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{
"cells": [
{
"cell_type": "markdown",
"id": "6e9fa1fc-eac5-4d1d-9be4-541b3f2b3458",
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"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"
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