diff --git a/week1/community-contributions/week1 exercise - my AI tutor.ipynb b/week1/community-contributions/week1 exercise - my AI tutor.ipynb new file mode 100644 index 0000000..e761e08 --- /dev/null +++ b/week1/community-contributions/week1 exercise - my AI tutor.ipynb @@ -0,0 +1,148 @@ +{ + "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 +}