": \"application/json\"}\n",
+ "MODEL = \"llama3.2\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "700fffc1-c7b0-4001-b381-5c4fd28c8799",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Reusing the Website BeautifulSoup wrapper from Day 1\n",
+ "# SSL Verification has been disabled\n",
+ "\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, verify=False) # NOTE Disabled ssl verification here to workaround VPN Limitations\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)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "402d5686-4e76-4110-b65a-b3906c35c0a4",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "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 are 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": "81f5f140-8f77-418f-a252-8ad5d11f6c5f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "## enter the web URL here:\n",
+ "website_url = \"https://www.timecube.net/\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1d0ce4aa-b43e-4642-bcbd-d5964700ece8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "## This will at first print a warning for SSL which can be ignored before providing response. \n",
+ "\n",
+ "import ollama\n",
+ "\n",
+ "system_prompt = \"You are a virtual assistant who 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",
+ "messages = [\n",
+ " {\"role\": \"system\", \"content\": system_prompt},\n",
+ " {\"role\": \"user\", \"content\": user_prompt_for(Website(website_url))}\n",
+ "]\n",
+ "\n",
+ "response = ollama.chat(model=MODEL, messages=messages)\n",
+ "print(response['message']['content'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "910b7e06-c92d-47bf-a4ee-a006d70deb06",
+ "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",
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+ }
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