WIP000.1- AI content writer
This commit is contained in:
AjaySi
@@ -1,113 +1,70 @@
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import sys
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import os
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from pathlib import Path
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import datetime
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from .gpt_providers.openai_chat_completion import openai_chatgpt
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import google.generativeai as genai
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from .gpt_providers.gemini_pro_text import gemini_text_response
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from .gpt_online_researcher import do_online_research
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from .get_blog_meta_desc import generate_blog_description
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from .get_tags import get_blog_tags
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from .get_blog_category import get_blog_categories
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from .get_blog_title import generate_blog_title
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from .get_code_examples import gemini_get_code_samples
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from .save_blog_to_file import save_blog_to_file
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from .take_url_screenshot import screenshot_api
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from dotenv import load_dotenv
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load_dotenv(Path('../.env'))
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from loguru import logger
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logger.remove()
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logger.add(sys.stdout,
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colorize=True,
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format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
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)
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def generate_detailed_blog(num_blogs, blog_keywords, niche, num_subtopics,
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wordpress=False, research_online=False, output_format="HTML"):
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def generate_keyword_blog(blog_keywords, url=None, output_format="markdown"):
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"""
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This function will take a blog Topic to first generate sections for it
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and then generate content for each section.
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"""
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# Use to store the blog in a string, to save in a *.md file.
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blog_markdown_str = ""
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# TBD: Check if the generated topics are equal to what user asked.
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blog_topic_arr = generate_blog_topics(blog_keywords, num_blogs, niche)
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logger.info(f"Generated Blog Topics:---- \n{blog_topic_arr}\n")
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# Split the string at newlines
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blog_topic_arr = blog_topic_arr.split('\n')
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# For each of blog topic, generate content.
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for a_blog_topic in blog_topic_arr:
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# if md/html
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a_blog_topic = a_blog_topic.replace('"', '')
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a_blog_topic = re.sub(r'^[\d.\s]+', '', a_blog_topic)
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blog_markdown_str = "# " + a_blog_topic + "\n\n"
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# Get the introduction specific to blog title and sub topics.
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tpc_outlines = generate_topic_outline(a_blog_topic, num_subtopics)
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tpc_outlines = tpc_outlines.split("\n")
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blog_intro = get_blog_intro(a_blog_topic, tpc_outlines)
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logger.info(f"The intro is:\n{blog_intro}")
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blog_markdown_str = blog_markdown_str + "### Introduction" + "\n\n" + f"{blog_intro}" + "\n\n"
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# Now, for each blog we have sub topic. Generate content for each of the sub topic.
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for a_outline in tpc_outlines:
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a_outline = a_outline.replace('"', '')
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logger.info(f"Generating content for sub-topic: {a_outline}")
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sub_topic_content = generate_topic_content(blog_keywords, a_outline)
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# a_outline is sub topic heading, hence part ToC also.
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#blog_markdown_str = blog_markdown_str + "\n\n" + f"### {a_outline}" + "\n\n"
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blog_markdown_str = blog_markdown_str + "\n" + f"\n {sub_topic_content}" + "\n\n"
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# Get the Conclusion of the blog, by passing the generated blog.
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blog_conclusion = get_blog_conclusion(blog_markdown_str)
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blog_markdown_str = blog_markdown_str + "### Conclusion" + "\n" + f"{blog_conclusion}" + "\n"
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for akeyword in blog_keywords:
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logger.info(f"Researching and Writing Blog on keywords: {akeyword}")
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# Use to store the blog in a string, to save in a *.md file.
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blog_markdown_str = ""
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# Call on the got-researcher, tavily apis for this. Do google search for organic competition.
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blog_markdown_str = do_online_research(akeyword, "gemini")
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# logger.info/check the final blog content.
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logger.info(f"Final blog content: {blog_markdown_str}")
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#if research_online:
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# # Call on the got-researcher, tavily apis for this. So many apis floating around.
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# report = do_online_research_on(blog_keywords)
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# blog_markdown_str = blog_with_research(report, blog_markdown_str)
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blog_meta_desc = generate_blog_description(blog_markdown_str)
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logger.info(f"\nThe blog meta description is:{blog_meta_desc}\n")
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# Generate an image based on meta description
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logger.info(f"Calling Image generation with prompt: {blog_meta_desc}")
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main_img_path = generate_image(blog_meta_desc, image_dir, "dalle3")
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blog_tags = get_blog_tags(blog_markdown_str)
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logger.info(f"\nBlog tags for generated content: {blog_tags}\n")
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blog_categories = get_blog_categories(blog_markdown_str)
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blog_title = generate_blog_title(blog_markdown_str, "gemini")
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blog_meta_desc = generate_blog_description(blog_markdown_str, "gemini")
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logger.info(f"The blog meta description is: {blog_meta_desc}\n")
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blog_tags = get_blog_tags(blog_markdown_str, "gemini")
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logger.info(f"Blog tags for generated content: {blog_tags}")
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blog_categories = get_blog_categories(blog_markdown_str, "gemini")
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logger.info(f"Generated blog categories: {blog_categories}\n")
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# Use chatgpt to convert the text into HTML or markdown.
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if 'html' in output_format:
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blog_markdown_str = convert_markdown_to_html(blog_markdown_str)
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#blog_markdown_str = gemini_get_code_samples(blog_markdown_str)
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#logger.info(f"Blog with code sample: \n {blog_markdown_str}")
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# Check if blog needs to be posted on wordpress.
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if wordpress:
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# Fixme: Fetch all tags and categories to check, if present ones are present and
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# use them else create new ones. Its better to use chatgpt than string comparison.
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# Similar tags and categories will be missed.
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# blog_categories =
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# blog_tags =
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logger.info("Uploading the blog to wordpress.\n")
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main_img_path = compress_image(main_img_path, quality=85)
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# fixme: Remove the hardcoding, need add another option OR in config ?
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image_dir = os.path.join(os.getcwd(), "blog_images")
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generated_image_name = f"generated_image_{datetime.datetime.now():%Y-%m-%d-%H-%M-%S}.png"
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generated_image_filepath = os.path.join(image_dir, generated_image_name)
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# Generate an image based on meta description
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#logger.info(f"Calling Image generation with prompt: {blog_meta_desc}")
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#main_img_path = generate_image(blog_meta_desc, image_dir, "dalle3")
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if url:
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try:
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img_details = analyze_and_extract_details_from_image(main_img_path)
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alt_text = img_details.get('alt_text')
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img_description = img_details.get('description')
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img_title = img_details.get('title')
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caption = img_details.get('caption')
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try:
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media = upload_media(wordpress_url, wordpress_username, wordpress_password,
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main_img_path, alt_text, img_description, img_title, caption)
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except Exception as err:
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sys.exit(f"Error occurred in upload_media: {err}")
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except Exception as e:
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sys.exit(f"Error occurred in analyze_and_extract_details_from_image: {e}")
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# Then create the post with the uploaded media as the featured image
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media_id = media['id']
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blog_markdown_str = convert_markdown_to_html(blog_markdown_str)
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try:
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upload_blog_post(wordpress_url, wordpress_username, wordpress_password, a_blog_topic,
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blog_markdown_str, media_id, blog_meta_desc, blog_categories, blog_tags, status='publish')
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generated_image_filepath = screenshot_api(url, generated_image_filepath)
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except Exception as err:
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sys.exit(f"Failed to upload blog to wordpress.Error: {err}")
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logger.error(f"Failed in taking compnay page screenshot: {err}")
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# TBD: Save the blog content as a .md file. Markdown or HTML ?
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save_blog_to_file(blog_markdown_str,
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a_blog_topic,
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blog_meta_desc, blog_tags,
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blog_categories, main_img_path)
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save_blog_to_file(blog_markdown_str, blog_title, blog_meta_desc, blog_tags, blog_categories, generated_image_filepath)
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# Now, we need perform some *basic checks on the blog content, such as:
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# is_content_ai_generated.py, plagiarism_checker_from_known_sources.py
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# seo_analyzer.py . These are present in the lib folder.
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# prompt: Rewrite, improve and paraphrase [text] and use headings and subheadings
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# to break up the content and make it easier to read using the keyword [keyword].
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logger.info(f"\n\n ################ Finished writing Blog for : {akeyword} #################### \n")
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