225 lines
7.6 KiB
Plaintext
225 lines
7.6 KiB
Plaintext
{
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"cells": [
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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 os\n",
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"import requests\n",
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"from dotenv import load_dotenv\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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"from openai import OpenAI\n",
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"\n",
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"# If you get an error running this cell, then please head over to the troubleshooting notebook!"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6900b2a8-6384-4316-8aaa-5e519fca4254",
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"metadata": {},
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"source": [
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"# Connecting to OpenAI\n",
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"\n",
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"The next cell is where we load in the environment variables in your `.env` file and connect to OpenAI.\n",
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"\n",
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"## Troubleshooting if you have problems:\n",
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"\n",
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"Head over to the [troubleshooting](troubleshooting.ipynb) notebook in this folder for step by step code to identify the root cause and fix it!\n",
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"\n",
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"If you make a change, try restarting the \"Kernel\" (the python process sitting behind this notebook) by Kernel menu >> Restart Kernel and Clear Outputs of All Cells. Then try this notebook again, starting at the top.\n",
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"\n",
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"Or, contact me! Message me or email ed@edwarddonner.com and we will get this to work.\n",
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"\n",
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"Any concerns about API costs? See my notes in the README - costs should be minimal, and you can control it at every point. You can also use Ollama as a free alternative, which we discuss during Day 2."
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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": "7b87cadb-d513-4303-baee-a37b6f938e4d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load environment variables in a file called .env\n",
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"\n",
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"load_dotenv()\n",
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"api_key = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"# Check the key\n",
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"\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif not api_key.startswith(\"sk-proj-\"):\n",
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" 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",
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"elif api_key.strip() != api_key:\n",
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" 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",
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"else:\n",
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" print(\"API key found and looks good so far!\")\n"
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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": "019974d9-f3ad-4a8a-b5f9-0a3719aea2d3",
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"metadata": {},
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"outputs": [],
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"source": [
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"openai = OpenAI()\n",
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"\n",
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"# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
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"# If it STILL doesn't work (horrors!) then please see the troubleshooting notebook, or try the below line instead:\n",
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"# openai = OpenAI(api_key=\"your-key-here-starting-sk-proj-\")"
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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": "abdb8417-c5dc-44bc-9bee-2e059d162699",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\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.\""
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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": "f0275b1b-7cfe-4f9d-abfa-7650d378da0c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# A function that writes a User Prompt that asks for summaries of websites:\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"
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]
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},
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{
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"cell_type": "markdown",
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"id": "36ed9f14-b349-40e9-a42c-b367e77f8bda",
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"metadata": {},
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"source": [
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"## An extra exercise for those who enjoy web scraping\n",
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"\n",
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"You may notice that if you try the course example with \"https://openai.com\" - it doesn't work! That's because OpenAI has a fancy website that uses Javascript. There are many ways around this that some of you might be familiar with. Below an example created with Playwright."
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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": "dca2768e",
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"metadata": {},
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"outputs": [],
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"source": [
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"! pip install playwright\n",
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"! playwright install"
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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": "682eff74-55c4-4d4b-b267-703edbc293c7",
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"metadata": {},
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"outputs": [],
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"source": [
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"import asyncio\n",
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"from playwright.async_api import async_playwright\n",
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"import nest_asyncio\n",
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"from bs4 import BeautifulSoup\n",
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"import time\n",
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"\n",
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"nest_asyncio.apply()\n",
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"\n",
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"class Website:\n",
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" title: str\n",
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" text: str\n",
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" url: str\n",
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"\n",
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" def __init__(self, url):\n",
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" self.url = url\n",
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" \n",
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" async def run(self, playwright):\n",
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" browser = await playwright.chromium.launch(headless=False)\n",
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" page = await browser.new_page()\n",
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" await page.goto(self.url)\n",
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" await page.wait_for_load_state('load')\n",
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" \n",
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" # Extract data from the page\n",
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" self.title = await page.title()\n",
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" text = await page.content()\n",
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" await browser.close()\n",
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" \n",
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" soup = BeautifulSoup(text, 'html.parser')\n",
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" for irrelevant in soup([\"script\", \"style\", \"img\", \"input\"]):\n",
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" irrelevant.decompose()\n",
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" self.text = soup.get_text(separator=\"\\n\", strip=True)\n",
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" \n",
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" async def main(self):\n",
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" async with async_playwright() as playwright:\n",
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" await self.run(playwright) \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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"if __name__ == \"__main__\":\n",
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" site = Website('https://openai.com')\n",
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" asyncio.run(site.main())\n",
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" response = openai.chat.completions.create(\n",
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" model = \"gpt-4o-mini\",\n",
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" messages = messages_for(site)\n",
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" )\n",
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"\n",
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" web_summary = response.choices[0].message.content\n",
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" display(Markdown(web_summary))"
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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": "69218dec-749c-412d-84a0-40a10fd80c73",
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.11.11"
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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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