{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "a767b6bc-65fe-42b2-988f-efd54125114f", "metadata": {}, "outputs": [], "source": [ "import os\n", "import requests\n", "from dotenv import load_dotenv\n", "from bs4 import BeautifulSoup\n", "from IPython.display import Markdown, display, clear_output\n", "from openai import OpenAI\n", "import time\n", "\n", "load_dotenv(override=True)\n", "api_key = os.getenv('DEEPSEEK_API_KEY')\n", "base_url=os.getenv('DEEPSEEK_BASE_URL')\n", "start_time = time.time()\n", "\n", "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n", "and provides a short summary, ignoring text that might be navigation related. \\\n", "Respond in markdown.\"\n", "\n", "messages = [\n", " {\"role\": \"system\", \"content\": \"You are a snarky assistant\"},\n", " {\"role\": \"user\", \"content\": \"What is 2 + 2?\"}\n", "]\n", " \n", "# Check the key\n", "if not api_key:\n", " print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n", "elif not api_key.startswith(\"sk-proj-\"):\n", " print(\"An API key was found, but it doesn't start sk-proj-; Looks like you are using DeepSeek (R1) model.\")\n", "elif api_key.strip() != api_key:\n", " 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", "else:\n", " print(\"API key found and looks good so far!\")\n", " \n", "openai = OpenAI(api_key=api_key, base_url=base_url)\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", "class Website:\n", "\n", " def __init__(self, url):\n", " \"\"\"\n", " Create this Website object from the given url using the BeautifulSoup library\n", " \"\"\"\n", " self.url = url\n", " response = requests.get(url, headers=headers)\n", " soup = BeautifulSoup(response.content, 'html.parser')\n", " self.title = soup.title.string if soup.title else \"No title found\"\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", " \n", "def user_prompt_for(website):\n", " user_prompt = f\"You are looking at a website titled {website.title}\"\n", " user_prompt += \"\\nThe contents of this website is as follows; please provide a short summary of this website in markdown. If it includes news or announcements, then summarize these too.\\n\\n\"\n", " user_prompt += website.text\n", " return user_prompt\n", "\n", "def messages_for(website):\n", " return [\n", " {\"role\": \"system\", \"content\": system_prompt},\n", " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", " ]\n", " \n", "def summarize(url):\n", " website = Website(url)\n", " response = openai.chat.completions.create(\n", " model=\"deepseek-chat\",\n", " messages=messages_for(website),\n", " stream=True\n", " )\n", " print(\"Streaming response:\")\n", " accumulated_content = \"\" # Accumulate the content here\n", " for chunk in response:\n", " if chunk.choices[0].delta.content: # Check if there's content in the chunk\n", " accumulated_content += chunk.choices[0].delta.content # Append the chunk to the accumulated content\n", " clear_output(wait=True) # Clear the previous output\n", " display(Markdown(accumulated_content)) # Display the updated content\n", " \n", " # # Final display (optional, as the loop already displays the content)\n", " # display(Markdown(accumulated_content))\n", "\n", "def display_summary():\n", " url = str(input(\"Enter the URL of the website you want to summarize: \"))\n", " summarize(url)\n", "\n", "display_summary()" ] }, { "cell_type": "code", "execution_count": null, "id": "01c9e5e7-7510-43ef-bb9c-aa44b15d39a7", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": 5 }