Adding Ollama brochure version and Ollama Tutor version with streaming

week1/community-contributions/week1_Tutor_Ollama.ipynb

@@ -0,0 +1,125 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "135ee16c-2741-4ebf-aca9-1d263083b3ce",
+   "metadata": {},
+   "source": [
+    "# End of week 1 exercise\n",
+    "\n",
+    "Build a tutor tool by using Ollama."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1070317-3ed9-4659-abe3-828943230e03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports\n",
+    "import ollama\n",
+    "from IPython.display import Markdown, display, clear_output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a456906-915a-4bfd-bb9d-57e505c5093f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# constants\n",
+    "MODEL_LLAMA = 'llama3.2'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3f0d0137-52b0-47a8-81a8-11a90a010798",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 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",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get Llama 3.2 to answer, with streaming\n",
+    "\n",
+    "\n",
+    "messages=[{\"role\":\"user\",\"content\":question}]\n",
+    "\n",
+    "for chunk in ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True):\n",
+    "    print(chunk['message']['content'], end='', flush=True)\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1f71014-e780-4d3f-a227-1a7c18158a4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Alternative answer with streaming in Markdown!\n",
+    "\n",
+    "def stream_response():\n",
+    "    messages = [{\"role\": \"user\", \"content\": question}]\n",
+    "    \n",
+    "    display_markdown = display(Markdown(\"\"), display_id=True)\n",
+    "\n",
+    "    response_text = \"\"\n",
+    "    for chunk in ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True):\n",
+    "        \n",
+    "        response_text += chunk['message']['content']\n",
+    "        clear_output(wait=True)  # Clears previous output\n",
+    "        display_markdown.update(Markdown(response_text))  # Updates Markdown dynamically\n",
+    "\n",
+    "# Run the function\n",
+    "stream_response()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c38fdd2a-4b09-402c-ba46-999b22b0cb15",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}