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   "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": [
    "import os\n",
    "import ollama\n",
    "from dotenv import load_dotenv\n",
    "from IPython.display import Markdown, display, update_display\n",
    "from openai import OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a456906-915a-4bfd-bb9d-57e505c5093f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# constants\n",
    "\n",
    "load_dotenv(override=True)\n",
    "api_key = os.getenv('OPENAI_API_KEY')\n",
    "\n",
    "if api_key and api_key.startswith('sk-proj-') and len(api_key)>10:\n",
    "    print(\"API key looks good so far\")\n",
    "else:\n",
    "    print(\"There might be a problem with your API key? Please visit the troubleshooting notebook!\")\n",
    "\n",
    "MODEL_GPT = 'gpt-4o-mini'\n",
    "MODEL_LLAMA = 'llama3.2'\n",
    "\n",
    "openai = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8d7923c-5f28-4c30-8556-342d7c8497c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set up environment\n",
    "system_prompt = \"You are an assistant that analyzes a technical question \\\n",
    "and responds with a short, clear, structured explanation. Response in markdown\"\n",
    "\n",
    "def get_user_prompt(question):\n",
    "    user_prompt = f\"You are looking at a technical questions as following: \\n\"\n",
    "    user_prompt += question\n",
    "    user_prompt += f\"\\nPlease response answer with a logical explanation\"\n",
    "    return user_prompt"
   ]
  },
  {
   "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",
    "def stream_QA(question):\n",
    "    stream = openai.chat.completions.create(\n",
    "        model= MODEL_GPT,\n",
    "        messages = [\n",
    "            {\"role\": \"system\", \"content\": system_prompt},\n",
    "            {\"role\": \"user\", \"content\": get_user_prompt(question)}\n",
    "        ],\n",
    "        stream=True\n",
    "    )\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",
    "stream_QA(question)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get Llama 3.2 to answer\n",
    "\n",
    "def ollama_QA(question):\n",
    "    response = ollama.chat(model=MODEL_LLAMA, messages = [\n",
    "            {\"role\": \"system\", \"content\": system_prompt},\n",
    "            {\"role\": \"user\", \"content\": get_user_prompt(question)}\n",
    "        ])\n",
    "    return Markdown(response['message']['content'])\n",
    "\n",
    "ollama_QA(question)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b484100-e5cf-40db-827c-d5618b154654",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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