Merge pull request #772 from kbaah/kwabena_bootcamp

kwabena_bootcamp

week1/community-contributions/kwabena/week1_exercise_solution.ipynb

@@ -0,0 +1,164 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4ea14045",
+   "metadata": {},
+   "source": [
+    "# End of Week 1 Exercise\n",
+    "\n",
+    "In this exercise, I'm building a small tool that takes a technical question and gets an explanation from **two models** — one from OpenAI and one from Ollama.  \n",
+    "The idea is to compare how they respond and understand how to use both APIs.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "18d3787e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports\n",
+    "\n",
+    "import os\n",
+    "from openai import OpenAI\n",
+    "from dotenv import load_dotenv\n",
+    "from IPython.display import Markdown, display\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1592e306",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# constants\n",
+    "\n",
+    "MODEL_GPT = \"gpt-4o-mini\"\n",
+    "MODEL_LLAMA = \"llama3.2\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "35da77ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# set up environment\n",
+    "\n",
+    "load_dotenv(override=True)\n",
+    "api_key = os.getenv(\"OPENAI_API_KEY\")\n",
+    "\n",
+    "if not api_key:\n",
+    "    print(\"⚠️  OPENAI_API_KEY not found in environment. Please add it to your .env file.\")\n",
+    "else:\n",
+    "    print(\"✅ API key loaded successfully\")\n",
+    "\n",
+    "client = OpenAI(api_key=api_key)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "67efa212",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# define the technical question\n",
+    "# (you can replace this text to ask something else)\n",
+    "\n",
+    "question = \"\"\"Please explain what this code does and why:\n",
+    "yield from {book.get(\"author\") for book in books if book.get(\"author\")}\n",
+    "\"\"\"\n",
+    "\n",
+    "print(\"Question:\", question)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85e1ac5b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get gpt-4o-mini to answer\n",
+    "\n",
+    "print(\"🔹 GPT-4o-mini's answer:\\n\")\n",
+    "\n",
+    "response = client.chat.completions.create(\n",
+    "    model=MODEL_GPT,\n",
+    "    messages=[\n",
+    "        {\"role\": \"system\", \"content\": \"You are a helpful Python tutor.\"},\n",
+    "        {\"role\": \"user\", \"content\": question},\n",
+    "    ],\n",
+    ")\n",
+    "\n",
+    "print(response.choices[0].message.content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4c031d74",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get LLaMA 3.2 to answer via local Ollama endpoint\n",
+    "\n",
+    "print(\"\\n🔹 LLaMA 3.2's answer:\\n\")\n",
+    "\n",
+    "ollama_client = OpenAI(base_url=\"http://localhost:11434/v1\",api_key=\"ollama\")\n",
+    "\n",
+    "response = ollama_client.chat.completions.create(\n",
+    "    model=MODEL_LLAMA,\n",
+    "    messages=[\n",
+    "        {\"role\":\"system\",\"content\":\"You are a helpful AI tutor.\"},\n",
+    "        {\"role\":\"user\",\"content\":question}\n",
+    "    ],\n",
+    ")\n",
+    "\n",
+    "print(response.choices[0].message.content)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e4ddf582",
+   "metadata": {},
+   "source": [
+    "### Reflection\n",
+    "\n",
+    "Both models provide explanations, but often with slightly different tones.  \n",
+    "`gpt-4o-mini` tends to give more structured explanations, while `llama3.2` (running locally through Ollama) may be more concise or technical depending on its settings.\n",
+    "\n",
+    "This exercise helped me understand:\n",
+    "- How to send prompts and handle responses (including streaming).\n",
+    "- How easy it is to swap between OpenAI and local models.\n",
+    "- The value of comparing model outputs side by side.\n"
+   ]
+  }
+ ],
+ "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
+}