164 lines
4.3 KiB
Plaintext
164 lines
4.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "227e221d-cb4c-4b52-9c4f-2bcff51b00a5",
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"metadata": {},
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"source": [
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"# This exercise is to test and try generating images using gpt. Note: This API is more expensive."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dddabc12-ce06-45c1-875c-ab7e32b94e10",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import requests\n",
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"from dotenv import load_dotenv\n",
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"from IPython.display import Markdown, display\n",
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"from openai import OpenAI\n",
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"\n",
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"# If you get an error running this cell, then please head over to the troubleshooting notebook!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ef28b0bd-f11f-4b2a-88b4-112f932c9132",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load environment variables in a file called .env\n",
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"\n",
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"load_dotenv(override=True)\n",
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"api_key = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"# Check the key\n",
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"\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif not api_key.startswith(\"sk-proj-\"):\n",
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" print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
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"elif api_key.strip() != api_key:\n",
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" print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
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"else:\n",
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" print(\"API key found and looks good so far!\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d8f1af3b-c748-41f0-95f3-e21f512e7539",
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"metadata": {},
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"outputs": [],
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"source": [
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"openai = OpenAI()\n",
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"\n",
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"# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
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"# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2319710e-10a4-4964-acec-276ad43442c0",
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"metadata": {},
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"source": [
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"# Setup done. Below code is for image generation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "77d07d13-b2d0-4402-94a6-02a46632ac8e",
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"metadata": {},
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"outputs": [],
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"source": [
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"pip show openai"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1b28e163-7518-4b18-b1a7-c6a6f5b7f62c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# client = openai.OpenAI()\n",
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"\n",
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"response = openai.images.generate(\n",
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" model=\"gpt-image-1\", # or \"dall-e-2\"\n",
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" prompt=\"realistic peaceful sunset\",\n",
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" size=\"1024x1024\",\n",
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" quality=\"high\", # or \"hd\" (for DALL·E 3 only, costs more)\n",
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" n=1\n",
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")\n",
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"\n",
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"# image_url = response.data[0].url\n",
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"# print(image_url)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b121b843-680f-4abd-9aaa-1b3eb9393541",
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"metadata": {},
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"outputs": [],
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"source": [
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"import base64\n",
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"\n",
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"image_base64 = response.data[0].b64_json\n",
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"image_bytes = base64.b64decode(image_base64)\n",
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"\n",
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"# Save the image to a file\n",
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"with open(\"genimage.png\", \"wb\") as f:\n",
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" f.write(image_bytes)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "75b24ef1-c779-490a-a763-5bb8ede8903b",
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"metadata": {},
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"outputs": [],
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"source": [
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"from IPython.display import Image\n",
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"Image(filename='genimage.png') "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b4b6a4a4-88ff-40ea-9434-6a667939d800",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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