Add my week1 EXERCISE.ipynb to community-contributions

community-contributions/pradeep1955/week1 EXERCISE.ipynb

@@ -0,0 +1,148 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fe12c203-e6a6-452c-a655-afb8a03a4ff5",
+   "metadata": {},
+   "source": [
+    "# End of week 1 exercise\n",
+    "\n",
+    "To demonstrate your familiarity with OpenAI API, and also Ollama, build a tool that takes a technical question,  \n",
+    "and responds with an explanation. This is a tool that you will be able to use yourself during the course!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1070317-3ed9-4659-abe3-828943230e03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports\n",
+    "import os\n",
+    "from openai import OpenAI\n",
+    "from IPython.display import Markdown, display, update_display\n",
+    "from dotenv import load_dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a456906-915a-4bfd-bb9d-57e505c5093f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# constants\n",
+    "\n",
+    "MODEL_GPT = 'gpt-4o-mini'\n",
+    "MODEL_LLAMA = 'llama3.2'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a8d7923c-5f28-4c30-8556-342d7c8497c1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# set up environment\n",
+    "load_dotenv(override=True)\n",
+    "api_key=os.getenv(\"OPENAI_API_KEY\")\n",
+    "if not api_key.startswith(\"sk-proj-\") and len(api_key)<10:\n",
+    "    print(\"api key not foud\")\n",
+    "else:\n",
+    "    print(\"api found and is ok\")\n",
+    "\n",
+    "openai=OpenAI()\n",
+    "print()"
+   ]
+  },
+  {
+   "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",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60ce7000-a4a5-4cce-a261-e75ef45063b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get gpt-4o-mini to answer, with streaming\n",
+    "messages = [{\"role\":\"system\",\"content\":\"You are a expert Dta Scientist\"}, {\"role\":\"user\",\"content\":question}]\n",
+    "\n",
+    "stream = openai.chat.completions.create(\n",
+    "                model = MODEL_GPT,\n",
+    "                messages = messages,\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"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get Llama 3.2 to answer\n",
+    "import ollama\n",
+    "\n",
+    "stream = ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True)\n",
+    "response = \"\"\n",
+    "display_handle = display(Markdown(\"\"), display_id=True)\n",
+    "for chunk in stream:\n",
+    "    response += chunk[\"message\"][\"content\"] or ''\n",
+    "    response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n",
+    "    update_display(Markdown(response), display_id=display_handle.display_id)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2a573174-779b-4d50-8792-fa0889b37211",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "llmenv",
+   "language": "python",
+   "name": "llmenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}