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Added contribution 'PPT Summariser' to community-contributions

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Zoya Hammad 3 months ago
parent
commit
ed8256afe5
  1. 223
      week1/community-contributions/day1_ppt_summariser.ipynb

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week1/community-contributions/day1_ppt_summariser.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "bfa3abd0-4e66-4117-96f9-7a71fbb6d0cb",
"metadata": {},
"source": [
"# Powerpoint Slides Summarizer\n",
"\n",
"This converts a Power Point presentation into notes that a student can easily skim through.\n",
"\n",
"Concepts Used:\n",
"- Converting Contents of PPT to text via python-pptx\n",
"- User and System Prompts\n",
"- Use of Open AI GPT-4o-mini via API key\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ab95eb49-6a2d-4c7d-9057-78a2cd9364cc",
"metadata": {},
"outputs": [],
"source": [
"!pip install python-pptx"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "62715f16-7125-455e-98e7-5705871c0e4a",
"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": null,
"id": "ff42eab7-789d-44f8-a5cc-64baeebf3224",
"metadata": {},
"outputs": [],
"source": [
"# Load environment variables in a file called .env\n",
"\n",
"load_dotenv(override=True)\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": null,
"id": "bce425c2-6d19-4c03-93ce-8930dabc61ee",
"metadata": {},
"outputs": [],
"source": [
"# creating an instance\n",
"openai = OpenAI()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c0c75e30-3b38-4a89-b7d3-a41a6f5dc650",
"metadata": {},
"outputs": [],
"source": [
"from pptx import Presentation\n",
"\n",
"class PowerPoint():\n",
" def __init__(self,ppt):\n",
" \"\"\"\n",
" Creates a PowerPoint object, with name and text.\n",
" \"\"\"\n",
" self.ppt = ppt\n",
" self.title = os.path.basename(ppt)\n",
" self.text = self.extract_text()\n",
"\n",
" def extract_text(self):\n",
" \"\"\"\n",
" Extracts text from powerpoint.\n",
" \"\"\"\n",
" prs = Presentation(self.ppt)\n",
" text_content = []\n",
" \n",
" for slide in prs.slides:\n",
" for shape in slide.shapes:\n",
" if hasattr(shape, \"text\"):\n",
" text_content.append(shape.text)\n",
" \n",
" return \"\\n\".join(text_content)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1963a055-87f4-4e47-8456-cac4d4ac57fc",
"metadata": {},
"outputs": [],
"source": [
"system_prompt = \"You are an assistant that analyzes the contents \\\n",
"of a PowerPoint presentation, and provides a summary in the style of \\\n",
"a cheat-sheet, for students to easily learn key concepts from.\\\n",
"You are to ignore text that might be navigation-related\\\n",
"and respond in Markdown.\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ca600e90-7d3f-4fc7-a698-1b8f2925f81e",
"metadata": {},
"outputs": [],
"source": [
"# A function that writes a User Prompt that asks for summaries of PowerPoints:\n",
"\n",
"def user_prompt_for(powerpoint):\n",
" user_prompt = f\"You are looking at a website titled {powerpoint.title}\"\n",
" user_prompt += \"\\nThe contents of this powerpoint are as follows; \\\n",
"please provide a summary of the content in markdown. \\\n",
"If it includes a question bank, add that along with short answers too.\\n\\n\"\n",
" user_prompt += powerpoint.text\n",
" return user_prompt"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4fe19c56-9940-4528-b43a-c86798b215d2",
"metadata": {},
"outputs": [],
"source": [
"def messages_for(powerpoint):\n",
" return [\n",
" {\"role\": \"system\", \"content\": system_prompt},\n",
" {\"role\": \"user\", \"content\": user_prompt_for(powerpoint)}\n",
" ]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f7704da5-90b0-40af-bbb4-7d589309f180",
"metadata": {},
"outputs": [],
"source": [
"# And now: call the OpenAI API. \n",
"\n",
"def summarize(powerpoint_path):\n",
" powerpoint = PowerPoint(powerpoint_path)\n",
" response = openai.chat.completions.create(\n",
" model = \"gpt-4o-mini\",\n",
" messages = messages_for(powerpoint)\n",
" )\n",
" return response.choices[0].message.content"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "49d1d0cf-fa4b-4bea-bd68-a834145070ef",
"metadata": {},
"outputs": [],
"source": [
"def display_summary(url):\n",
" summary = summarize(url)\n",
" display(Markdown(summary))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "348078d1-e86f-4eb3-909d-33ab4ede984e",
"metadata": {},
"outputs": [],
"source": [
"ppt_file = \"Theoretical Perspectives on Media and Technology.pptx\" \n",
"display_summary(ppt_file)"
]
}
],
"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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