gptGame.ipynb

gptgame.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "gptGame.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNvL+d2I/JFziK/AIgD88dJ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/brockmanmatt/3629fce8f4c9bc3f8697346c5f897e41/gptgame.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J7wnsgT2kPut",
        "colab_type": "code",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "outputId": "41b56176-6413-40f6-9671-4e83189c00cd"
      },
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()\n",
        "print(\"done\")"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-d2454892-841b-4d82-9fc4-5519e754c969\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-d2454892-841b-4d82-9fc4-5519e754c969\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving key.json to key.json\n",
            "done\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WHPHrUnhpKnI",
        "colab_type": "text"
      },
      "source": [
        "I'll install the API"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zq0ltp2xn4yt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "outputId": "d959c6c5-fab3-4163-a591-554d1a320650"
      },
      "source": [
        "!pip install openai\n",
        "import openai, json, pandas as pd"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting openai\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/a8/65/c7461f4c87984534683f480ea5742777bc39bbf5721123194c2d0347dc1f/openai-0.2.4.tar.gz (157kB)\n",
            "\r\u001b[K     |██                              | 10kB 16.7MB/s eta 0:00:01\r\u001b[K     |████▏                           | 20kB 1.7MB/s eta 0:00:01\r\u001b[K     |██████▎                         | 30kB 2.2MB/s eta 0:00:01\r\u001b[K     |████████▍                       | 40kB 2.4MB/s eta 0:00:01\r\u001b[K     |██████████▍                     | 51kB 1.9MB/s eta 0:00:01\r\u001b[K     |████████████▌                   | 61kB 2.2MB/s eta 0:00:01\r\u001b[K     |██████████████▋                 | 71kB 2.4MB/s eta 0:00:01\r\u001b[K     |████████████████▊               | 81kB 2.6MB/s eta 0:00:01\r\u001b[K     |██████████████████▊             | 92kB 2.8MB/s eta 0:00:01\r\u001b[K     |████████████████████▉           | 102kB 2.7MB/s eta 0:00:01\r\u001b[K     |███████████████████████         | 112kB 2.7MB/s eta 0:00:01\r\u001b[K     |█████████████████████████       | 122kB 2.7MB/s eta 0:00:01\r\u001b[K     |███████████████████████████     | 133kB 2.7MB/s eta 0:00:01\r\u001b[K     |█████████████████████████████▏  | 143kB 2.7MB/s eta 0:00:01\r\u001b[K     |███████████████████████████████▎| 153kB 2.7MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 163kB 2.7MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests>=2.20 in /usr/local/lib/python3.6/dist-packages (from openai) (2.23.0)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->openai) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->openai) (2020.6.20)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->openai) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->openai) (2.10)\n",
            "Building wheels for collected packages: openai\n",
            "  Building wheel for openai (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for openai: filename=openai-0.2.4-cp36-none-any.whl size=170709 sha256=722e300e907330f062c86c9c3a996b10b576b140a2970268a9677378cd23f21c\n",
            "  Stored in directory: /root/.cache/pip/wheels/74/96/c8/c6e170929c276b836613e1b9985343b501fe455e53d85e7d48\n",
            "Successfully built openai\n",
            "Installing collected packages: openai\n",
            "Successfully installed openai-0.2.4\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q2yE0jcnpMEV",
        "colab_type": "text"
      },
      "source": [
        "Loading in key.json that I uploaded; I do this so I don't need to worry about accidently leaking creds if I share the colab (which I'm 99% sure is just a json file that won't expose them)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bwNXXwHen5x9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "openai.api_key = json.load(open(\"key.json\", \"r\"))[\"key\"]"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k67w5H0fpTkT",
        "colab_type": "text"
      },
      "source": [
        "Default keyword arguments to pass the aPI"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e1EwpqqJkTYh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#arguments to send the API\n",
        "kwargs = {\n",
        "\"engine\":\"davinci\",\n",
        "\"temperature\":.2,\n",
        "\"max_tokens\":50,\n",
        "\"stop\":\"\\n\\n\",\n",
        "}"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zZubgPoOpWDH",
        "colab_type": "text"
      },
      "source": [
        "Quick wrapper to automatically save prompts and responses sent for later analysis if needed"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sXTDJx0An9Bl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import datetime\n",
        "def query(prompt, myKwargs = kwargs):\n",
        "  \"\"\"\n",
        "  wrapper for the API to save the prompt and the result\n",
        "  \"\"\"\n",
        "\n",
        "  r = openai.Completion.create(prompt=prompt, **myKwargs)[\"choices\"][0][\"text\"].strip()\n",
        "  with open(\"{}.json\".format(datetime.datetime.now().strftime(\"%Y%m%d%s\")), \"w\") as fh:\n",
        "    json.dump({\"prompt\":prompt, \"response\":r}, fh, indent=4)\n",
        "  return r"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EdFXafcJpZ3Q",
        "colab_type": "text"
      },
      "source": [
        "Test to make sure my query works"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4SlyKgjyopPn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "9308452a-a2b7-403e-9a0d-5b958a5c60ae"
      },
      "source": [
        "newKwargs = kwargs.copy()\n",
        "newKwargs[\"stop\"] = \"\\n\"\n",
        "query(\"q: what is 1+1?\\na:\", newKwargs)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic": {
              "type": "string"
            },
            "text/plain": [
              "'2'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QMz6kFZwtTak",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "game = \"\"\"Here are the rules:\n",
        "Pets have life points, hunger points, energy points, and happiness points.\n",
        "Different interactions change their points. Hunger goes up each turn.\n",
        "\n",
        "My pet's name is max. His stats are initially:\n",
        "\n",
        "Turn: I begin game!\n",
        "consequence: no change to stats\n",
        "pet status: Life:100 - Hunger:0 - Energy:100 - Happiness:50\n",
        "pet activity: laying around\n",
        "\n",
        "Turn: I do nothing.\n",
        "consequence: Hunger increases, energy decreases, happiness decreases\n",
        "pet status: Life:100 - Hunger:10 - Energy:90 - Happiness:40\n",
        "pet activity: max is starts running around\n",
        "\n",
        "Turn: I give max a treat.\n",
        "consequence: life increases, hunger decreases, energy increases, happiness increases\n",
        "pet status: Life:110 - Hunger:0 - Energy:110 - Happiness:60\n",
        "pet activity: max needs to go to the bathroom\n",
        "\n",
        "Turn:{}\n",
        "consequence:\"\"\""
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KOOU6D2pt514",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "5db79e61-53ca-40b2-93df-d2565d304ee5"
      },
      "source": [
        "action = \"I take max to the park\"\n",
        "result = (query(game.format(action)))\n",
        "print(result)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "life increases, hunger decreases, energy decreases, happiness increases\n",
            "pet status: Life:110 - Hunger:0 - Energy:100 - Happiness:70\n",
            "pet activity: max is running around\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5nPObYBZt_ae",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "game = game.format(action)\n",
        "game = game + result + \"\\n\\nTurn:{}\\nconsequence:\""
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nWYE1oKovc3p",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "15903d72-4dad-4f44-d145-321237f467e2"
      },
      "source": [
        "action = \"I take max home\"\n",
        "result = (query(game.format(action)))\n",
        "print(result)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "no change to stats\n",
            "pet status: Life:110 - Hunger:0 - Energy:100 - Happiness:70\n",
            "pet activity: max is running around\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VIIpTtGDvlKX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "game = game.format(action)\n",
        "game = game + result + \"\\n\\nTurn:{}\\nconsequence:\""
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rAZsKicwvf27",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "f5d594da-191f-409a-9b48-e6b595d1020b"
      },
      "source": [
        "action = \"max gets attacked by a bear\"\n",
        "result = (query(game.format(action)))\n",
        "print(result)"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "life decreases, hunger increases, energy decreases, happiness decreases\n",
            "pet status: Life:100 - Hunger:10 - Energy:90 - Happiness:40\n",
            "pet activity: max is running around\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PxyCjqMnvlyA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}