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{
"cells": [
{
"cell_type": "markdown",
"id": "9ae10427-6ca2-4ac0-b6a0-e9206dd3cb52",
"metadata": {},
"source": [
"### Using OpenAI gpt-4o-mini model to generate social media posts for events"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "477fe060-a11f-424f-bac4-34c5121cf437",
"metadata": {},
"outputs": [],
"source": [
"# imports\n",
"\n",
"import os\n",
"import requests\n",
"from dotenv import load_dotenv\n",
"from bs4 import BeautifulSoup\n",
"from IPython.display import Markdown, display\n",
"from openai import OpenAI"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "61f012e5-cdba-48cb-ae74-df9659c23d90",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"API key found and looks good so far!\n"
]
}
],
"source": [
"# Load environment variables in a file called .env\n",
"\n",
"load_dotenv()\n",
"api_key = os.getenv('OPENAI_API_KEY')\n",
"\n",
"# Check the key\n",
"\n",
"if not api_key:\n",
" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
"elif not api_key.startswith(\"sk-proj-\"):\n",
" print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
"elif api_key.strip() != api_key:\n",
" print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
"else:\n",
" print(\"API key found and looks good so far!\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "19c79615-57aa-40e0-a83b-891f43df4f65",
"metadata": {},
"outputs": [],
"source": [
"openai = OpenAI()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "68ad05f8-dfcc-47b1-ba16-b35bedeff48b",
"metadata": {},
"outputs": [],
"source": [
"# A class to represent a Webpage\n",
"# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n",
"\n",
"# Some websites need you to use proper headers when fetching them:\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)\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": 14,
"id": "acff6c95-77a5-40f0-bf9f-7d47cec987fc",
"metadata": {},
"outputs": [],
"source": [
"# See how this function creates exactly the format above\n",
"\n",
"def messages_for(website):\n",
" return [\n",
" {\"role\": \"system\", \"content\": \"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",
" {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
" ]\n",
"\n",
"# A function that writes a User Prompt that asks for summaries of websites:\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",
"# Generate a summary of content fetched by scraping the website\n",
"\n",
"def summarize(url):\n",
" website = Website(url)\n",
" response = openai.chat.completions.create(\n",
" model = \"gpt-4o-mini\",\n",
" messages = messages_for(website)\n",
" )\n",
" return response.choices[0].message.content"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "b43f8cda-8a61-4773-83b2-bb8fe55a0cb2",
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"**Twitter Post:** \n",
"🚀 Join us online for #StartupMastery on Jan 7, 6-9 PM GMT! Explore Lean Startup, Agile, & Design Thinking methodologies. Gain practical skills, access resources, and earn a certificate! Tickets from €74.98. Don't miss out! 🎟️🌟\n",
"\n",
"**Instagram Post:** \n",
"🌟 Ready to boost your startup skills? Join us for **Startup Mastery**! 💡 On January 7 from 6 PM to 9 PM GMT, dive into Lean Startup, Agile, and Design Thinking with top-notch experts. Access recorded sessions, worksheets, and get certified! 🎟️ Tickets from €74.98. See you online! 🚀✨ #StartupMastery #LeanStartup #Agile #DesignThinking\n",
"\n",
"**Facebook Post:** \n",
"🗓️ Exciting opportunity for entrepreneurs and startup enthusiasts! Attend our **Startup Mastery** online workshop on January 7, from 6 PM to 9 PM GMT. Learn about Lean Startup, Agile, and Design Thinking methodologies to enhance your startup journey. Enjoy a transformative experience with insights on MVP development, rapid prototyping, and feedback loops. Plus, you'll get access to recorded sessions and can earn a certificate! Limited tickets available from €74.98. Organizers: Lean Agile Zone. Don’t miss out! 🚀 #StartupMastery #Entrepreneurship"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Step 1: Create your prompts\n",
"WEBSITE_LINK = \"https://www.eventbrite.ie/e/startup-mastery-leveraging-lean-startup-agile-and-design-thinking-tickets-920474252267?aff=ebdssbcategorybrowse&keep_tld=1\"\n",
"\n",
"system_prompt = \"You are an assistant that analyzes the contents of an event \\\n",
"and provides short summaries for a Twitter post, an instagram post and a facebook post.\\\n",
"Ensure the summaries abide by the platform rules for each of the platforms.\"\n",
"\n",
"website_summary = summarize(WEBSITE_LINK)\n",
"user_prompt = f\"The events details are as follows: {website_summary}. Please summarize the above. Capture details like time and location, please capture them as well.\"\n",
"\n",
"# Step 2: Make the messages list\n",
"\n",
"messages = [\n",
" {\"role\": \"system\", \"content\": system_prompt},\n",
" {\"role\": \"user\", \"content\": user_prompt},\n",
"]\n",
"\n",
"# Step 3: Call OpenAI\n",
"\n",
"response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=messages)\n",
"\n",
"# Step 4: print the result\n",
"\n",
"display(Markdown(response.choices[0].message.content))"
]
}
],
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"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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