WIP000.1- AI content writer
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AjaySi
150
lib/main_youtube_research_blog.py
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150
lib/main_youtube_research_blog.py
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import json
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import os
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import sys
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from loguru import logger
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# Import from local packages
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from .gpt_providers.openai_chat_completion import openai_chatgpt
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from .gpt_providers.gpt_vision_img_details import analyze_and_extract_details_from_image
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from .generate_image_from_prompt import generate_image
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from .write_blogs_from_youtube_videos import youtube_to_blog
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from .wordpress_blog_uploader import compress_image, upload_blog_post, upload_media
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from .gpt_online_researcher import do_online_research
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from .save_blog_to_file import save_blog_to_file
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from .optimize_images_for_upload import optimize_image
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from .combine_research_and_blog import blog_with_research
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from .get_blog_meta_desc import generate_blog_description
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from .get_blog_title import generate_blog_title
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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 .convert_content_to_markdown import convert_tomarkdown_format
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from .convert_markdown_to_html import convert_markdown_to_html
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from .utils.youtube_keyword_research import research_yt
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# Configuring the logger
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logger.remove()
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logger.add(sys.stdout, colorize=True, format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}")
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# Constants for directory paths
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IMAGE_DIR = os.path.join(os.getcwd(), "blog_images")
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OUTPUT_PATH = os.path.join(os.getcwd(), "blogs")
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def generate_youtube_research_blog(yt_keywords):
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"""
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Research YouTube based on given keywords and get top video URLs.
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"""
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for ayt_keyword in yt_keywords:
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yt_research_response = ''
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data = {}
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logger.info(f"Researching YouTube top videos for: {yt_keywords}")
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try:
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yt_research_response = research_yt(ayt_keyword)
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if not yt_research_response:
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yt_research_response = research_yt(ayt_keyword)
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except Exception as err:
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logger.error(f"Failed to do YouTube Research: {err}")
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if not yt_research_response.strip():
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logger.warning("Error: JSON data is empty.")
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yt_research_response = research_yt(ayt_keyword)
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else:
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try:
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aggregated_data = load_response_json(yt_research_response, ayt_keyword)
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except Exception as err:
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logger.error(f"Failed to load json response: {err}")
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sys.exit(1)
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for title, a_yt_url, views, references, quickstart_code in zip(
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aggregated_data["titles"], aggregated_data["urls"], aggregated_data["views"],
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aggregated_data["references"], aggregated_data["quickstart_codes"]):
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blog_markdown_str = ""
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if a_yt_url != "No URL Provided":
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# Transcribe the audio using whisper model.
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try:
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logger.info(f"Starting to write blog on URL: {a_yt_url}")
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blog_markdown_str, yt_title = youtube_to_blog(a_yt_url)
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logger.warning("\n\n--------------- First Draft of the Blog: --------\n\n")
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logger.info(f"{blog_markdown_str}\n")
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logger.warning("--------------------END of First draft----------\n\n")
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if not yt_title or not blog_markdown_str:
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logger.error("No content or title for audio to proceed.")
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sys.exit(1)
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except Exception as e:
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logger.error(f"Error in youtube_to_blog: {e}")
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sys.exit(1)
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sys.exit(1)
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if title != "Unknown Title":
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print(f"Title: {title}")
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if url != "No URL Provided":
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print(f"URL: {url}")
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if views != "No View Count":
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print(f"Views: {views}")
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if references: # Checks if references list is not empty
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print(f"References: {', '.join(references)}")
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if quickstart_code != "Code coming soon":
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print(f"Quickstart Code: {quickstart_code}")
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print() # Adds a newline for separation between entries
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def load_response_json(yt_research_response, yt_keyword):
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"""
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Load and parse the YouTube research response JSON.
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"""
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try:
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logger.info(f"Loading the JSON data for parsing: {yt_research_response}")
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data = json.loads(yt_research_response.replace('`', '').strip())
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if isinstance(data, dict):
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results_key = next((key for key in data if key.lower().startswith("result")), None)
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if results_key:
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research_yt_dict = process_results(data[results_key])
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elif isinstance(data, list):
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research_yt_dict = process_results(data)
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except json.JSONDecodeError as e:
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logger.error(f"load_response_json: Failed to parse JSON data: {e}")
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generate_youtube_research_blog([yt_keyword])
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return research_yt_dict
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def process_results(results):
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"""
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Process the results from the YouTube research JSON and return the aggregated data.
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Args:
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results (list): List of dictionaries containing YouTube video details.
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Returns:
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dict: A dictionary containing lists of titles, URLs, views, references, and quickstart codes.
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Raises:
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Exception: If an error occurs during the processing of individual entries.
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"""
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titles = []
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urls = []
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views_list = []
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references_list = []
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quickstart_codes = []
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for entry in results:
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try:
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titles.append(entry.get("Title", "Unknown Title"))
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urls.append(entry.get("URL", "No URL Provided"))
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views_list.append(entry.get("Views", "No View Count"))
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references_list.append(entry.get("References", []))
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quickstart_codes.append(entry.get("Quickstart_Code", "Code coming soon"))
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except Exception as e:
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logger.error(f"Error processing yt resulr entry: {e}")
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continue
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return {
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"titles": titles,
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"urls": urls,
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"views": views_list,
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"references": references_list,
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"quickstart_codes": quickstart_codes
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}
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