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post.py
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post.py
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# file: post.py
# author: @aidenetre
# description: This file contains the Post class that will be used to generate fake news posts
#------------------------------------IMPORTS------------------------------------#
import os
import openai
import requests
import re
import io
import textwrap
import time
from PIL import Image, ImageDraw, ImageFont
from datetime import date
from pathlib import Path
# Set up OpenAI API Key
openai.api_key = os.getenv("OPENAI_API_KEY") # Set your OpenAI API key here, retrieve from PATH
class Post:
def __init__(self, is_educational = False):
self.is_educational = is_educational
self.news_headline = None
self.image_prompt = None
self.post_description = None
self.image_url = None
self.image = None
self.image_path = None
if self.is_educational: # Generate an educational post if the 'is_educational' argument is True
self._generate_educational_post()
else:
self._generate_post() # Generate a fake news post if the 'is_educational' argument is False
if self.news_headline is None or self.image_prompt is None or self.post_description is None or self.image is None:
raise ValueError("Failed to generate content") # Raise an error if the content is not generated
def _generate_headline(self): # Generates the fake news headline using the prompt as a prompt
max_retries = 10 # Maximum number of retries
retry_delay = 5 # Delay between retries
for attempt in range(max_retries): # Retries if there is an error
try:
today = date.today() # Gets the current date
base_news_prompt = f"Generate a short current financial news headline for the current date, only respond with the headline {today}:"
response = openai.ChatCompletion.create(
model = "gpt-3.5-turbo",
messages = [{"role": "user", "content": base_news_prompt}],
max_tokens = 100,
temperature = 0.7,
top_p = 1,
)
generated_news_headline = response["choices"][0]["message"]["content"].strip() # Extracts the fake news headline from the generated post
self.news_headline = self._extract_headline(generated_news_headline)
break
except openai.error.APIConnectionError as e: # Retries if there is an error
if attempt < max_retries - 1: # Retries if there is an error
print(f"Error generating headline: {e}. Retrying in {retry_delay} seconds.")
time.sleep(retry_delay)
retry_delay *= 2
else: # Gives up if there is an error
print(f"Error generating headline: {e}. Giving up after {max_retries} retries.")
self.news_headline = None
break
def _generate_educational_headline(self): # Generates the educational headline using the prompt as a prompt
max_retries = 10 # Maximum number of retries
retry_delay = 5 # Delay between retries
for attempt in range(max_retries): # Retries if there is an error
try:
base_educational_prompt = "Generate the title for a social media post aiming to educate users on a topic about critical data literacy, only respond with the title :"
response = openai.ChatCompletion.create(
model = "gpt-3.5-turbo",
messages = [{"role": "user", "content": base_educational_prompt}],
max_tokens = 100,
temperature = 0.7,
top_p = 1,
)
generated_educational_headline = response["choices"][0]["message"]["content"].strip()
self.news_headline = self._extract_headline(generated_educational_headline)
break
except openai.error.APIConnectionError as e: # Retries if there is an error
if attempt < max_retries - 1: # Retries if there is an error
print(f"Error generating headline: {e}. Retrying in {retry_delay} seconds.")
time.sleep(retry_delay)
retry_delay *= 2
else: # Gives up if there is an error
print(f"Error generating headline: {e}. Giving up after {max_retries} retries.")
self.news_headline = None
break
def _generate_image_prompt(self): # Generates the image prompt using the headline as a prompt
try:
base_image_prompt = f"Write a sentence describing the image in an instagram post relating to the financial news headline: {self.news_headline} using the following template: PROMPT: <A [format] of [scene] in the style of [style], [perspective].> You need to replace the parameters in the brackets. Use the following lists to choose from for each one: format: ... style: ... perspective: ... The scene parameter needs to specify an object or subject performing an action. Describe the scenery. Describe the mood and the lighting."
response = openai.ChatCompletion.create( # Generates the image prompt using the headline as a prompt
model = "gpt-3.5-turbo",
messages = [{"role": "user", "content": base_image_prompt}],
max_tokens = 200,
temperature = 0.7,
top_p = 1,
)
generated_image_prompt = response["choices"][0]["message"]["content"] # Extracts the image prompt from the generated post
self.image_prompt = self._extract_image_prompt(generated_image_prompt)
except openai.error.OpenAIError as e:
print(f"Error generating image prompt: {e}")
self.image_prompt = None
def _generate_educational_image_prompt(self): # Generates the educational image prompt using the headline as a prompt
try:
base_image_prompt = f"Write a sentence describing the image in an educational Instagram post relating to the critical data literacy topic: {self.news_headline} using the following template: PROMPT: <A [format] of [scene] in the style of [style], [perspective].> You need to replace the parameters in the brackets. Use the following lists to choose from for each one: format: ... style: ... perspective: ... The scene parameter needs to specify an object or subject performing an action. Describe the scenery. Describe the mood and the lighting."
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": base_image_prompt}],
max_tokens=200,
temperature=0.5,
top_p=1,
)
generated_image_prompt = response["choices"][0]["message"]["content"]
self.image_prompt = self._extract_image_prompt(generated_image_prompt)
except openai.error.OpenAIError as e:
print(f"Error generating educational image prompt: {e}")
self.image_prompt = None
def _generate_post_description(self): # Generates the post description using the headline as a prompt
try:
description_prompt = f"Create an Instagram post for the following financial news headline: {self.news_headline} using the following template: DESCRIPTION: <description including hashtags and emojis.>"
response = openai.ChatCompletion.create( # Generates the post description
model = "gpt-3.5-turbo",
messages = [{"role": "user", "content": description_prompt}],
max_tokens = 250,
temperature = 0.5,
top_p = 1,
)
generated_post_description = response["choices"][0]["message"]["content"] # Extracts the post description from the generated post
self.post_description = self._extract_post_description(generated_post_description)
except openai.error.OpenAIError as e:
print(f"Error generating post: {e}")
self.post_description = None
def _generate_educational_post_description(self): # Generates the educational post description using the headline as a prompt
try:
description_prompt = f"Create an Instagram post to educate social media users on the following critical data literacy topic: {self.news_headline} using the following template: DESCRIPTION: <description including hashtags and emojis.>"
response = openai.ChatCompletion.create(
model = "gpt-3.5-turbo",
messages = [{"role": "user", "content": description_prompt}],
max_tokens = 250,
temperature = 0.5,
top_p=1,
)
generated_post_description = response["choices"][0]["message"]["content"]
self.post_description = self._extract_post_description(generated_post_description)
except openai.error.OpenAIError as e:
print(f"Error generating educational post: {e}")
self.post_description = None
def _generate_image(self): # Generates the image using the image prompt as a prompt
try:
response = openai.Image.create(
prompt = self.image_prompt,
num_images = 1,
)
self.image_url = response["data"][0]["url"] # Extracts the image URL from the generated post
# Download the image and add the headline to the resized image
image_response = requests.get(self.image_url)
image = Image.open(io.BytesIO(image_response.content))
resized_image = self.resize_image(image, (1080, 1080))
self.image = self.add_headline_to_image(resized_image, self.news_headline)
except openai.error.OpenAIError as e:
print(f"Error generating image: {e}")
self.image_url = None
self.image = None
@staticmethod
def _extract_headline(generated_headline): # Extracts the headline from the generated post
if generated_headline.startswith("nt"): # Removes the "nt" from the start of the headline
generated_headline = generated_headline[2:].strip()
# Remove any quotations around the headline
generated_headline = generated_headline.strip('"')
generated_headline = generated_headline.strip("'")
return generated_headline # Returns the headline
@staticmethod
def _extract_image_prompt(generated_image_prompt): # Extracts the image prompt from the generated post
try:
# Find the index of "PROMPT: "
prompt_index = generated_image_prompt.find("PROMPT: ") + len("PROMPT: ") # Finds the index of "PROMPT: "
# Extract the prompt
image_prompt = generated_image_prompt[prompt_index:].strip() # Removes the "PROMPT: " from the start of the prompt
if image_prompt.startswith("nt"): # Removes the "nt" from the start of the prompt
image_prompt = image_prompt[2:].strip()
return image_prompt # Returns the image prompt
except Exception as e:
print(f"Error extracting image prompt: {e}")
return None
@staticmethod
def _extract_post_description(generated_post_description): # Extracts the post description from the generated post
try:
# Find the index of "DESCRIPTION: "
description_index = generated_post_description.find("DESCRIPTION: ") + len("DESCRIPTION: ") # Finds the index of "DESCRIPTION: "
# Extract the description
post_description = generated_post_description[description_index:].strip() # Removes the "DESCRIPTION: " from the start of the description
if post_description.startswith("nt"): # Removes the "nt" from the start of the description
post_description = post_description[2:].strip()
return post_description # Returns the post description
except Exception as e:
print(f"Error extracting post description: {e}")
return None
def sanitize_filename(self, filename): # Sanitizes the filename to remove any invalid characters
filename = filename.replace("\n", " ")
return re.sub(r'[^\w\s]+', '_', filename)
def resize_image(self, image, size): # Resizes the image to the specified size
return image.resize(size, Image.ANTIALIAS)
def add_headline_to_image(self, image, headline, font_path = '/fonts/timesbd.ttf', font_size = 80): # Adds the headline to the image
draw = ImageDraw.Draw(image)
font = ImageFont.truetype(font_path, font_size)
width, height = image.size
# Wrap the text within the image boundaries
wrapped_headline = textwrap.fill(headline, width = (width - 40) // font.getsize("x")[0])
text_width, text_height = draw.multiline_textsize(wrapped_headline, font)
# Calculate the position of the text box
x = (width - text_width) // 2
y = int(height * 0.75 - text_height // 2)
# Draw the semi-transparent gray background
background_height = height // 2
background = Image.new("RGBA", (width, background_height), (50, 50, 50, 200))
image.paste(background, (0, height - background_height), background)
# Draw the wrapped headline text
draw.multiline_text((x, y), wrapped_headline, font = font, fill = (255, 255, 255), align = "center")
return image
def _save_post(self, output_dir = "generated_posts"): # Saves the generated post to the specified directory
try:
unique_id = int(time.time())
output_path = Path(output_dir) / str(unique_id)
output_path.mkdir(parents=True, exist_ok=True)
sanitized_headline = self.sanitize_filename(self.news_headline)
post_filename = output_path / f"{sanitized_headline[:10]}_post.txt"
with open(post_filename, "w", encoding = "utf-8") as post_file:
post_file.write(f"Headline: {self.news_headline}\n\n")
post_file.write(f"Image Prompt: {self.image_prompt}\n\n")
post_file.write(f"Image URL: {self.image_url}\n\n")
post_file.write(f"Description: {self.post_description}\n\n")
# Save the resized image with the headline instead of the base image
image_filename = output_path / f"{sanitized_headline[:10]}_image.jpg"
self.image_path = image_filename
with open(image_filename, "wb") as image_file:
self.image.save(image_file, "JPEG")
print(f"Post and image saved to {output_path}")
except Exception as e:
print(f"Error saving post and image: {e}")
def _generate_post(self): # Generates a post
try:
self._generate_headline()
self._generate_image_prompt()
self._generate_post_description()
self._generate_image()
self._save_post()
except ValueError as e:
print(f"Error generating post: {e}")
def _generate_educational_post(self): # Generates an educational post
try:
self._generate_educational_headline()
self._generate_educational_image_prompt()
self._generate_educational_post_description()
self._generate_image()
self._save_post()
except ValueError as e:
print(f"Error generating post: {e}")