assignments/assignment_yourname_t81_559_class5.ipynb

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    "<a href=\"https://colab.research.google.com/github/jeffheaton/app_generative_ai/blob/main/assignments/assignment_yourname_t81_559_class5.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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   "source": [
    "# T81-559: Applications of Generative AI\n",
    "* Instructor: [Jeff Heaton](https://sites.wustl.edu/jeffheaton/), McKelvey School of Engineering, [Washington University in St. Louis](https://engineering.wustl.edu/index.html)\n",
    "* For more information visit the [class website](https://sites.wustl.edu/jeffheaton/t81-559/).\n",
    "\n",
    "**Module 5 Assignment: LangChain Data Extraction**\n",
    "\n",
    "**Student Name: Your Name**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lky4xopspO-Z"
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   "source": [
    "# Assignment Instructions\n",
    "\n",
    "Make use of the LangChain CommaSeparatedListOutputParser to first find 10 programming languages. Then for each programming language find 10 features, produce a table similar to this.\n",
    "\n",
    "| Language   | Feature 1                       | Feature 2                    | ...                           | Feature 10                |\n",
    "|------------|---------------------------------|------------------------------|-------------------------------|---------------------------|\n",
    "| Python     | Dynamic typing                  | Interpreted language          | ...                           | Object-oriented           |\n",
    "| Java       | Object-oriented                 | Platform-independent          | ...                           | Robust exception handling |\n",
    "| C++        | Object-oriented programming     | Strongly typed                | ...                           | Compile-time polymorphism |\n",
    "| JavaScript | Dynamic typing                  | First-class functions         | ...                           | Extensive community support|\n",
    "| Ruby       | Object-oriented                 | Dynamic typing                | ...                           | Cross-platform compatibility|\n",
    "| Go         | Concurrency support             | Garbage collection            | ...                           | Fast compilation times    |\n",
    "| Swift      | Type safety                     | Optionals                     | ...                           | Strong community support  |\n",
    "| PHP        | Dynamic typing                  | Cross-platform compatibility  | ...                           | Wide range of frameworks and libraries |\n",
    "| Rust       | Memory safety                   | Zero-cost abstractions        | ...                           | Excellent tooling         |\n",
    "| Kotlin     | Null safety                     | Extension functions           | ...                           | Concise syntax            |\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
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   "metadata": {
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   "source": [
    "# Google CoLab Instructions\n",
    "\n",
    "If you are using Google CoLab, it will be necessary to mount your GDrive so that you can send your notebook during the submit process. Running the following code will map your GDrive to ```/content/drive```."
   ]
  },
  {
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   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1ZnCEIEopO-Z",
    "outputId": "e09ce29b-8aed-4f64-bf27-6e9b9cd03919"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "try:\n",
    "  from google.colab import drive, userdata\n",
    "  drive.mount('/content/drive', force_remount=True)\n",
    "  COLAB = True\n",
    "  print(\"Note: using Google CoLab\")\n",
    "except:\n",
    "  print(\"Note: not using Google CoLab\")\n",
    "  COLAB = False\n",
    "\n",
    "# Assignment Submission Key - Was sent you first week of class.\n",
    "# If you are in both classes, this is the same key.\n",
    "if COLAB:\n",
    "  # For Colab, add to your \"Secrets\" (key icon at the left)\n",
    "  key = userdata.get('T81_559_KEY')\n",
    "else:\n",
    "  # If not colab, enter your key here, or use an environment variable.\n",
    "  # (this is only an example key, use yours)\n",
    "  key = \"Gx5en9cEVvaZnjhdaushddhuhhO4PsI32sgldAXj\"\n",
    "\n",
    "# OpenAI Secrets\n",
    "if COLAB:\n",
    "    os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY')\n",
    "\n",
    "# Install needed libraries in CoLab\n",
    "if COLAB:\n",
    "    !pip install langchain langchain_openai"
   ]
  },
  {
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   "metadata": {
    "id": "PMLHwV0hpO-a"
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   "source": [
    "# Assignment Submit Function\n",
    "\n",
    "You will submit the 10 programming assignments electronically.  The following submit function can be used to do this.  My server will perform a basic check of each assignment and let you know if it sees any basic problems.\n",
    "\n",
    "**It is unlikely that should need to modify this function.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "source": [
    "import base64\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "import PIL\n",
    "import PIL.Image\n",
    "import io\n",
    "from typing import List, Union\n",
    "\n",
    "# This function submits an assignment.  You can submit an assignment as much as you like, only the final\n",
    "# submission counts.  The paramaters are as follows:\n",
    "# data - List of pandas dataframes or images.\n",
    "# key - Your student key that was emailed to you.\n",
    "# course - The course that you are in, currently t81-558 or t81-559.\n",
    "# no - The assignment class number, should be 1 through 10.\n",
    "# source_file - The full path to your Python or IPYNB file.  This must have \"_class1\" as part of its name.\n",
    "# .             The number must match your assignment number.  For example \"_class2\" for class assignment #2.\n",
    "\n",
    "def submit(\n",
    "    data: List[Union[pd.DataFrame, PIL.Image.Image]],\n",
    "    key: str,\n",
    "    course: str,\n",
    "    no: int,\n",
    "    source_file: str = None\n",
    ") -> None:\n",
    "    if source_file is None and '__file__' not in globals():\n",
    "        raise Exception(\"Must specify a filename when in a Jupyter notebook.\")\n",
    "    if source_file is None:\n",
    "        source_file = __file__\n",
    "\n",
    "    suffix = f'_class{no}'\n",
    "    if suffix not in source_file:\n",
    "        raise Exception(f\"{suffix} must be part of the filename.\")\n",
    "\n",
    "    ext = os.path.splitext(source_file)[-1].lower()\n",
    "    if ext not in ['.ipynb', '.py']:\n",
    "        raise Exception(f\"Source file is {ext}; must be .py or .ipynb\")\n",
    "\n",
    "    with open(source_file, \"rb\") as file:\n",
    "        encoded_python = base64.b64encode(file.read()).decode('ascii')\n",
    "\n",
    "    payload = []\n",
    "    for item in data:\n",
    "        if isinstance(item, PIL.Image.Image):\n",
    "            buffered = io.BytesIO()\n",
    "            item.save(buffered, format=\"PNG\")\n",
    "            payload.append({'PNG': base64.b64encode(buffered.getvalue()).decode('ascii')})\n",
    "        elif isinstance(item, pd.DataFrame):\n",
    "            payload.append({'CSV': base64.b64encode(item.to_csv(index=False).encode('ascii')).decode(\"ascii\")})\n",
    "        else:\n",
    "            raise ValueError(f\"Unsupported data type: {type(item)}\")\n",
    "\n",
    "    response = requests.post(\n",
    "        \"https://api.heatonresearch.com/wu/submit\",\n",
    "        headers={'x-api-key': key},\n",
    "        json={\n",
    "            'payload': payload,\n",
    "            'assignment': no,\n",
    "            'course': course,\n",
    "            'ext': ext,\n",
    "            'py': encoded_python\n",
    "        }\n",
    "    )\n",
    "\n",
    "    if response.status_code == 200:\n",
    "        print(f\"Success: {response.text}\")\n",
    "    else:\n",
    "        print(f\"Failure: {response.text}\")"
   ]
  },
  {
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   },
   "source": [
    "# Assignment #5 Sample Code\n",
    "\n",
    "The following code provides a starting point for this assignment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "8ZPLGWgkpO-a"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "from scipy.stats import zscore\n",
    "import string\n",
    "\n",
    "# You must identify your source file.  (modify for your local setup)\n",
    "file=\"/content/drive/My Drive/Colab Notebooks/assignment_yourname_t81_559_class5.ipynb\"  # Google CoLab\n",
    "# file='C:\\\\Users\\\\jeffh\\\\projects\\\\t81_559_deep_learning\\\\assignments\\\\assignment_yourname_t81_559_class5.ipynb'  # Windows\n",
    "# file='/Users/jheaton/projects/t81_559_deep_learning/assignments/assignment_yourname_t81_559_class5.ipynb'  # Mac/Linux\n",
    "\n",
    "# Begin assignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 675
    },
    "id": "jFtm7i7H3Pmw",
    "outputId": "6aaae26c-a3f6-4638-a947-85b33791dccc"
   },
   "outputs": [],
   "source": [
    "from langchain.output_parsers import CommaSeparatedListOutputParser\n",
    "from langchain_core.prompts import PromptTemplate\n",
    "from langchain_openai import ChatOpenAI\n",
    "import pandas as pd\n",
    "\n",
    "## ... continue your code...\n",
    "\n",
    "## Submit assignment\n",
    "submit(source_file=file,data=[df_submit],course='t81-559',key=key,no=5)"
   ]
  }
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