Added my contributions to community-contributions

week1/community-contributions/week1 exercise - my AI tutor.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f38e9ebb-453d-4b40-84f6-bc3e9bf4d7ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports\n",
+    "\n",
+    "import os\n",
+    "import requests\n",
+    "import json\n",
+    "import ollama\n",
+    "from typing import List\n",
+    "from dotenv import load_dotenv\n",
+    "from bs4 import BeautifulSoup\n",
+    "from IPython.display import Markdown, display, update_display\n",
+    "from openai import OpenAI\n",
+    "\n",
+    "# constants\n",
+    "\n",
+    "MODEL_GPT = 'gpt-4o-mini'\n",
+    "MODEL_LLAMA = 'llama3.2'\n",
+    "OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
+    "HEADERS = {\"Content-Type\": \"application/json\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f367c5bb-80a2-4d78-8f27-823f5dafe7c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# set up environment\n",
+    "\n",
+    "load_dotenv(override=True)\n",
+    "api_key = os.getenv('OPENAI_API_KEY')\n",
+    "openai = OpenAI()\n",
+    "\n",
+    "# System prompt for the AI TECHNICAL LLM AND PYTHON TUTOR.\"\n",
+    "\n",
+    "system_prompt = \"You are an EXPERT in AI, LLMS and Python \\\n",
+    "Provide the answer with example ALLWAYS when necessary. \\\n",
+    "If you do not know the answer just say 'I don't know the answer' \\\n",
+    "Respond in markdown in Spanish.\"\n",
+    "\n",
+    "# messages\n",
+    "def messages_for(question):\n",
+    "    return [\n",
+    "        {\"role\": \"system\", \"content\": system_prompt},\n",
+    "        {\"role\": \"user\", \"content\": question}\n",
+    "    ]\n",
+    "\n",
+    "# here is the question; type over this to ask something new\n",
+    "\n",
+    "question = \"\"\"\n",
+    "Please explain what this code does and why:\n",
+    "yield from {book.get(\"author\") for book in books if book.get(\"author\")}\n",
+    "\"\"\"\n",
+    "question = question[:5_000] # Truncate if more than 5,000 characters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a90d726d-d494-401f-9cd6-0260f5c781e0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# METHODS TO DISPLAY\n",
+    "def display_summary_ollama(question):\n",
+    "    response = ollama.chat(\n",
+    "        model = MODEL_LLAMA,\n",
+    "        messages = messages_for(question)\n",
+    "    )    \n",
+    "    summary = response['message']['content']\n",
+    "    display(Markdown(summary))\n",
+    "\n",
+    "def display_summary_gpt(question):\n",
+    "    stream = openai.chat.completions.create(\n",
+    "        model = MODEL_GPT,\n",
+    "        messages = messages_for(question),\n",
+    "        stream=True\n",
+    "    )\n",
+    "    response = \"\"\n",
+    "    display_handle = display(Markdown(\"\"), display_id=True)\n",
+    "    for chunk in stream:\n",
+    "        response += chunk.choices[0].delta.content or ''\n",
+    "        response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n",
+    "        update_display(Markdown(response), display_id=display_handle.display_id)\n",
+    "    \n",
+    "def display_summary(llm, question):\n",
+    "    if llm.startswith(\"llama3.2\"):\n",
+    "        display_summary_ollama(question)\n",
+    "    else:\n",
+    "        display_summary_gpt(question)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4e993b6d-8fee-43f3-9e36-f86701a5cc57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get gpt-4o-mini to answer, with streaming\n",
+    "\n",
+    "display_summary(MODEL_GPT, question)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "31f6283a-ee57-415e-9a57-83d07261b7f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get Llama 3.2 to answer\n",
+    "\n",
+    "display_summary(MODEL_LLAMA, question)"
+   ]
+  }
+ ],
+ "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
+}