124 lines
3.8 KiB
Plaintext
124 lines
3.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "6e9fa1fc-eac5-4d1d-9be4-541b3f2b3458",
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"metadata": {},
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"source": [
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"# Day 2 EXERCISE Solution:\n",
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"\n",
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"Upgraded day 1 project that scrapes and summarizes any webpage using an Open Source model running locally via Ollama instead of OpenAI\n",
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"\n",
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"## Note:-\n",
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"If Ollama is slow on your machine, try using `llama3.2:1b` as an alternative: \n",
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"1. Run `ollama pull llama3.2:1b` from a Terminal or Powershell\n",
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"2. **Ctrl + /** to comment this code line below: `MODEL = \"llama3.2\"`\n",
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"3. same **Ctrl + /** to uncomment: `MODEL = \"llama3.2:1b\"`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4e2a9393-7767-488e-a8bf-27c12dca35bd",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports:-\n",
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"\n",
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"import requests\n",
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"from bs4 import BeautifulSoup\n",
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"from IPython.display import Markdown, display\n",
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"import ollama"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "29ddd15d-a3c5-4f4e-a678-873f56162724",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Constants:-\n",
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"\n",
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"# MODEL = \"llama3.2\"\n",
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"MODEL = \"llama3.2:1b\"\n",
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"# MODEL = \"deepseek-r1:1.5b\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6de38216-6d1c-48c4-877b-86d403f4e0f8",
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"metadata": {},
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"outputs": [],
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"source": [
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"class Website:\n",
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" def __init__(self, url):\n",
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" self.url = url\n",
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" response = requests.get(url)\n",
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" soup = BeautifulSoup(response.content, 'html.parser')\n",
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" self.title = soup.title.string if soup.title else \"No title found\"\n",
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" for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
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" irrelevant.decompose()\n",
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" self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n",
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"\n",
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"\n",
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"system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
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" and provides a short summary, ignoring text that might be navigation related. \\\n",
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" Respond in markdown.\"\n",
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"\n",
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"\n",
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"def user_prompt_for(website):\n",
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" user_prompt = f\"You are looking at a website titled {website.title}\"\n",
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" user_prompt += \"\\nThe contents of this website is as follows; \\\n",
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" please provide a short summary of this website in markdown. \\\n",
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" If it includes news or announcements, then summarize these too.\\n\\n\"\n",
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" user_prompt += website.text\n",
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" return user_prompt\n",
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"\n",
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"\n",
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"def messages_for(website):\n",
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" return [\n",
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" {\"role\": \"system\", \"content\": system_prompt},\n",
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" {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
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" ]\n",
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"\n",
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"\n",
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"def summary(url):\n",
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" website = Website(url)\n",
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" response = ollama.chat(\n",
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" model = MODEL,\n",
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" messages = messages_for(website)\n",
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" )\n",
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" return display(Markdown(response['message']['content']))\n",
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"\n",
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"\n",
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"summary(\"https://edwarddonner.com\")\n",
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"# summary(\"https://cnn.com\")\n",
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"# summary(\"https://anthropic.com\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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