{ "cells": [ { "cell_type": "markdown", "id": "e71d7ff9-c27a-4602-9230-856626b1de07", "metadata": {}, "source": [ "# Company Brochure Generator UI\n", "Generates a brochure for a company website, after scraping the website and pages linked with that page, based on the provided company URL. \n", "Enables users to \n", "- Choose a model type (Llama 3.2, Claude, GPT)-\n", "- Choose the tone preference\n", "- Choose the target audience" ] }, { "cell_type": "markdown", "id": "de9b59b9-8673-42e7-8849-62fe30f56711", "metadata": {}, "source": [ "#### Imports, Keys, Instantiation" ] }, { "cell_type": "code", "execution_count": 38, "id": "39fd7fed-b215-4037-bd6e-7e1af1b83897", "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\n", "from openai import OpenAI\n", "import anthropic\n", "import gradio as gr" ] }, { "cell_type": "code", "execution_count": 15, "id": "0bf24357-1d77-4721-9d5a-f99827b2158c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OpenAI API Key exists and begins sk-proj-\n", "Anthropic API Key exists and begins sk-ant-\n" ] } ], "source": [ "# Load environment variables in a file called .env\n", "\n", "load_dotenv(override=True)\n", "openai_api_key = os.getenv('OPENAI_API_KEY')\n", "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", "\n", "if openai_api_key:\n", " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", "else:\n", " print(\"OpenAI API Key not set\")\n", " \n", "if anthropic_api_key:\n", " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", "else:\n", " print(\"Anthropic API Key not set\")" ] }, { "cell_type": "code", "execution_count": 20, "id": "1afc12e1-02c1-4394-b589-19cd08d2a8bb", "metadata": {}, "outputs": [], "source": [ "# Define models\n", "CLAUDE_MODEL = \"claude-3-haiku-20240307\"\n", "GPT_MODEL = \"gpt-4o-mini\"" ] }, { "cell_type": "code", "execution_count": 17, "id": "d5d79a69-0a39-4ab4-aaf8-bc591bce0536", "metadata": {}, "outputs": [], "source": [ "# Creating instances\n", "claude = anthropic.Anthropic()\n", "openai = OpenAI()" ] }, { "cell_type": "markdown", "id": "1d3369bc-b751-4f4d-a288-d7d81c384e67", "metadata": {}, "source": [ "#### Web Scraper" ] }, { "cell_type": "code", "execution_count": 8, "id": "fafe1074-fbf4-47cc-80dc-34413a447977", "metadata": {}, "outputs": [], "source": [ "# A class to represent a Webpage\n", "\n", "# Some websites need you to use proper headers when fetching them:\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", "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\"" ] }, { "cell_type": "code", "execution_count": 9, "id": "41c1f1af-ae20-423b-bf7c-efd7f8c2751b", "metadata": {}, "outputs": [], "source": [ "link_system_prompt = \"You are provided with a list of links found on a webpage. \\\n", "You are able to decide which of the links would be most relevant to include in a brochure about the company, \\\n", "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", "{\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", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 10, "id": "eb537563-e393-47ca-9af2-a8ea7393edd9", "metadata": {}, "outputs": [], "source": [ "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. \\\n", "Do not include Terms of Service, Privacy, email or social media links.\\n\"\n", " user_prompt += \"Links (some might be relative links):\\n\"\n", " user_prompt += \"\\n\".join(website.links)\n", " return user_prompt" ] }, { "cell_type": "code", "execution_count": 36, "id": "033568d2-3f1a-43ac-a288-7a65b4ea86a5", "metadata": {}, "outputs": [], "source": [ "def get_links(url):\n", " website = Website(url)\n", " response = openai.chat.completions.create(\n", " model=GPT_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)" ] }, { "cell_type": "code", "execution_count": 12, "id": "d8f316ac-f0b1-42d9-88a8-0a61fcb0023d", "metadata": {}, "outputs": [], "source": [ "def get_all_details(url):\n", " result = \"Landing page:\\n\"\n", " result += Website(url).get_contents()\n", " links = get_links(url)\n", " print(\"Found links:\", links)\n", " for link in links[\"links\"]:\n", " print(f\"Processing {link['url']}...\")\n", " result += f\"\\n\\n{link['type']}\\n\"\n", " result += Website(link[\"url\"]).get_contents()\n", " return result" ] }, { "cell_type": "markdown", "id": "016e065a-ac5a-48c0-bc4b-e916e9801384", "metadata": {}, "source": [ "#### System Message" ] }, { "cell_type": "code", "execution_count": 18, "id": "ed1c6068-5f4f-47a7-ab97-738dfb94e057", "metadata": {}, "outputs": [], "source": [ "system_message = \"You are an assistant that analyzes the contents of a company website landing page \\\n", "and creates a short brochure about the company for prospective customers, investors and recruits. \\\n", "You are also provided with the tone, and the target audience. Provide an appropriate answer. Respond in markdown.\"" ] }, { "cell_type": "markdown", "id": "6d4f594c-927d-440f-8aae-33cfeb9c445c", "metadata": {}, "source": [ "#### LLM Call Functions" ] }, { "cell_type": "code", "execution_count": 40, "id": "5b6a0379-3465-4c04-a553-4e4cdb9064b9", "metadata": {}, "outputs": [], "source": [ "def stream_gpt(prompt,company_name,url):\n", " messages = [\n", " {\"role\": \"user\", \"content\": prompt},\n", " {\"role\":\"system\",\"content\":system_message}\n", " ]\n", " stream = openai.chat.completions.create(\n", " model=GPT_MODEL,\n", " messages=messages,\n", " stream=True\n", " )\n", " result = \"\"\n", " for chunk in stream:\n", " result += chunk.choices[0].delta.content or \"\"\n", " yield result" ] }, { "cell_type": "code", "execution_count": 21, "id": "a2194e1d-4e99-4127-9515-aa9353382bc6", "metadata": {}, "outputs": [], "source": [ "def stream_claude(prompt):\n", " result = claude.messages.stream(\n", " model=CLAUDE_MODEL,\n", " max_tokens=1000,\n", " temperature=0.7,\n", " system=system_message,\n", " messages=[\n", " {\"role\": \"user\", \"content\": prompt},\n", " ],\n", " )\n", " response = \"\"\n", " with result as stream:\n", " for text in stream.text_stream:\n", " response += text or \"\"\n", " yield response" ] }, { "cell_type": "markdown", "id": "64adf26c-33b2-4589-8df6-dc5d6da71420", "metadata": {}, "source": [ "#### Brochure Creation" ] }, { "cell_type": "code", "execution_count": 13, "id": "8192f39f-508b-4592-a075-767db68672b3", "metadata": {}, "outputs": [], "source": [ "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[:5_000] # Truncate if more than 5,000 characters\n", " return user_prompt" ] }, { "cell_type": "code", "execution_count": 32, "id": "8aebfabe-4d51-4ee7-a9d2-5a379e9427cb", "metadata": {}, "outputs": [], "source": [ "def create_brochure(company_name, url,model,tone,target):\n", " print('create brochure function called')\n", " prompt = f\"Please generate a company brochure for {company_name}.\"\n", " prompt += f\"Use a {tone} tone; and target content at {target}\"\n", " prompt += get_brochure_user_prompt(company_name,url)\n", " \n", " if model == \"GPT\":\n", " result = stream_gpt(prompt,company_name,url)\n", " elif model==\"Claude\":\n", " result = stream_claude(prompt,company_name,url)\n", " else:\n", " raise ValueError(\"Unknown model\")\n", " yield from result" ] }, { "cell_type": "markdown", "id": "c5f4f97b-c9d0-4d4c-8b02-e6209ba2549c", "metadata": {}, "source": [ "#### Putting it all together : Gradio UI" ] }, { "cell_type": "code", "execution_count": 22, "id": "33162303-9b49-46fe-a8e0-0d01be45685b", "metadata": {}, "outputs": [], "source": [ "force_dark_mode = \"\"\"\n", "function refresh() {\n", " const url = new URL(window.location);\n", " if (url.searchParams.get('__theme') !== 'dark') {\n", " url.searchParams.set('__theme', 'dark');\n", " window.location.href = url.href;\n", " }\n", "}\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 41, "id": "47ab9a41-cecd-4c21-bd68-4a15966b80c4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "* Running on local URL: http://127.0.0.1:7877\n", "\n", "To create a public link, set `share=True` in `launch()`.\n" ] }, { "data": { "text/html": [ "
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