diff --git a/week1/community-contributions/wk1-day5-CHALLENGE.ipynb b/week1/community-contributions/wk1-day5-CHALLENGE.ipynb new file mode 100644 index 0000000..8b828aa --- /dev/null +++ b/week1/community-contributions/wk1-day5-CHALLENGE.ipynb @@ -0,0 +1,208 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import requests\n", + "import json\n", + "from typing import List\n", + "from dotenv import load_dotenv\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display, update_display, clear_output\n", + "import openai\n", + "\n", + "load_dotenv(override=True)\n", + "api_key = os.getenv('OPENAI_API_KEY')\n", + "\n", + "if api_key and api_key.startswith('sk-proj-') and len(api_key)>10:\n", + " print(\"API key looks good so far\")\n", + "else:\n", + " print(\"There might be a problem with your API key? Please visit the troubleshooting notebook!\")\n", + "\n", + "MODEL = 'gpt-4o-mini'\n", + "\n", + "headers = {\n", + " \"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", + "}\n", + "\n", + "# Prompt user for company name and URL\n", + "company_name = input(\"Enter the company name: \")\n", + "url = input(\"Enter the company URL: \")\n", + "\n", + "class Website:\n", + " \"\"\"\n", + " A utility class to represent a Website that we have scraped, now with links\n", + " \"\"\"\n", + "\n", + " def __init__(self, url):\n", + " self.url = url\n", + " response = requests.get(url, headers=headers)\n", + " self.body = response.content\n", + " soup = BeautifulSoup(self.body, 'html.parser')\n", + " self.title = soup.title.string if soup.title else \"No title found\"\n", + " if soup.body:\n", + " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", + " irrelevant.decompose()\n", + " self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n", + " else:\n", + " self.text = \"\"\n", + " links = [link.get('href') for link in soup.find_all('a')]\n", + " self.links = [link for link in links if link]\n", + "\n", + " def get_contents(self):\n", + " return f\"Webpage Title:\\n{self.title}\\nWebpage Contents:\\n{self.text}\\n\\n\"\n", + "# multi-shot prompt\n", + "link_system_prompt = \"You are provided with a list of links found on a webpage. \\You are able to decide which of the links would be most relevant to include in a brochure about the company, \\such as links to an About page, or a Company page, or Careers/Jobs pages.\\n\"\n", + "link_system_prompt += \"You should respond in JSON as in this example:\"\n", + "link_system_prompt += \"\"\"\n", + " EXAMPLE 1:\n", + " {\n", + " \"links\": [\n", + " {\"type\": \"about page\", \"url\": \"https://full.url/goes/here/about\"},\n", + " {\"type\": \"careers page\", \"url\": \"https://another.full.url/careers\"}\n", + " ]\n", + " }\n", + " EXAMPLE 2:\n", + " {\n", + " \"links\": [\n", + " {\"type\": \"company blog\", \"url\": \"https://blog.example.com\"},\n", + " {\"type\": \"our story\", \"url\": \"https://example.com/our-story\"}\n", + " ]\n", + " }\n", + " \"\"\"\n", + "\n", + "def get_links_user_prompt(website):\n", + " user_prompt = f\"Here is the list of links on the website of {website.url} - \"\n", + " 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. \\ Do not include Terms of Service, Privacy, email links.\\n\"\n", + " user_prompt += \"Links (some might be relative links):\\n\"\n", + " user_prompt += \"\\n\".join(website.links)\n", + " return user_prompt\n", + "\n", + "\n", + "def get_links(url):\n", + " website = Website(url)\n", + " response = openai.chat.completions.create(\n", + " model=MODEL,\n", + " messages=[\n", + " {\"role\": \"system\", \"content\": link_system_prompt},\n", + " {\"role\": \"user\", \"content\": get_links_user_prompt(website)}\n", + " ],\n", + " response_format={\"type\": \"json_object\"}\n", + " )\n", + " result = response.choices[0].message.content\n", + " return json.loads(result)\n", + "\n", + "def get_all_details(url):\n", + " result = \"Landing page:\\n\"\n", + " result += Website(url).get_contents()\n", + " links = get_links(url)\n", + "\n", + " for link in links[\"links\"]:\n", + " result += f\"\\n\\n{link['type']}\\n\"\n", + " result += Website(link[\"url\"]).get_contents()\n", + " return result\n", + "\n", + "# set format to json_object\n", + "system_prompt = (\n", + " \"You are an assistant that analyzes the contents of several relevant pages from a company website \"\n", + " \"and creates a short tempered, irritated, disappointed in the world type of brochure about the company for prospective customers, investors, and recruits. \"\n", + " \"Respond in markdown. Include details of company culture, customers, and careers/jobs if you have the information. Add emoticons where ever possible.\\n\\n\"\n", + "\n", + " \"Please structure the brochure using the following sections:\\n\"\n", + " \"1. **Introduction**: A brief overview of the company.\\n\"\n", + " \"2. **Company Culture**: Emphasize fun, atmosphere, and any unique cultural elements.\\n\"\n", + " \"3. **Customers**: Mention notable customers or industries.\\n\"\n", + " \"4. **Careers/Jobs**: Highlight career opportunities.\\n\"\n", + " \"5. **Conclusion**: Wrap up with a final lighthearted message.\\n\"\n", + " \"6. Finish the brochure with a very sarcastic and pun-intended mission statement.\\n\"\n", + ")\n", + "\n", + "def get_brochure_user_prompt(company_name, url):\n", + " user_prompt = f\"You are looking at a company called: {company_name}\\n\"\n", + " 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", + " user_prompt += get_all_details(url)\n", + " user_prompt = user_prompt[:20_000]\n", + " return user_prompt\n", + "\n", + "def stream_brochure():\n", + " global brochure_text # Access the global variable\n", + " brochure_text = \"\" # Initialize\n", + " \n", + " stream = openai.chat.completions.create(\n", + " model=MODEL,\n", + " messages=[\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": get_brochure_user_prompt(company_name, url)}\n", + " ],\n", + " stream=True\n", + " )\n", + " \n", + " response = \"\"\n", + " display_handle = display(Markdown(\"\"), display_id=True)\n", + " for chunk in stream: \n", + " content = chunk.choices[0].delta.content or ''\n", + " response += content\n", + " brochure_text += content # Accumulate the text\n", + " response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n", + " update_display(Markdown(response), display_id=display_handle.display_id)\n", + "\n", + "def user_translate_brochure(lang):\n", + " # Clear previous output\n", + " clear_output(wait=True)\n", + " \n", + " # Stream #2: translate accumulated text\n", + " translation_stream = openai.chat.completions.create( # Changed from ChatCompletion\n", + " model=MODEL,\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": f\"Translate the following to {lang}:\\n\\n{brochure_text}\"}\n", + " ],\n", + " stream=True\n", + " )\n", + " \n", + " # Setup display for streaming translation\n", + " display_handle = display(Markdown(\"\"), display_id=True)\n", + " translated_text = \"\"\n", + " \n", + " for chunk in translation_stream:\n", + " content = chunk.choices[0].delta.content or \"\"\n", + " if content:\n", + " translated_text += content\n", + " update_display(Markdown(translated_text), display_id=display_handle.display_id)\n", + "\n", + "# stream the brochure in english\n", + "stream_brochure()\n", + "\n", + "# prompt user for language choice\n", + "language_choice = input(\"Enter the language to translate the brochure into (e.g., 'French'): \")\n", + "\n", + "# translate the brochure and stream the translation\n", + "user_translate_brochure(language_choice)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llms", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.11" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}