LLM_Engineering_OLD/week1/community-contributions/day-1-to-do-list using-ollama.ipynb

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   "id": "f61139a1-40e1-4273-b9a6-5a0a9d63a9bd",
   "metadata": {},
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   "source": [
    "import requests\n",
    "import json\n",
    "from reportlab.lib.pagesizes import letter\n",
    "from reportlab.pdfgen import canvas\n",
    "from IPython.display import display, FileLink\n",
    "from IPython.display import display, HTML, FileLink\n",
    "from reportlab.lib.pagesizes import A4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "e0858b96-fd41-4911-a333-814e4ed23279",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting reportlab\n",
      "  Downloading reportlab-4.2.5-py3-none-any.whl.metadata (1.5 kB)\n",
      "Requirement already satisfied: pillow>=9.0.0 in c:\\users\\legion\\anaconda3\\envs\\to_do_list\\lib\\site-packages (from reportlab) (11.0.0)\n",
      "Collecting chardet (from reportlab)\n",
      "  Downloading chardet-5.2.0-py3-none-any.whl.metadata (3.4 kB)\n",
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      "Downloading chardet-5.2.0-py3-none-any.whl (199 kB)\n",
      "Installing collected packages: chardet, reportlab\n",
      "Successfully installed chardet-5.2.0 reportlab-4.2.5\n"
     ]
    }
   ],
   "source": [
    "!pip install reportlab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "62cc9d37-c801-4e8a-ad2c-7b1450725a10",
   "metadata": {},
   "outputs": [],
   "source": [
    "OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
    "HEADERS = {\"Content-Type\":\"application/json\"}\n",
    "MODEL = \"llama3.2\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "525a81e7-30f8-4db7-bc8d-29948195bd4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_prompt = \"\"\"You are a to-do list generator. Based on the user's input, you will create a clear and descriptive to-do\n",
    "list using bullet points. Only generate the to-do list as bullet points with some explaination and time fraame only if asked for and nothing else. \n",
    "Be a little descriptive.\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "id": "7fca3303-3add-468a-a6bd-be7a4d72c811",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_to_do_list(task_description):\n",
    "    payload = {\n",
    "        \"model\": MODEL,\n",
    "        \"messages\": [\n",
    "            {\"role\": \"system\", \"content\": system_prompt},\n",
    "            {\"role\": \"user\", \"content\": task_description}\n",
    "        ],\n",
    "        \"stream\": False\n",
    "    }\n",
    "\n",
    "    response = requests.post(OLLAMA_API, json=payload, headers=HEADERS)\n",
    "\n",
    "    if response.status_code == 200:\n",
    "        try:\n",
    "            json_response = response.json()\n",
    "            to_do_list = json_response.get(\"message\", {}).get(\"content\", \"No to-do list found.\")\n",
    "            \n",
    "            formatted_output = \"Your To-Do List:\\n\\n\" + to_do_list\n",
    "            file_name = \"to_do_list.txt\"\n",
    "            \n",
    "            with open(file_name, \"w\", encoding=\"utf-8\") as file:\n",
    "                file.write(formatted_output)\n",
    "\n",
    "            return file_name\n",
    "        \n",
    "        except Exception as e:\n",
    "            return f\"Error parsing JSON: {e}\"\n",
    "    else:\n",
    "        return f\"Error: {response.status_code} - {response.text}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "id": "d45d6c7e-0e89-413e-8f30-e4975ea6d043",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the task description of the to-do list: Give me a 4-week to-do list plan for a wedding reception party.\n"
     ]
    }
   ],
   "source": [
    "task_description = input(\"Enter the task description of the to-do list:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "id": "5493da44-e254-4d06-b973-a8069c2fc625",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "result = generate_to_do_list(task_description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "id": "5e95c722-ce1a-4630-b21a-1e00e7ba6ab9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p>You can download your to-do list by clicking the link below:</p>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<a href='to_do_list.txt' target='_blank'>to_do_list.txt</a><br>"
      ],
      "text/plain": [
       "C:\\Users\\Legion\\to-do list using ollama\\to_do_list.txt"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(HTML(\"<p>You can download your to-do list by clicking the link below:</p>\"))\n",
    "display(FileLink(result))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3d0a44e-bca4-4944-8593-1761c2f73a70",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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