From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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379 lines
13 KiB
379 lines
13 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "a98030af-fcd1-4d63-a36e-38ba053498fa", |
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"metadata": {}, |
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"source": [ |
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"# Snarky brochure" |
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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": "d5b08506-dc8b-4443-9201-5f1848161363", |
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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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"# If these fail, please check you're running from an 'activated' environment with (llms) in the command prompt\n", |
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"\n", |
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"import os\n", |
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"import requests\n", |
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"import json\n", |
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"from typing import List\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, update_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": "code", |
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"execution_count": null, |
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"id": "fc5d8880-f2ee-4c06-af16-ecbc0262af61", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Initialize and constants\n", |
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"\n", |
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"load_dotenv(override=True)\n", |
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"api_key = os.getenv('OPENAI_API_KEY')\n", |
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"\n", |
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"if api_key and api_key.startswith('sk-proj-') and len(api_key)>10:\n", |
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" print(\"API key looks good so far\")\n", |
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"else:\n", |
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" print(\"There might be a problem with your API key? Please visit the troubleshooting notebook!\")\n", |
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" \n", |
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"MODEL = 'gpt-4o-mini'\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": "106dd65e-90af-4ca8-86b6-23a41840645b", |
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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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"# Some websites need you to use proper headers when fetching them:\n", |
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"headers = {\n", |
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" \"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", |
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"}\n", |
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"\n", |
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"class Website:\n", |
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" \"\"\"\n", |
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" A utility class to represent a Website that we have scraped, now with links\n", |
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" \"\"\"\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, headers=headers)\n", |
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" self.body = response.content\n", |
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" soup = BeautifulSoup(self.body, 'html.parser')\n", |
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" self.title = soup.title.string if soup.title else \"No title found\"\n", |
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" if soup.body:\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)\n", |
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" else:\n", |
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" self.text = \"\"\n", |
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" links = [link.get('href') for link in soup.find_all('a')]\n", |
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" self.links = [link for link in links if link]\n", |
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"\n", |
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" def get_contents(self):\n", |
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" return f\"Webpage Title:\\n{self.title}\\nWebpage Contents:\\n{self.text}\\n\\n\"" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "1771af9c-717a-4fca-bbbe-8a95893312c3", |
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"metadata": {}, |
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"source": [ |
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"## Link prompts\n", |
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"### Multi-shot system prompt" |
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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": "6957b079-0d96-45f7-a26a-3487510e9b35", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"link_system_prompt = \"You are provided with a list of links found on a webpage. \\\n", |
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"You are able to decide which of the links would be most relevant to include in a brochure about the company, \\\n", |
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"such as links to an About page, or a Company page, or Careers/Jobs pages.\\n\"\n", |
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"link_system_prompt += \"You should respond in JSON as in these examples:\"\n", |
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"link_system_prompt += \"\"\"\n", |
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"Example 1\n", |
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"['https://my-company.com', 'https://my-company.com/about-me', 'https://www.linkedin.com/in/my-company/', 'mailto:joe.blog@gmail.com', 'https://my-company.com/news', '/case-studies', 'https://patents.google.com/patent/US20210049536A1/', 'https://my-company.com/workshop-ai']\n", |
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"\n", |
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" Links:\n", |
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"{\n", |
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" \"links\": [\n", |
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" {\"type\": \"landing page\", \"url\": \"https://great-comps.com/about-me\"},\n", |
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" {\"type\": \"about page\", \"url\": \"https://great-comps.com/about-me\"},\n", |
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" {\"type\": \"news page\": \"url\": \"https://great-comps.com/news\"},\n", |
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" {\"type\": \"case studies page\": \"url\": \"https://great-comps.com/case-studies\"},\n", |
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" {\"type\": \"workshop page\": \"url\": \"https://great-comps.com/workshop-ai\"},\n", |
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" ]\n", |
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"}\n", |
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"Example 2\n", |
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"['https://www.acmeinc.com', '/#about', '/#projects', '/#experience', '/#skills', 'https://github.com/acmeinc']\n", |
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"\n", |
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" Links:\n", |
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"{\n", |
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" \"links\": [\n", |
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" {\"type\": \"landing page\", \"url\": \"https://www.acmeinc.com\"},\n", |
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" {\"type\": \"GitHub projects\": \"url\": \"https://github.com/acmeinc\"},\n", |
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" ]\n", |
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"}\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": "b97e4068-97ed-4120-beae-c42105e4d59a", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"print(link_system_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": "baf384bb-4577-4885-a445-dc8da232b1d9", |
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"metadata": {}, |
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"source": [ |
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"### 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": "51174859-666a-43ad-9c34-5f082298d398", |
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"metadata": {}, |
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"source": [ |
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"## Get links" |
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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": "8e1f601b-2eaf-499d-b6b8-c99050c9d6b3", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def get_links_user_prompt(website):\n", |
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" user_prompt = f\"Here is the list of links on the website of {website.url} - \"\n", |
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" user_prompt += \"please decide which of these are relevant web links for a brochure about the company, respond with the full https URL in JSON format. \\\n", |
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"Do not include Terms of Service, Privacy, email links.\\n\"\n", |
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" user_prompt += \"Links (some might be relative links):\\n\"\n", |
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" user_prompt += \"\\n\".join(website.links)\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": "code", |
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"execution_count": null, |
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"id": "a29aca19-ca13-471c-a4b4-5abbfa813f69", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def get_links(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=MODEL,\n", |
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" messages=[\n", |
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" {\"role\": \"system\", \"content\": link_system_prompt},\n", |
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" {\"role\": \"user\", \"content\": get_links_user_prompt(website)}\n", |
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" ],\n", |
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" response_format={\"type\": \"json_object\"}\n", |
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" )\n", |
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" result = response.choices[0].message.content\n", |
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" return json.loads(result)" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "0d74128e-dfb6-47ec-9549-288b621c838c", |
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"metadata": {}, |
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"source": [ |
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"## Create brochure" |
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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": "85a5b6e2-e7ef-44a9-bc7f-59ede71037b5", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def get_all_details(url):\n", |
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" result = \"Landing page:\\n\"\n", |
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" result += Website(url).get_contents()\n", |
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" links = get_links(url)\n", |
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" print(\"Found links:\", links)\n", |
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" for link in links[\"links\"]:\n", |
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" result += f\"\\n\\n{link['type']}\\n\"\n", |
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" result += Website(link[\"url\"]).get_contents()\n", |
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" return result" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "4b4d8ec1-4855-4c0e-afc0-33055e6b0a6d", |
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"metadata": {}, |
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"source": [ |
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"### Snarky system prompt" |
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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": "9b863a55-f86c-4e3f-8a79-94e24c1a8cf2", |
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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 several relevant pages from a company website \\\n", |
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"# and creates a short brochure about the company for prospective customers, investors and recruits. Respond in markdown.\\\n", |
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"# Include details of company culture, customers and careers/jobs if you have the information.\"\n", |
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"\n", |
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"# Or uncomment the lines below for a more humorous brochure - this demonstrates how easy it is to incorporate 'tone':\n", |
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"\n", |
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"# system_prompt = \"You are an assistant that analyzes the contents of several relevant pages from a company website \\\n", |
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"# and creates a short humorous, entertaining, jokey brochure about the company for prospective customers, investors and recruits. Respond in markdown.\\\n", |
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"# Include details of company culture, customers and careers/jobs if you have the information.\"\n", |
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"\n", |
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"system_prompt = \"You are an assistant that analyzes the contents of several relevant pages from a company website \\\n", |
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"and creates a short snarky, entertaining, pun loaded brochure about the company for prospective customers, investors and recruits. Respond in markdown.\\\n", |
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"Include details of company culture, customers and careers/jobs if you have the information.\"\n" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "c5766318-97cc-4442-bb9f-fa8c6998777e", |
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"metadata": {}, |
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"source": [ |
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"### 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": "d6e224b2-8ab0-476e-96c3-42763ad21f25", |
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"metadata": {}, |
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"source": [ |
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"### Generate brochure in English" |
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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": "6ab83d92-d36b-4ce0-8bcc-5bb4c2f8ff23", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def get_brochure_user_prompt(company_name, url):\n", |
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" user_prompt = f\"You are looking at a company called: {company_name}\\n\"\n", |
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" user_prompt += f\"Here are the contents of its landing page and other relevant pages; use this information to build a short brochure of the company in markdown.\\n\"\n", |
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" user_prompt += get_all_details(url)\n", |
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" user_prompt = user_prompt[:5_000] # Truncate if more than 5,000 characters\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": "code", |
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"execution_count": null, |
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"id": "e44de579-4a1a-4e6a-a510-20ea3e4b8d46", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def create_brochure(company_name, url):\n", |
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" response = openai.chat.completions.create(\n", |
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" model=MODEL,\n", |
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" messages=[\n", |
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" {\"role\": \"system\", \"content\": system_prompt},\n", |
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" {\"role\": \"user\", \"content\": get_brochure_user_prompt(company_name, url)}\n", |
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" ],\n", |
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" )\n", |
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" result = response.choices[0].message.content\n", |
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" display(Markdown(result))\n", |
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" return result" |
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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": "e093444a-9407-42ae-924a-145730591a39", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"brochure_text = create_brochure(\"HuggingFace\", \"https://huggingface.co\")" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "30415c72-d26a-454e-8900-f584977aca96", |
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"metadata": {}, |
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"source": [ |
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"### Translate brochure to another language" |
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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": "2331eb34-12bf-4e88-83f9-a48d97cc83ec", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"translation_sys_prompt = \"You are a language translator who is very good at translating business documents from \\\n", |
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"English to any language. You preserve the formatting, tone and facts contained in the document.\"\n", |
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"\n", |
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"def translate_brochure(brochure, language):\n", |
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" response = openai.chat.completions.create(\n", |
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" model=MODEL,\n", |
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" messages=[\n", |
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" {\"role\": \"system\", \"content\": translation_sys_prompt},\n", |
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" {\"role\": \"user\", \"content\": f\"Translate the following document into {language}: {brochure}\"}\n", |
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" ],\n", |
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" )\n", |
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" result = response.choices[0].message.content\n", |
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" display(Markdown(result))" |
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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": "112beb4d-984b-4162-8d36-8cef79c351cc", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"translate_brochure(brochure_text, \"Spanish\")" |
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] |
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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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