added 2 day ollama option
This commit is contained in:
Kartik Sharma
@@ -0,0 +1,344 @@
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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": 13,
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"id": "0abc4dde-8396-4867-bf48-a534c7ae89c0",
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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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"# imports\n",
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"\n",
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"import os\n",
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"from dotenv import load_dotenv\n",
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"from openai import OpenAI\n",
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"from IPython.display import Markdown, display"
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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": 14,
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"id": "92e9e303-9c2b-4e4b-a210-829a31d975e5",
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"API key found and looks good so far!\n"
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]
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}
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],
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"source": [
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"# Load environment variables in a file called .env\n",
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"\n",
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"load_dotenv()\n",
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"api_key = os.getenv('OPENAI_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 not api_key.startswith(\"sk-proj-\"):\n",
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" print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\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!\")"
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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": 15,
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"id": "7c8da66c-96b6-45fc-8f5d-e8314fcc9352",
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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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"openai = OpenAI()"
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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": 50,
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"id": "3cb23b83-a4d2-474d-9ea3-24a5530d9768",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠋ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠙ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠹ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠸ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠼ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠴ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠦ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠧ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠇ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠏ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest ⠋ \u001b[K\u001b[?25h\u001b[?2026l\u001b[?2026h\u001b[?25l\u001b[1Gpulling manifest \u001b[K\n",
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"pulling dde5aa3fc5ff: 100% ▕██████████████████▏ 2.0 GB \u001b[K\n",
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"pulling 966de95ca8a6: 100% ▕██████████████████▏ 1.4 KB \u001b[K\n",
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"pulling fcc5a6bec9da: 100% ▕██████████████████▏ 7.7 KB \u001b[K\n",
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"pulling a70ff7e570d9: 100% ▕██████████████████▏ 6.0 KB \u001b[K\n",
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"pulling 56bb8bd477a5: 100% ▕██████████████████▏ 96 B \u001b[K\n",
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"pulling 34bb5ab01051: 100% ▕██████████████████▏ 561 B \u001b[K\n",
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"verifying sha256 digest \u001b[K\n",
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"writing manifest \u001b[K\n",
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"success \u001b[K\u001b[?25h\u001b[?2026l\n"
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]
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}
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],
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"source": [
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"# Let's just make sure the model is loaded\n",
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"!ollama pull llama3.2\n",
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"import ollama\n"
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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": 52,
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"id": "30681517-8acd-49f0-b3c8-ab66854e0e4e",
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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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"# System prompt - defines the AI's behavior\n",
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"SYSTEM_PROMPT = \"\"\"You are a helpful cooking assistant that provides ingredient lists for recipes.\n",
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"Format your response as clean markdown with this structure:\n",
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"\n",
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"# [Dish Name]\n",
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"**Serves:** [number] people \n",
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"**Cook Time:** [estimated time]\n",
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"\n",
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"## Shopping List\n",
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"- [ ] [amount] [unit] [ingredient]\n",
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"- [ ] [amount] [unit] [ingredient]\n",
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"\n",
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"Guidelines:\n",
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"- Use common grocery store measurements (cups, lbs, oz, pieces, cans, etc.)\n",
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"- Round to practical shopping amounts (1.5 lbs instead of 1.47 lbs)\n",
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"- Group similar items when logical (all spices together)\n",
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"- Include pantry staples only if they're essential (salt, oil, etc.)\n",
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"- Assume basic seasonings are available unless recipe-specific\n",
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"- For produce, specify size when important (large onion, medium tomatoes)\n",
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"- Keep optional items at the end of similar item groups or end of the list\"\"\""
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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": 59,
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"id": "0d3abbd9-d0eb-434a-b382-f28d8c7ca9ea",
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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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"def get_recipe_openai(dish_name: str, num_people: int):\n",
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" \"\"\"Get scaled recipe ingredients using system and user prompts\"\"\"\n",
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"\n",
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" user_prompt = f\"Give me the ingredients needed to make {dish_name} for {num_people} people.\"\n",
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" \n",
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" try:\n",
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" response = openai.chat.completions.create(\n",
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" model=\"gpt-4o-mini\",\n",
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" messages=[\n",
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" {\"role\": \"system\", \"content\": SYSTEM_PROMPT},\n",
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" {\"role\": \"user\", \"content\": user_prompt}\n",
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" ],\n",
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" max_tokens=400\n",
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" )\n",
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" \n",
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" return response.choices[0].message.content\n",
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" \n",
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" except Exception as e:\n",
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" return f\"❌ Error: Failed to get recipe - {str(e)}\""
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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": 60,
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"id": "b7a6f70b-91ab-414f-b6d7-265c0d4dcd74",
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"metadata": {},
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"outputs": [],
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"source": [
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"OLLAMA_MODEL = \"llama3.2\""
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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": 61,
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"id": "badf702d-f1c1-4294-9aa2-63e5737ae8df",
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"metadata": {},
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"outputs": [],
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"source": [
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"def get_recipe_ollama(dish_name: str, num_people: int):\n",
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" \"\"\"Get recipe using Ollama API\"\"\"\n",
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" user_prompt = f\"Give me the ingredients needed to make {dish_name} for {num_people} people.\"\n",
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" \n",
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" messages = [\n",
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" {\"role\": \"system\", \"content\": SYSTEM_PROMPT},\n",
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" {\"role\": \"user\", \"content\": user_prompt}\n",
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" ]\n",
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" \n",
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" try:\n",
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" response = ollama.chat(model=OLLAMA_MODEL, messages=messages)\n",
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" return response['message']['content']\n",
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" except Exception as e:\n",
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" return f\"❌ Ollama Error: {str(e)}\""
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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": 62,
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"id": "c2281db6-a4c7-4749-9aa9-d9eaf461dd7e",
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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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"def print_shopping_list(recipe_markdown):\n",
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" \"\"\"Print the markdown response\"\"\"\n",
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" display(Markdown(recipe_markdown))"
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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": 63,
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"id": "dd1c13fb-0836-423d-aa9a-2ff433e5f916",
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"🍳 Recipe Scaler & Grocery List Maker\n",
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"========================================\n"
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]
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},
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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"\n",
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"Choose AI service (1 for OpenAI, 2 for Ollama): 1\n",
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"What dish do you want to make? macaroni pasta\n",
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"How many people? 5\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"🔍 Getting recipe for macaroni pasta...\n",
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"Using OpenAI API...\n"
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]
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},
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{
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"data": {
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"text/markdown": [
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"# Macaroni Pasta\n",
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"**Serves:** 5 people \n",
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"**Cook Time:** 15 minutes\n",
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"\n",
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"## Shopping List\n",
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"- [ ] 1 lb macaroni pasta\n",
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"- [ ] 4 cups water (for boiling)\n",
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"- [ ] 2 tablespoons salt (for boiling water)\n",
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"\n",
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"### Optional Ingredients (for serving)\n",
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"- [ ] 1 cup shredded cheese\n",
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"- [ ] 1/2 cup milk\n",
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"- [ ] 1/4 cup butter\n",
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"- [ ] Black pepper to taste"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"print(\"🍳 Recipe Scaler & Grocery List Maker\")\n",
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"print(\"=\" * 40)\n",
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" \n",
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"ai_service_choice = input(\"\\nChoose AI service (1 for OpenAI, 2 for Ollama): \").strip()\n",
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"\n",
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"dish = input(\"What dish do you want to make? \")\n",
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"num_people = int(input(\"How many people? \"))\n",
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" \n",
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"print(f\"\\n🔍 Getting recipe for {dish}...\")\n",
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" \n",
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"# Get and display recipe\n",
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"if ai_service_choice == '1':\n",
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" print(\"Using OpenAI API...\")\n",
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" recipe_markdown = get_recipe_openai(dish, num_people)\n",
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"else:\n",
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" print(\"Using Ollama (local)...\")\n",
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" recipe_markdown = get_recipe_ollama(dish, num_people)\n",
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"\n",
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"print_shopping_list(recipe_markdown)"
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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": "90338d50-679f-4388-933c-c77b1d0da5a1",
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.11.13"
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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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