diff --git a/week1/community-contributions/Day2-Solution-Ollama.ipynb b/week1/community-contributions/Day2-Solution-Ollama.ipynb new file mode 100644 index 0000000..2d67c7b --- /dev/null +++ b/week1/community-contributions/Day2-Solution-Ollama.ipynb @@ -0,0 +1,123 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e9fa1fc-eac5-4d1d-9be4-541b3f2b3458", + "metadata": {}, + "source": [ + "# Day 2 EXERCISE Solution:\n", + "\n", + "Upgraded day 1 project that scrapes and summarizes any webpage using an Open Source model running locally via Ollama instead of OpenAI\n", + "\n", + "## Note:-\n", + "If Ollama is slow on your machine, try using `llama3.2:1b` as an alternative: \n", + "1. Run `ollama pull llama3.2:1b` from a Terminal or Powershell\n", + "2. **Ctrl + /** to comment this code line below: `MODEL = \"llama3.2\"`\n", + "3. same **Ctrl + /** to uncomment: `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\n", + "import ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "29ddd15d-a3c5-4f4e-a678-873f56162724", + "metadata": {}, + "outputs": [], + "source": [ + "# Constants:-\n", + "\n", + "# MODEL = \"llama3.2\"\n", + "MODEL = \"llama3.2:1b\"\n", + "# MODEL = \"deepseek-r1:1.5b\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6de38216-6d1c-48c4-877b-86d403f4e0f8", + "metadata": {}, + "outputs": [], + "source": [ + "class Website:\n", + " def __init__(self, url):\n", + " self.url = url\n", + " response = requests.get(url)\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", + "\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", + "\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", + "\n", + "def messages_for(website):\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", + " ]\n", + "\n", + "\n", + "def summary(url):\n", + " website = Website(url)\n", + " response = ollama.chat(\n", + " model = MODEL,\n", + " messages = messages_for(website)\n", + " )\n", + " return display(Markdown(response['message']['content']))\n", + "\n", + "\n", + "summary(\"https://edwarddonner.com\")\n", + "# summary(\"https://cnn.com\")\n", + "# summary(\"https://anthropic.com\")" + ] + } + ], + "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": "3.10.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}