Add tutorial code

openai-dalle/README.md

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+# Generate Images With DALL·E 2 and the OpenAI API
+
+Learn to use the OpenAI Python library to create images with DALL·E, a state-of-the-art latent diffusion model. In the associated tutorial on [generating images with DALL·E 2 and the OpenAI API](https://realpython.com/generate-images-with-dalle-openai-api/), you explore image creation and generating image variations. You learn to interact with DALL·E using API calls, and incorporate this functionality into your Python scripts.
+
+## Setup
+
+Create and activate a virtual environment, then install the `openai` package:
+
+```console
+$ python --version
+Python 3.11.0
+$ python -m venv venv
+$ source venv/bin/activate
+(venv) $ python -m pip install openai
+```
+
+You need to be on Python 3.7.1 or higher.
+
+## Create Images and Image Variations
+
+Follow the instructions in [the tutorial](https://realpython.com/generate-images-with-dalle-openai-api/) to create images from text prompts, create image variations, and convert a Base64 JSON response to a PNG image file.
+
+You can find the code for each of these steps in dedicated scripts:
+
+- `create.py`: Create an image from a text prompt and save the image data to a file.
+- `convert.py`: Convert a Base64 encoded PNG image delivered in a JSON response to a PNG image file.
+- `vary.py`: Read Base64 encoded image data and make an API request to receive variations of that image.
+
+The tutorial walks you through each of these scripts and their functionality and output in more detail.
+
+## Edit Images (Inpainting and Outpainting)
+
+The OpenAI Image API also allows you to [edit parts of an image](https://beta.openai.com/docs/guides/images/edits) using text prompts. For this, you need to create a mask with transparent image data in the area where you want to edit the image.
+
+You can run `edit.py` to give this functionality a try.

openai-dalle/convert.py

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+import json
+from base64 import b64decode
+from pathlib import Path
+
+JSON_FILE_NAME = "An ec-1667994848"
+IMAGE_DIR = Path.cwd() / "images" / JSON_FILE_NAME
+DATA_DIR = Path.cwd() / "responses"
+
+IMAGE_DIR.mkdir(parents=True, exist_ok=True)
+
+with open(DATA_DIR / f"{JSON_FILE_NAME}.json", "r") as f:
+    response = json.load(f)
+
+for index, image_dict in enumerate(response["data"]):
+    image_data = b64decode(image_dict["b64_json"])
+    with open(IMAGE_DIR / f"{JSON_FILE_NAME}-{index}.png", "wb") as f:
+        f.write(image_data)

openai-dalle/create.py

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+import json
+import os
+from pathlib import Path
+
+import openai
+
+PROMPT = "An eco-friendly computer from the 90s in the style of vaporwave"
+DATA_DIR = Path.cwd() / "responses"
+
+DATA_DIR.mkdir(exist_ok=True)
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+response = openai.Image.create(
+    prompt=PROMPT,
+    n=1,
+    size="256x256",
+    response_format="b64_json",
+)
+
+file_name = DATA_DIR / f"{PROMPT[:5]}-{response['created']}.json"
+
+with open(file_name, mode="w") as file_path:
+    json.dump(response, file_path)

openai-dalle/edit.py

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+import json
+import os
+from pathlib import Path
+
+import openai
+
+SOURCE_PATH = Path.cwd() / "images" / "An ec-1667994848"
+DESTINATION_PATH = Path.cwd() / "responses"
+PROMPT = "A 90s vaporwave computer showing Rick Astley on the screen"
+
+SOURCE_PATH.mkdir(parents=True, exist_ok=True)
+DESTINATION_PATH.mkdir(parents=True, exist_ok=True)
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+response = openai.Image.create_edit(
+    image=open(SOURCE_PATH / "computer.png", "rb"),
+    mask=open(SOURCE_PATH / "mask.png", "rb"),
+    prompt=PROMPT,
+    n=1,
+    size="256x256",
+    response_format="b64_json",
+)
+
+with open(
+    DESTINATION_PATH / f"edit-{PROMPT[:5]}-{response['created']}.json",
+    mode="w",
+) as fp:
+    json.dump(response, fp)

openai-dalle/vary.py

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+import json
+import os
+from base64 import b64decode
+from pathlib import Path
+
+import openai
+
+SOURCE_FILE = "A com-1667994848.json"
+DATA_DIR = Path.cwd() / "responses"
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+with open(DATA_DIR / SOURCE_FILE, "r") as json_file:
+    saved_response = json.load(json_file)
+    image_data = b64decode(saved_response["data"][0]["b64_json"])
+
+response = openai.Image.create_variation(
+    image=image_data,
+    n=3,
+    size="256x256",
+    response_format="b64_json",
+)
+
+new_file_name = f"vary-{SOURCE_FILE[:4]}-{response['created']}.json"
+
+with open(DATA_DIR / new_file_name, mode="w") as new_json_file:
+    json.dump(response, new_json_file)