add solutions for week1
This commit is contained in:
Natalia Kaczyńska
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4e5da3f5-ebd0-4e20-ab89-95847187287b",
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"metadata": {},
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"outputs": [],
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"source": [
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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 bs4 import BeautifulSoup\n",
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"from IPython.display import Markdown, display, update_display, clear_output\n",
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"from openai import OpenAI\n",
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"from dotenv import load_dotenv\n",
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"import os\n",
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"from scraper import fetch_website_links, fetch_website_contents"
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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": "86adec56-3b27-46da-9b1a-1e5946a76a09",
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"metadata": {},
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"outputs": [],
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"source": [
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"load_dotenv(override=True)\n",
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"api_key = os.getenv('OPENROUTER_API_KEY')\n",
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"\n",
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"# Check the key\n",
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"\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif api_key.strip() != api_key:\n",
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" print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
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"else:\n",
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" print(\"API key found and looks good so far!\")\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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"openrouter_url = \"https://openrouter.ai/api/v1\"\n",
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"openai = OpenAI(api_key=api_key, base_url=openrouter_url)\n",
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"MODEL = \"gpt-5-nano\""
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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": "abf2f706-2709-404a-9fb7-774a9f57dd11",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"company_name = input(\"Enter the company name: \")\n",
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"url = input(\"Enter the company url: \")"
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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": "153fa3d1-3ce5-46d0-838d-3e95a4b8628b",
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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. 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",
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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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" EXAMPLE 1:\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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" EXAMPLE 2:\n",
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" {\n",
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" \"links\": [\n",
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" {\"type\": \"company blog\", \"url\": \"https://blog.example.com\"},\n",
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" {\"type\": \"our story\", \"url\": \"https://example.com/our-story\"}\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": "6fcacc2e-7445-4d8a-aa80-489d3a2247ec",
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"metadata": {},
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"outputs": [],
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"source": [
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"def get_links_user_prompt(url):\n",
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" user_prompt = f\"Here is the list of links on the website of {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. 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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" links = fetch_website_links(url)\n",
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" user_prompt += \"\\n\".join(links[:20])\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": "dfe222c5-0d3e-4be2-85e1-596ab9d407dc",
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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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" 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(url)}\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": "c964bdce-be5d-41c7-a8d7-8e25e58463c5",
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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 += fetch_website_contents(url)\n",
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" links = get_links(url)\n",
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"\n",
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" for link in links[\"links\"]:\n",
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" result += f\"{link['type']}\\n\"\n",
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" try:\n",
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" result += f\"\\n\\n### Link: Link: {link['type']}\\n\"\n",
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" result += fetch_website_contents(link[\"url\"])\n",
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" except Exception as e:\n",
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" print(f\"Omitted link: {link['url']}: {e}\")\n",
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" continue\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": "5337019a-b789-49d7-bf10-0f15148c0276",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_prompt = (\n",
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" \"You are an assistant that analyzes the contents of several relevant pages from a company website \"\n",
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" \"and creates a great type of brochure about the company for prospective customers, investors, and recruits. \"\n",
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" \"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",
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"\n",
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" \"Please structure the brochure using the following sections:\\n\"\n",
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" \"1. **Introduction**: A brief overview of the company.\\n\"\n",
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" \"2. **Company Culture**: Emphasize fun, atmosphere, and any unique cultural elements.\\n\"\n",
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" \"3. **Customers**: Mention notable customers or industries.\\n\"\n",
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" \"4. **Careers/Jobs**: Highlight career opportunities.\\n\"\n",
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" \"5. **Conclusion**: Wrap up with a final lighthearted message.\\n\"\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": "1dd4f2d4-8189-452a-b15a-c09ae5894ac8",
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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[:20000]\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": "8ab4bfef-eb22-43fb-8a46-f1f6a225793b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def stream_brochure():\n",
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" global brochure_text\n",
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" brochure_text = \"\"\n",
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"\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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" content = chunk.choices[0].delta.content or ''\n",
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" response += content\n",
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" brochure_text += content\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": "7828c747-7872-48e2-b3e6-faab95ba76cb",
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"metadata": {},
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"outputs": [],
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"source": [
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"def user_translate_brochure(language):\n",
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" clear_output(wait = True)\n",
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"\n",
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" translation_stream = openai.chat.completions.create(\n",
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" model = MODEL,\n",
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" messages = [\n",
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" {\"role\": \"user\", \"content\": f\"Translate the following to {language}:\\n {brochure_text}\"}\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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" display_handle = display(Markdown(\"\"), display_id = True)\n",
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" translated_text = \"\"\n",
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"\n",
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" for chunk in translation_stream:\n",
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" content = chunk.choices[0].delta.content or \"\"\n",
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" if content:\n",
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" translated_text += content\n",
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" update_display(Markdown(translated_text), 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": "e6cfa92a-8a86-485d-a7e1-1651705ee6dc",
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"metadata": {},
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"outputs": [],
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"source": [
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"stream_brochure()\n",
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"language_choice = input(\"Enter the language to translate the brochure into (e.g., 'French'): \")\n",
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"user_translate_brochure(language_choice)"
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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": "3.13.7"
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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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