From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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453 lines
15 KiB
453 lines
15 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "e14248ff-07be-4ba8-a13c-d8c7f40ffb5f", |
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"metadata": {}, |
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"source": [ |
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"# A full business solution\n", |
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"## Now we will take our project from Day 1 to the next level\n", |
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"## BUSINESS CHALLENGE:\n", |
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"Create a product that builds a Brochure for a company to be used for prospective clients, investors and potential recruits.\n", |
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"\n", |
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"We will be provided a company name and their primary website.\n", |
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"\n", |
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"See the end of this notebook for examples of real-world business applications.\n", |
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"\n", |
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"And remember: I'm always available if you have problems or ideas! Please do reach out." |
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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": "6c8dc88a-85d9-493b-965c-68895cdd93f2", |
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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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"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": "131c483b-dd58-4faa-baf5-469ab6b00fbb", |
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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()\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[:8]=='sk-proj-':\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? \")\n", |
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"\n", |
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"MODEL='gpt-4o-mini'\n", |
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"openai=OpenAI()\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": "196c0dee-7236-4f88-b7c2-f2a885190b19", |
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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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" \"\"\"\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)\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": "code", |
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"execution_count": null, |
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"id": "f1329717-3727-4987-ada7-75df87a10459", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"ed=Website(\"https://www.anthropic.com/\")\n", |
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"print(ed.get_contents)\n", |
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"ed.links" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "912d4f83-c8f1-437c-a01b-e21988af477c", |
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"metadata": {}, |
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"source": [ |
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"## First step: Have GPT-4o-mini figure out which links are relevant\n", |
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"\n", |
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"### Use a call to gpt-4o-mini to read the links on a webpage, and respond in structured JSON. \n", |
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"It should decide which links are relevant, and replace relative links such as \"/about\" with \"https://company.com/about\". \n", |
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"We will use \"one shot prompting\" in which we provide an example of how it should respond in the prompt.\n", |
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"\n", |
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"This is an excellent use case for an LLM, because it requires nuanced understanding. Imagine trying to code this without LLMs by parsing and analyzing the webpage - it would be very hard!\n", |
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"\n", |
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"Sidenote: there is a more advanced technique called \"Structured Outputs\" in which we require the model to respond according to a spec. We cover this technique in Week 8 during our autonomous Agentic AI project." |
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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": "ed206771-df05-429d-8743-310bc86358ce", |
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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 this example:\"\n", |
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"link_system_prompt+=\"\"\"\n", |
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"{\n", |
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" \"links\":[\n", |
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" {\"type\": \"about page\", \"url\": \"https://full.url/goes/here/about\"},\n", |
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" {\"type\": \"careers page\": \"url\": \"https://another.full.url/careers\"}\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": "ef835a85-9a48-42bd-979e-ca5f51bb1586", |
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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": "code", |
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"execution_count": null, |
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"id": "f2885e89-6455-4239-a98d-5599ea6e5947", |
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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": "da7e4468-a225-4263-a212-94b1c69d38da", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"print(get_links_user_prompt(ed))" |
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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": "53c59051-eed0-4292-8204-abbbd1d78df4", |
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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": "code", |
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"execution_count": null, |
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"id": "76d3d68d-6534-4b04-8a26-a07a9e532665", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"anthropic=Website(\"https://www.anthropic.com/\")\n", |
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"anthropic.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": "12ca6438-bc99-4b45-9603-54bee5d8bce2", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"get_links(\"https://www.anthropic.com/\")" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "4304d6e8-900e-4702-b84c-f202d6265459", |
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"metadata": {}, |
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"source": [ |
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"## Second step: make the brochure!\n", |
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"\n", |
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"Assemble all the details into another prompt to GPT4-o" |
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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": "91ac10e6-8a7a-4367-939b-ac537c1c6c67", |
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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": "code", |
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"execution_count": null, |
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"id": "765e9c71-2bbc-4222-bce1-0f553d8d2b10", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"print(get_all_details(\"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": "7116adc1-6f5e-445f-9869-ffcf5fa6a9b8", |
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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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] |
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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": "02edb903-6352-417f-8c0f-85c2eee269b6", |
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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[:20_000] # Truncate if more than 20,000 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": "2f760069-910e-4209-b357-b97e710f560d", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"get_brochure_user_prompt(\"Anthropic\", \"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": "faf9d9cc-fe30-4441-9adc-aee5b4dc80ca", |
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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))" |
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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": "c8a672f4-ee87-4e2a-a6b1-dfb46f344ef3", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"create_brochure(\"Anthropic\", \"https://anthropic.com\")" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "781fa1db-7acc-41fc-b26c-0d64964eb161", |
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"metadata": {}, |
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"source": [ |
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"## Finally - a minor improvement\n", |
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"\n", |
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"With a small adjustment, we can change this so that the results stream back from OpenAI,\n", |
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"with the familiar typewriter animation" |
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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": "b8359501-9f05-42bc-916c-7990ac910866", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def stream_brochure(company_name, url):\n", |
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" stream= 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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" stream=True\n", |
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" )\n", |
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"\n", |
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" response=\"\"\n", |
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" display_handle=display(Markdown(\"\"),display_id=True)\n", |
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" for chunk in stream:\n", |
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" response +=chunk.choices[0].delta.content or ''\n", |
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" response = response.replace(\"```\",\"\").replace(\"markdown\",\"\")\n", |
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" update_display(Markdown(response),display_id=display_handle.display_id)" |
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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": "cd834aa7-deda-40cd-97ab-5fa5117fc6e0", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"stream_brochure(\"HuggingFace\", \"http://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": "207068f8-d768-46b2-8b92-0ec78a9f71ae", |
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"metadata": {}, |
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"source": [ |
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"# Convert the brochure to a specified language\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": "e75be9e6-040d-4178-a5b3-1b7ae4460bc8", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def create_brochure_language(company_name, url, language):\n", |
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" language_prompt = f\"You are a professional translator and writer specializing in creating and translating brochures. Convert the brochure to {language} while maintaining its original tone, format, and purpose.\"\n", |
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" user_language_prompt = f\"Generate a brochure for the company '{company_name}' available at the URL: {url}, and translate it into {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\": language_prompt},\n", |
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" {\"role\": \"user\", \"content\": user_language_prompt}\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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] |
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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": "0748ec58-335b-4796-ae15-300dee7b24b0", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"create_brochure_language(\"HuggingFace\", \"http://huggingface.co\",\"Hindi\")" |
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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": "ba54f80b-b2cd-4a50-b460-e0d042499c49", |
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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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"cell_type": "code", |
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"execution_count": null, |
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"id": "182f35da-d7b1-40f8-b1a7-74e0cd7fd6fe", |
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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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