From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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291 lines
8.6 KiB
291 lines
8.6 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "d15d8294-3328-4e07-ad16-8a03e9bbfdb9", |
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"metadata": {}, |
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"source": [ |
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"# Instant Gratification!\n", |
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"\n", |
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"Let's build a useful LLM solution - in a matter of minutes.\n", |
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"\n", |
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"Our goal is to code a new kind of Web Browser. Give it a URL, and it will respond with a summary. The Reader's Digest of the internet!!\n", |
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"\n", |
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"Before starting, be sure to have followed the instructions in the \"README\" file, including creating your API key with OpenAI and adding it to the `.env` file." |
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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 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" |
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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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"1. OpenAI takes a few minutes to register after you set up an account. If you receive an error about being over quota, try waiting a few minutes and try again.\n", |
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"2. Also, double check you have the right kind of API token with the right permissions. You should find it on [this webpage](https://platform.openai.com/api-keys) and it should show with Permissions of \"All\". If not, try creating another key by:\n", |
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"- Pressing \"Create new secret key\" on the top right\n", |
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"- Select **Owned by:** you, **Project:** Default project, **Permissions:** All\n", |
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"- Click Create secret key, and use that new key in the code and the `.env` file (it might take a few minutes to activate)\n", |
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"4. As a fallback, replace the line `openai = OpenAI()` with `openai = OpenAI(api_key=\"your-key-here\")` - while it's not recommended to hard code tokens in Jupyter lab, because then you can't share your lab with others, it's a workaround for now\n", |
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"5. 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." |
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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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"os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n", |
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"openai = OpenAI()" |
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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": "c5e793b2-6775-426a-a139-4848291d0463", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# A class to represent a Webpage\n", |
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"\n", |
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"class Website:\n", |
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" url: str\n", |
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" title: str\n", |
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" text: 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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" 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)" |
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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": "2ef960cf-6dc2-4cda-afb3-b38be12f4c97", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Let's try one out\n", |
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"\n", |
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"ed = Website(\"https://edwarddonner.com\")\n", |
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"print(ed.title)\n", |
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"print(ed.text)" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "6a478a0c-2c53-48ff-869c-4d08199931e1", |
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"metadata": {}, |
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"source": [ |
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"## Types of prompts\n", |
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"\n", |
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"You may know this already - but if not, you will get very familiar with it!\n", |
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"\n", |
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"Models like GPT4o have been trained to receive instructions in a particular way.\n", |
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"\n", |
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"They expect to receive:\n", |
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"\n", |
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"**A system prompt** that tells them what task they are performing and what tone they should use\n", |
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"\n", |
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"**A user prompt** -- the conversation starter that they should reply to" |
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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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"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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"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 += \"The 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": "ea211b5f-28e1-4a86-8e52-c0b7677cadcc", |
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"metadata": {}, |
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"source": [ |
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"## Messages\n", |
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"\n", |
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"The API from OpenAI expects to receive messages in a particular structure.\n", |
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"Many of the other APIs share this structure:\n", |
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"\n", |
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"```\n", |
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"[\n", |
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" {\"role\": \"system\", \"content\": \"system message goes here\"},\n", |
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" {\"role\": \"user\", \"content\": \"user message goes here\"}\n", |
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"]" |
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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": "0134dfa4-8299-48b5-b444-f2a8c3403c88", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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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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" ]" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "16f49d46-bf55-4c3e-928f-68fc0bf715b0", |
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"metadata": {}, |
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"source": [ |
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"## Time to bring it together - the API for OpenAI is very simple!" |
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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": "905b9919-aba7-45b5-ae65-81b3d1d78e34", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def summarize(url):\n", |
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" website = Website(url)\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(website)\n", |
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" )\n", |
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" return response.choices[0].message.content" |
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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": "05e38d41-dfa4-4b20-9c96-c46ea75d9fb5", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"summarize(\"https://edwarddonner.com\")" |
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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": "3d926d59-450e-4609-92ba-2d6f244f1342", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def display_summary(url):\n", |
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" summary = summarize(url)\n", |
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" display(Markdown(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": "3018853a-445f-41ff-9560-d925d1774b2f", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"display_summary(\"https://edwarddonner.com\")" |
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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": "45d83403-a24c-44b5-84ac-961449b4008f", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"display_summary(\"https://cnn.com\")" |
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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": "75e9fd40-b354-4341-991e-863ef2e59db7", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"display_summary(\"https://anthropic.com\")" |
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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": "49c4315f-340b-4371-b6cd-2a772f4b7bdd", |
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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": "3.11.10" |
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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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