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Maksym's day 2 exercise

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Maksym Solomyanov 3 months ago
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commit
252ea7595b
  1. 131
      week1/community-contributions/web-page-summarizer.ipynb

131
week1/community-contributions/web-page-summarizer.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "6418dce8-3ad0-4da9-81de-b3bf57956086",
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"from bs4 import BeautifulSoup\n",
"from IPython.display import Markdown, display"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "75b7849a-841b-4525-90b9-b9fd003516fb",
"metadata": {},
"outputs": [],
"source": [
"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",
" def __init__(self, url):\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": null,
"id": "45c07164-3276-47f3-8620-a5d0ca6a8d24",
"metadata": {},
"outputs": [],
"source": [
"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": null,
"id": "b334629a-cf2a-49fa-b198-edd73493720f",
"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 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"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e4dd0855-302d-4423-9b8b-80c4bbb9ab31",
"metadata": {},
"outputs": [],
"source": [
"website = Website(\"https://cnn.com\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "65c6cc43-a16a-4337-8c3d-4ab10ee0377a",
"metadata": {},
"outputs": [],
"source": [
"messages = [\n",
" {\"role\": \"system\", \"content\": system_prompt},\n",
" {\"role\": \"user\", \"content\": user_prompt_for(website)}]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "59799f7b-a244-4572-9296-34e4b87ba026",
"metadata": {},
"outputs": [],
"source": [
"import ollama\n",
"\n",
"MODEL = \"llama3.2\"\n",
"response = ollama.chat(model=MODEL, messages=messages)\n",
"print(response['message']['content'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a0c03050-60d2-4165-9d8a-27eb57455704",
"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": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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