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Blogen-V0.1 AI blog writer. Video, Image, Research and write blogs.

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This commit is contained in:
AjaySi
2023-11-09 13:22:30 +05:30
parent eb87847124
commit d91688055b
118 changed files with 61599 additions and 3142 deletions
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181
lib/generate_image_from_prompt.py
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@@ -8,27 +8,23 @@
#########################################################
# imports
import sys
import datetime
import openai # OpenAI Python library to make API calls
import requests # used to download images
import os # used to access filepaths
from PIL import Image # used to logger.info and edit images
from loguru import logger
logger.remove()
logger.add(sys.stdout,
colorize=True,
format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
)
# set API key
# Taking from env is safer than hardcoding here. But, not all have shell to export.
# Better to take it from a config file and pass it as a parameter.
# variable OPENAI_API_KEY=<API-KEY>
openai.api_key = os.environ.get("OPENAI_API_KEY")
# set a directory to save DALL·E images to
image_dir_name = "blog_images"
image_dir = os.path.join(os.curdir, image_dir_name)
# create the directory if it doesn't yet exist
if not os.path.isdir(image_dir):
os.mkdir(image_dir)
from .gpt_providers.openai_gpt_provider import generate_dalle2_images, generate_dalle3_images, openai_chatgpt
from .stabl_diff_img2html import generate_stable_diffusion_image
def generate_image(logger, num_images=1, img_size="1024x1024", response_format="url"):
def generate_image(user_prompt, image_dir, image_engine="dalle3"):
"""
The generation API endpoint creates an image based on a text prompt.
@@ -36,6 +32,7 @@ def generate_image(logger, num_images=1, img_size="1024x1024", response_format="
prompt (str): A text description of the desired image(s). The maximum length is 1000 characters.
Optional inputs:
--> image_engine: dalle2, dalle3, stable diffusion are supported.
--> num_images (int): The number of images to generate. Must be between 1 and 10. Defaults to 1.
--> size (str): The size of the generated images. Must be one of "256x256", "512x512", or "1024x1024".
Smaller images are faster. Defaults to "1024x1024".
@@ -43,137 +40,37 @@ def generate_image(logger, num_images=1, img_size="1024x1024", response_format="
Must be one of "url" or "b64_json". Defaults to "url".
--> user (str): A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse.
"""
# logger.info the directory to save to. TBD: Need to log these.
logger.info(f"Generated blog images will be stored at: {image_dir=}")
# TBD: Ask gpt for prompt for AI generated images as:
img_prompt = generate_img_prompt(user_prompt)
# call the OpenAI API to generate image from prompt.
logger.info(f"Calling openai.image.generate with prompt: {img_prompt}")
if 'dalle2' in image_engine:
image_stored_at = generate_dalle2_images(img_prompt, image_dir)
elif 'dalle3' in image_engine:
image_stored_at = generate_dalle3_images(img_prompt, image_dir)
elif 'stable_diffusion' in image_engine:
image_stored_at = generate_stable_diffusion_image(img_prompt, image_dir)
return image_stored_at
def generate_img_prompt(user_prompt):
"""
Given prompt, this functions generated a prompt for image generation.
"""
# I want you to act as an artist advisor providing advice on various art styles such tips on utilizing
# light & shadow effects effectively in painting, shading techniques while sculpting etc.
# Develop prompts for an AI-generated art piece inspired by [concept], using [symbolism] and [metaphor].
# Provide prompts for an AI-generated art piece inspired by [era] art, incorporating [medium] and [subject matter].
# Develop a set of prompts that could be used to generate AI-generated art focused on the theme of “urban decay.”
# I want you to act as a prompt generator for Science Fiction Art and
# give me five prompts that transport me to a futuristic world.
# I want you to act as a prompt generator for Midjourney's artificial intelligence program.
# Your job is to provide detailed and creative descriptions that will inspire unique and interesting images from the AI.
# Keep in mind that the AI is capable of understanding a wide range of language and can interpret abstract concepts,
# so feel free to be as imaginative and descriptive as possible. For example,
# you could describe a scene from a futuristic city, or a surreal landscape filled with strange creatures.
# The more detailed and imaginative your description, the more interesting the resulting image will be.
# Here is your first prompt: ""
prompt = "An illustration of AI teaching human to speak"
# call the OpenAI API to generate image from prompt.
logger.info(f"Calling openai.image.generate with prompt: {prompt}")
try:
img_generation_response = openai.Image.create(
prompt=prompt,
n=1,
size="1024x1024",
response_format="url",
)
except AttributeError as aerr:
logger.info(f"Failed to generate Image, Try: pip install openai --upgrade in your terminal.Error: {aerr}")
else:
# logger.info response/result. dbg.
print(f"{img_generation_response}")
save_generated_image(logger, img_generation_response)
def save_generated_image(logger, img_generation_response):
"""
"""
# save the image
# We need to change the image name to unique, overwrite and for SEO considerations.
# Note: filetype should be *.png
generated_image_name = "generated_image.png"
generated_image_filepath = os.path.join(image_dir, generated_image_name)
# extract image URL from response
generated_image_url = img_generation_response["data"][0]["url"]
print(f"Extracted URL: {generated_image_url}")
# We use the requests library to fetch the image from URL
response = requests.get(generated_image_url, stream=True)
# We use the Image Class from PIL library to open the image
Image.open(response.raw)
# Download the image.
try:
generated_image = requests.get(generated_image_url).content
except requests.exceptions.RequestException as e:
raise SystemExit(f"Failed to get generted image content: {e}")
else:
with open(generated_image_filepath, "wb") as image_file:
# Write the image to a file and store.
image_file.write(generated_image)
# Optional, dbg.
# logger.info the image
#logger.info(generated_image_filepath)
print("Display the generated image.")
img = Image.open(generated_image_filepath)
img.show()
# Close image window.
#for proc in psutil.process_iter():
# if proc.name() == "Image Viewer":
# proc.kill()
# WIP
# The idea is to download images from other blogs and recreate from it.
# This helps us generate images very close to the topic and also not worry about prompt message.
def gen_new_from_given_img(logger, num_img=1, img_size="1024x1024", response_format="url"):
"""
This function will take an image and produce a variant of it.
Required inputs:
image (str): The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square.
Optional inputs:
n (int): The number of images to generate. Must be between 1 and 10. Defaults to 1.
size (str): The size of the generated images. Must be one of "256x256", "512x512", or "1024x1024".
Smaller images are faster. Defaults to "1024x1024".
response_format (str): The format in which the generated images are returned. Must be one of "url" or "b64_json". Defaults to "url".
user (str): A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse.
"""
img_path = "/home/ajsingh/pseo_experiments_V0.0.1/blog_images/variation_example.png"
try:
png = Image.open(img_path).convert('RGBA')
background = Image.new('RGBA', png.size, (255, 255, 255))
alpha_composite = Image.alpha_composite(background, png)
alpha_composite.save('foo.png', 'PNG', quality=80)
variation_response = openai.Image.create_variation(
image=open('foo.jpg', "rb"),
n=num_img,
size=img_size,
response_format=response_format,
)
except Exception as err:
logger.error(f"An error occured in Image.create_variation::: {err}")
SystemExit(1)
# logger.info response
logger.info(variation_response)
# save the images
variation_urls = [datum["url"] for datum in variation_response["data"]] # extract URLs
variation_images = [requests.get(url).content for url in variation_urls] # download images
variation_image_names = [f"variation_image_{i}.png" for i in range(len(variation_images))] # create names
variation_image_filepaths = [os.path.join(image_dir, name) for name in variation_image_names] # create filepaths
for image, filepath in zip(variation_images, variation_image_filepaths): # loop through the variations
with open(filepath, "wb") as image_file: # open the file
image_file.write(image) # write the image to the file
# logger.info the original image
logger.info(generated_image_filepath)
orig_img = Image.open(generated_image_filepath)
orig_img.show()
# logger.info the new variations
for variation_image_filepaths in variation_image_filepaths:
logger.info(variation_image_filepaths)
var_img = Image.open(variation_image_filepaths)
var_img.show()
logger.info(f"Generate image prompt for : {user_prompt}")
prompt = f"""As an educationist and expert infographic artist, your tasked to create prompts that will be used for image generation.
Craft prompt for Openai Dall-e image generation program. Clearly describe the given text to represent it as image.
Make sure to avoid common image generation mistakes.
Advice for creating prompt for image from the given text(no more than 150 words).
Reply with only one answer and no descrition. Generate image prompt for the below text.
Text: {user_prompt}"""
response = openai_chatgpt(prompt)
return response