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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0df0d850-49eb-4a0b-a27a-146969db710d",
+   "metadata": {},
+   "source": [
+    "# The Price is Right\n",
+    "\n",
+    "## Week 8 Order of Play\n",
+    "\n",
+    "Day 1: Modal.com and SpecialistAgent  \n",
+    "Day 2: RAG, FrontierAgent, Ensemble Agent  \n",
+    "Day 3: ScannerAgent, MessengerAgent  \n",
+    "Day 4: AutonomousPlannerAgent and DealAgentFramework  \n",
+    "Day 5: The Price Is Right Finale\n",
+    "\n",
+    "\n",
+    "Today we'll build another piece of the puzzle: a ScanningAgent that looks for promising deals by subscribing to RSS feeds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d3763a79-8a5a-4300-8de4-93e85475af10",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from dotenv import load_dotenv\n",
+    "from openai import OpenAI\n",
+    "from agents.deals import ScrapedDeal, DealSelection\n",
+    "import logging\n",
+    "import requests\n",
+    "load_dotenv(override=True)\n",
+    "openai = OpenAI()\n",
+    "MODEL = 'gpt-5-mini'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "afece9db-8cd4-46be-ac57-0b472e84da7d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deals = ScrapedDeal.fetch(show_progress=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8cd15c4d-eb44-4601-bf0c-f945c1d8e3ec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "len(deals)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4259f30a-6455-49ed-8863-2f9ddd4776cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deals[10].describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53984504",
+   "metadata": {},
+   "source": [
+    "### We are going to ask GPT-5-mini to summarize deals and identify their price"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8100e5ac-38f5-40c1-a712-08ae12c85038",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "SYSTEM_PROMPT = \"\"\"You identify and summarize the 5 most detailed deals from a list, by selecting deals that have the most detailed, high quality description and the most clear price.\n",
+    "Respond strictly in JSON with no explanation, using this format. You should provide the price as a number derived from the description. If the price of a deal isn't clear, do not include that deal in your response.\n",
+    "Most important is that you respond with the 5 deals that have the most detailed product description with price. It's not important to mention the terms of the deal; most important is a thorough description of the product.\n",
+    "Be careful with products that are described as \"$XXX off\" or \"reduced by $XXX\" - this isn't the actual price of the product. Only respond with products when you are highly confident about the price. \n",
+    "\"\"\"\n",
+    "\n",
+    "USER_PROMPT_PREFIX = \"\"\"Respond with the most promising 5 deals from this list, selecting those which have the most detailed, high quality product description and a clear price that is greater than 0.\n",
+    "You should rephrase the description to be a summary of the product itself, not the terms of the deal.\n",
+    "Remember to respond with a short paragraph of text in the product_description field for each of the 5 items that you select.\n",
+    "Be careful with products that are described as \"$XXX off\" or \"reduced by $XXX\" - this isn't the actual price of the product. Only respond with products when you are highly confident about the price. \n",
+    "\n",
+    "Deals:\n",
+    "\n",
+    "\"\"\"\n",
+    "\n",
+    "USER_PROMPT_SUFFIX = \"\\n\\nInclude exactly 5 deals, no more.\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f4bca170-af71-40c9-9597-1d72980c74d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# this makes a suitable user prompt given scraped deals\n",
+    "\n",
+    "def make_user_prompt(scraped):\n",
+    "    user_prompt = USER_PROMPT_PREFIX\n",
+    "    user_prompt += '\\n\\n'.join([scrape.describe() for scrape in scraped])\n",
+    "    user_prompt += USER_PROMPT_SUFFIX\n",
+    "    return user_prompt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "020947a6-561b-417b-98a0-a085e31d2ce3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Let's create a user prompt for the deals we just scraped, and look at how it begins\n",
+    "\n",
+    "user_prompt = make_user_prompt(deals)\n",
+    "print(user_prompt[:2000])\n",
+    "messages = [{\"role\": \"system\", \"content\": SYSTEM_PROMPT}, {\"role\": \"user\", \"content\": user_prompt}]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7de46f74-868c-4127-8a68-cf2da7d600bb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "response = openai.chat.completions.parse(model=MODEL, messages=messages, response_format=DealSelection, reasoning_effort=\"minimal\")\n",
+    "results = response.choices[0].message.parsed\n",
+    "results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "065cfe7a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for deal in results.deals:\n",
+    "    print(deal.product_description)\n",
+    "    print(deal.price)\n",
+    "    print(deal.url)\n",
+    "    print()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9e04f2b2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "root = logging.getLogger()\n",
+    "root.setLevel(logging.INFO)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8bdc57fb-7497-47af-a643-6ba5a21cc17e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from agents.scanner_agent import ScannerAgent"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "132278bc-217a-43a6-b6c4-724140c6a225",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "agent = ScannerAgent()\n",
+    "result = agent.scan()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2e1d013a-c930-4dad-901b-41433379e14b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ee2e837-1f1d-42d4-8bc4-51cccc343006",
+   "metadata": {},
+   "source": [
+    "### Introducing Pushover\n",
+    "\n",
+    "Pushover is a nifty tool for sending Push Notifications to your phone.\n",
+    "\n",
+    "It's super easy to set up and install!\n",
+    "\n",
+    "Simply visit https://pushover.net/ and click 'Login or Signup' on the top right to sign up for a free account, and create your API keys.\n",
+    "\n",
+    "Once you've signed up, on the home screen, click \"Create an Application/API Token\", and give it any name (like AIEngineer) and click Create Application.\n",
+    "\n",
+    "Then add 2 lines to your `.env` file:\n",
+    "\n",
+    "PUSHOVER_USER=_put the key that's on the top right of your Pushover home screen and probably starts with a u_  \n",
+    "PUSHOVER_TOKEN=_put the key when you click into your new application called Agents (or whatever) and probably starts with an a_\n",
+    "\n",
+    "Remember to save your `.env` file, and run `load_dotenv(override=True)` after saving, to set your environment variables.\n",
+    "\n",
+    "Finally, click \"Add Phone, Tablet or Desktop\" to install on your phone."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "761bc7d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "load_dotenv(override=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d7fafd66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pushover_user = os.getenv('PUSHOVER_USER')\n",
+    "pushover_token = os.getenv('PUSHOVER_TOKEN')\n",
+    "pushover_url = \"https://api.pushover.net/1/messages.json\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d531ed4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if pushover_user:\n",
+    "    print(f\"Pushover user found and starts with {pushover_user[0]}\")\n",
+    "else:\n",
+    "    print(\"Pushover user not found\")\n",
+    "\n",
+    "if pushover_token:\n",
+    "    print(f\"Pushover token found and starts with {pushover_token[0]}\")\n",
+    "else:\n",
+    "    print(\"Pushover token not found\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "003c858f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def push(message):\n",
+    "    print(f\"Push: {message}\")\n",
+    "    payload = {\"user\": pushover_user, \"token\": pushover_token, \"message\": message}\n",
+    "    requests.post(pushover_url, data=payload)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43fd1fa4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "push(\"MASSIVE DEAL!!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "be0c3276",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from agents.messaging_agent import MessagingAgent\n",
+    "\n",
+    "agent = MessagingAgent()\n",
+    "agent.push(\"SUCH A MASSIVE DEAL!!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1200929",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "agent.notify(\"A special deal on Sumsung 60 inch LED TV going at a great bargain\", 300, 1000, \"www.samsung.com\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "46d59b1e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.12.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}