{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Introduction to Stable Diffusion and Google Colab Workshop for Capricon 2023 \n",
        "Jim Plaxco, www.artsnova.com\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "#SECTION 1: OPENAI GPT-3 and DALL-E\n",
        "\n",
        "---\n"
      ],
      "metadata": {
        "id": "KeQDzLbLmhET"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Step 1**: Make sure that the runtime type is GPU \n",
        "        ( Runtime -> Change Runtime type -> Hardware Accelerator =  GPU )\n",
        "        Click Save after selecting GPU\n",
        "Verify GPU availability\n",
        "\n",
        "Documentation for the nvidia command is at https://developer.nvidia.com/nvidia-system-management-interface\n",
        "\n"
      ],
      "metadata": {
        "id": "_W0Ai6zdKTwU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!nvidia-smi"
      ],
      "metadata": {
        "id": "mUNxBmgYnOQN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Step 2**: Install the openai library"
      ],
      "metadata": {
        "id": "dSDiDjCOnUE8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install openai"
      ],
      "metadata": {
        "id": "uerbDU33Uc60"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Step 3**: Import the getpass library and use it to enter your private openai API key. Using getpass() your key will not be written to the screen."
      ],
      "metadata": {
        "id": "EpIYEM-ZKaTo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import getpass\n",
        "mykey = getpass.getpass(\"Enter your openAI API Key: \")\n",
        "#print(password)"
      ],
      "metadata": {
        "id": "WC6Z7QNi08kX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eaab41d3-6b20-4fb5-8ab9-a3ba2f8e043f"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Enter your openAI API Key: ··········\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Step 4**: import the libraries you will use and set the openai api key\n",
        "\n",
        "This only needs to be done once per session."
      ],
      "metadata": {
        "id": "HeNc6C2WSNyE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import openai\n",
        "import random\n",
        "openai.api_key = mykey"
      ],
      "metadata": {
        "id": "udO1YrpPSYOk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Step 5**: Use GPT-3 model to generate text responses.\n",
        "\n",
        "The number of responses to generate is controlled by the variable gty.\n",
        "\n",
        "The temperature for each response is set to a random value based on range input. 0 is for well defined answers and 1 is for more creative answers"
      ],
      "metadata": {
        "id": "EJ-Z_fO7LM0R"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "IcCYpJwmTcID"
      },
      "outputs": [],
      "source": [
        "# use the GPT-3 model to generate text \n",
        "engineToUse= \"text-davinci-002\"\n",
        "qty = 2 #@param {type:\"number\"}\n",
        "minTemp=0.44 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
        "maxTemp=0.53 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
        "thePrompt = \"Tell me about artificial intelligence as depicted in science fiction.\" #@param {type:\"string\"}\n",
        "\n",
        "for x in range(qty):\n",
        "  thetemp = random.uniform(minTemp,maxTemp)\n",
        "  completions = openai.Completion.create(engine=engineToUse, prompt=thePrompt, max_tokens=3048,n=1,stop=None,temperature=thetemp,)\n",
        "  theResponse = completions.choices[0].text  # <class 'openai.openai_object.OpenAIObject'>\n",
        "  print(\"\\n\",thetemp, theResponse, \"\\n-----------------------------------------------------\")\n",
        "\n",
        "print(\"*** DONE ***\")  "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Step5B**: Or you can submit a list of prompts"
      ],
      "metadata": {
        "id": "uhbxg3pGpBHD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# import openai  only need to do this once\n",
        "# openai.api_key = mykey  # only need to do this once\n",
        "# openai.api_key = \"key string\"\n",
        "# use the GPT-3 model to generate responses\n",
        "promptlist = [f\"make up a name for a high tech product\", f\"Write a limerick about science fiction\", f\"what is CSS?\"]\n",
        "qty=2 # this is the number of responses to generate for each prompt\n",
        "for x in promptlist:\n",
        "    print(\"Response to the prompt: \", x)\n",
        "    for i in range(qty):\n",
        "        completions = openai.Completion.create(engine=\"text-davinci-002\",prompt=x,max_tokens=3024,n=1,stop=None,temperature=0.5,)\n",
        "        message = completions.choices[0].text\n",
        "        print(message)\n",
        "    print(\"----------------------------------\")\n",
        "print(\"*** END ***\")  "
      ],
      "metadata": {
        "id": "wPJeVXS1iCTN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Use Dall-E to Generate Images**\n",
        "\n",
        "Generate a single image based on the Prompt"
      ],
      "metadata": {
        "id": "jWBv4ltYq77h"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# NOTE: Image objects are tied to the session and are deleted when the session is disconnected\n",
        "# available sizes are is not one of ['256x256', '512x512', '1024x1024']\n",
        "# Parameters for openai.Image.create()\n",
        "# n:  integer, Optional, Defaults to 1, The number of images to generate. Must be between 1 and 10.\n",
        "# size: string, Optional, Defaults to 1024x1024, The size of the generated images. Must be one of 256x256, 512x512, or 1024x1024.\n",
        "# See https://beta.openai.com/docs/api-reference/images\n",
        "#\n",
        "dallePrompt = \"An image of an artificial intelligence as depicted in science fiction.\" #@param {type:\"string\"}\n",
        "response = openai.Image.create(\n",
        "  prompt = dallePrompt,\n",
        "  n = 1,\n",
        "  size = \"512x512\"\n",
        ")\n",
        "image_url = response['data'][0]['url']  # response is in the form of <class 'openai.openai_object.OpenAIObject'> \n",
        "print(image_url)"
      ],
      "metadata": {
        "id": "2xmzqMmOmRCJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5c3bcf38-f525-44eb-fa13-cd66929538c2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "https://oaidalleapiprodscus.blob.core.windows.net/private/org-7bpCzjBfiJRYpOW55skcuhEx/user-dU4knlZxj16rUFWZAJqCQxMR/img-WPvM2tcAisLVxG1kdbNPzUui.png?st=2023-01-30T20%3A58%3A20Z&se=2023-01-30T22%3A58%3A20Z&sp=r&sv=2021-08-06&sr=b&rscd=inline&rsct=image/png&skoid=6aaadede-4fb3-4698-a8f6-684d7786b067&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2023-01-30T13%3A24%3A06Z&ske=2023-01-31T13%3A24%3A06Z&sks=b&skv=2021-08-06&sig=QK2LeKCp2TiMEBjwyqrxDDZUZIbReCpwumjhsah18eI%3D\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Use Dall-E to Generate Images**\n",
        "\n",
        "Generate multiple images based on the Prompt\n"
      ],
      "metadata": {
        "id": "ufLH0CQ8s13l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# NOTE: Image objects are tied to the session and are deleted when the session is disconnected\n",
        "# available sizes are is not one of ['256x256', '512x512', '1024x1024']\n",
        "# Parameters for openai.Image.create()\n",
        "# n:  integer, Optional, Defaults to 1, The number of images to generate. Must be between 1 and 10.\n",
        "# size: string, Optional, Defaults to 1024x1024, The size of the generated images. Must be one of 256x256, 512x512, or 1024x1024.\n",
        "# See https://beta.openai.com/docs/api-reference/images\n",
        "\n",
        "dallePrompt = \"What is your prompt?\" #@param {type:\"string\"}\n",
        "numberOfImages = 2 #@param {type:\"number\"}\n",
        "\n",
        "# response variable is an openai.openai_object.OpenAIObject\n",
        "response = openai.Image.create(\n",
        "  prompt = dallePrompt,\n",
        "  n = numberOfImages,\n",
        "  size = \"1024x1024\"\n",
        ")\n",
        "# get the url of where the generated image is and print it out\n",
        "for ndx in range(numberOfImages):\n",
        "  image_url = response['data'][ndx]['url']\n",
        "  print(\"Image {} URL: {}\\n\".format(ndx,image_url))\n",
        "\n",
        "print(\"*** DONE ***\")  "
      ],
      "metadata": {
        "id": "1frAGY6_mb7K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **The End**"
      ],
      "metadata": {
        "id": "sHzLWHGWzPwC"
      }
    }
  ]
}