copywriter and blog metadata updates
This commit is contained in:
ajaysi
@@ -6,6 +6,7 @@ import streamlit as st
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from loguru import logger
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import random
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import asyncio
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import re
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logger.remove()
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logger.add(sys.stdout,
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@@ -17,110 +18,367 @@ from ..gpt_providers.text_generation.main_text_generation import llm_text_gen
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async def blog_metadata(blog_article):
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""" Common function to get blog metadata """
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logger.info(f"Generating Content MetaData\n")
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"""
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Generate comprehensive SEO metadata for a blog article.
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Args:
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blog_article (str): The content of the blog article
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Returns:
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tuple: (blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug)
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"""
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logger.info("Generating comprehensive blog metadata")
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progress_bar = st.progress(0)
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total_steps = 4
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total_steps = 6 # Increased steps for new metadata types
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status_container = st.empty()
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# Step 1: Generate blog title
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await asyncio.sleep(random.uniform(1, 3))
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blog_title = generate_blog_title(blog_article)
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progress_bar.progress(1 / total_steps)
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try:
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# Step 1: Generate blog title
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status_container.info("Generating SEO-optimized blog title...")
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await asyncio.sleep(random.uniform(0.5, 1.5))
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blog_title = generate_blog_title(blog_article)
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progress_bar.progress(1 / total_steps)
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# Step 2: Generate blog meta description
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await asyncio.sleep(random.uniform(1, 3))
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blog_meta_desc = generate_blog_description(blog_article)
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progress_bar.progress(2 / total_steps)
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# Step 2: Generate blog meta description
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status_container.info("Creating compelling meta description...")
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await asyncio.sleep(random.uniform(0.5, 1.5))
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blog_meta_desc = generate_blog_description(blog_article)
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progress_bar.progress(2 / total_steps)
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# Step 3: Generate blog tags
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await asyncio.sleep(random.uniform(1, 3))
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blog_tags = get_blog_tags(blog_article)
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progress_bar.progress(3 / total_steps)
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# Step 3: Generate blog tags
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status_container.info("Extracting relevant blog tags...")
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await asyncio.sleep(random.uniform(0.5, 1.5))
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blog_tags = get_blog_tags(blog_article)
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progress_bar.progress(3 / total_steps)
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# Step 4: Generate blog categories
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await asyncio.sleep(random.uniform(1, 3))
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blog_categories = get_blog_categories(blog_article)
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progress_bar.progress(4 / total_steps)
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# Step 4: Generate blog categories
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status_container.info("Identifying primary blog categories...")
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await asyncio.sleep(random.uniform(0.5, 1.5))
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blog_categories = get_blog_categories(blog_article)
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progress_bar.progress(4 / total_steps)
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# Step 5: Generate social media hashtags
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status_container.info("Creating social media hashtags...")
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await asyncio.sleep(random.uniform(0.5, 1.5))
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blog_hashtags = generate_blog_hashtags(blog_article)
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progress_bar.progress(5 / total_steps)
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# Step 6: Generate SEO URL slug
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status_container.info("Generating SEO-friendly URL slug...")
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await asyncio.sleep(random.uniform(0.5, 1.5))
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blog_slug = generate_blog_slug(blog_title)
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progress_bar.progress(6 / total_steps)
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# Present the result in a table format
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st.table({
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"Metadata": ["Blog Title", "Meta Description", "Tags", "Categories"],
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"Value": [blog_title, blog_meta_desc, blog_tags, blog_categories]
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})
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# Present the result in a table format
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status_container.success("✅ Metadata generation complete")
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st.table({
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"Metadata": ["Blog Title", "Meta Description", "Tags", "Categories", "Social Hashtags", "URL Slug"],
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"Value": [blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug]
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})
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return blog_title, blog_meta_desc, blog_tags, blog_categories
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return blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug
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except Exception as e:
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status_container.error(f"Error generating metadata: {str(e)}")
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logger.error(f"Failed to generate metadata: {str(e)}")
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# Return default values to ensure the blog generation process can continue
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return f"Blog Article", "An informative blog post", "content, blog", "General, Information", "#content #blog", "blog-article"
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def generate_blog_title(blog_article):
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"""
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Given a blog title generate an outline for it
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Generate an SEO-optimized and engaging title for a blog article.
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Args:
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blog_article (str): The content of the blog article
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Returns:
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str: An SEO-optimized title
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"""
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logger.info("Generating blog title.")
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prompt = f"""As a SEO expert, I will provide you with a blog content.
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Your task is write a SEO optimized and call to action, blog title for given blog content.
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Follow SEO best practises to suggest the blog title.
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Please keep the titles concise, not exceeding 60 words.
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Respond with only the title and no explanations.
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Negative Keywords: Unvieling, unleash, power of. Dont use such words in your title.
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\nGenerate blog title for this given blog content:\n '{blog_article}' """
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logger.info("Generating SEO-optimized blog title")
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# Extract the first 3000 characters for title generation
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snippet = blog_article[:3000] if len(blog_article) > 3000 else blog_article
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prompt = f"""As an expert SEO copywriter, create the perfect blog title based on this content.
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REQUIREMENTS:
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1. Make it compelling, specific, and actionable
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2. Include primary keywords naturally near the beginning
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3. Keep it between 50-60 characters (10-12 words maximum)
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4. Make it promise clear value to the reader
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5. Use power words that evoke emotion where appropriate
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AVOID:
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- Clickbait tactics or false promises
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- Generic titles that could apply to any article
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- Using words like "unveiling", "unleash", "power of", "ultimate guide", or "complete"
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- ALL CAPS or excessive punctuation!!!!
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EXAMPLES OF GREAT TITLES:
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- "7 Proven Strategies to Improve Your Email Marketing ROI"
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- "Why Remote Work Improves Productivity: New Research Findings"
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- "How to Build a Personal Budget That Actually Works"
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CONTENT TO ANALYZE:
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"{snippet}"
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Reply with ONLY the title and no other text or explanation.
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"""
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try:
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response = llm_text_gen(prompt)
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return response
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title = llm_text_gen(prompt)
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# Clean up any quotes or extra spaces
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title = title.strip('"\'').strip()
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logger.info(f"Generated title: {title}")
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return title
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except Exception as err:
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logger.error(f"Failed to get response from LLM: {err}")
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raise err
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logger.error(f"Failed to generate blog title: {err}")
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return "Blog Article" # Fallback title
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def generate_blog_description(blog_content):
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"""
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Prompt designed to give SEO optimized blog descripton
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Generate an SEO-optimized meta description for the blog.
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Args:
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blog_content (str): The content of the blog article
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Returns:
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str: An SEO-optimized meta description
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"""
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logger.info("Generating Blog Meta Description for the given blog.")
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prompt = f"""As an expert SEO and blog writer, Compose a compelling meta description for the given blog content,
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adhering to SEO best practices. Keep it between 150-160 characters.
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Provide a glimpse of the content's value to entice readers.
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Respond with only one of your best effort and do not include your explanations.
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Blog Content: '{blog_content}'"""
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logger.info("Generating SEO-optimized meta description")
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# Extract the first 2000 characters for description generation
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snippet = blog_content[:2000] if len(blog_content) > 2000 else blog_content
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prompt = f"""As an SEO expert, write the perfect meta description for this blog content.
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try:
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response = llm_text_gen(prompt)
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return response
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except Exception as err:
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logger.error(f"Failed to get response from LLM:{err}")
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raise err
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REQUIREMENTS:
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1. Exactly 150-160 characters (this is critical for SEO)
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2. Include primary keywords naturally
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3. Compelling value proposition that makes readers want to click
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4. Clear indication of what the reader will learn/gain
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5. End with an implicit call-to-action when possible
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def get_blog_categories(blog_article):
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"""
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Function to generate blog categories for given blog content.
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"""
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prompt = f"""As an expert SEO and content writer, I will provide you with blog content.
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Suggest only 2 blog categories which are most relevant to provided blog content,
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by identifying the main topic. Also consider the target audience and the
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blog's category taxonomy. Only reply with comma separated values.
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The blog content is: '{blog_article}'"
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"""
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logger.info("Generating blog categories for the given blog.")
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EXAMPLES OF EXCELLENT META DESCRIPTIONS:
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- "Learn how to increase email open rates by 43% with these 5 proven strategies from industry experts. Implement today for immediate results."
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- "Discover why 67% of professionals struggle with work-life balance and explore research-backed techniques to reclaim your time and energy."
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CONTENT TO SUMMARIZE:
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"{snippet}"
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Reply with ONLY the meta description and no other text. Keep it between 150-160 characters exactly.
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"""
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try:
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response = llm_text_gen(prompt)
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return response
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description = llm_text_gen(prompt)
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# Clean up any quotes or extra spaces
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description = description.strip('"\'').strip()
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logger.info(f"Generated meta description: {description}")
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return description
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except Exception as err:
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logger.error(f"get_blog_categories:Failed to get response from LLM: {err}")
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logger.error(f"Failed to generate blog description: {err}")
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return "An informative blog post about this topic." # Fallback description
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def get_blog_tags(blog_article):
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"""
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Function to suggest tags for the given blog content
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Generate relevant SEO tags for a blog article.
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Args:
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blog_article (str): The content of the blog article
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Returns:
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str: Comma-separated list of relevant tags
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"""
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prompt = f"""As an expert SEO and blog writer, suggest only 2 relevant and specific blog tags
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for the given blog content. Only reply with comma separated values.
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Blog content: {blog_article}."""
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logger.info("Generating Blog tags for the given blog post.")
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logger.info("Generating SEO-optimized blog tags")
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# Extract the first 3000 characters for tag generation
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snippet = blog_article[:3000] if len(blog_article) > 3000 else blog_article
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prompt = f"""As an SEO specialist, extract the 4-6 most relevant tags for this blog post.
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REQUIREMENTS:
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1. Choose specific, targeted keywords that accurately represent the content
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2. Include a mix of broad and specific tags
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3. Focus on terms users would actually search for
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4. Include at least one long-tail keyword phrase
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5. Ensure all tags are directly addressed in the content
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CONTENT TO ANALYZE:
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"{snippet}"
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Reply with ONLY the tags as a comma-separated list (e.g., "keyword1, keyword2, keyword3, keyword phrase"). Provide 4-6 tags total.
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"""
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try:
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response = llm_text_gen(prompt)
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return response
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tags = llm_text_gen(prompt)
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# Clean up any quotes or extra commas
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tags = tags.strip('"\'').strip()
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if tags.endswith(','):
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tags = tags[:-1]
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logger.info(f"Generated tags: {tags}")
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return tags
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except Exception as err:
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logger.error(f"Failed to get response from LLM: {err}")
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raise err
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logger.error(f"Failed to generate blog tags: {err}")
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return "content, blog" # Fallback tags
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def get_blog_categories(blog_article):
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"""
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Identify the most appropriate blog categories for the article.
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Args:
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blog_article (str): The content of the blog article
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Returns:
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str: Comma-separated list of relevant categories
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"""
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logger.info("Generating blog categories")
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# Extract the first 2000 characters for category generation
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snippet = blog_article[:2000] if len(blog_article) > 2000 else blog_article
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prompt = f"""As a content strategist, identify the 2-3 most appropriate high-level categories for this blog.
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REQUIREMENTS:
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1. Choose broad, established categories used in content organization
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2. Select categories that best represent the main themes of the article
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3. Consider the target audience and their interests
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4. Focus on categories that would help with site navigation
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5. Aim for a primary category and 1-2 supporting categories
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EXAMPLES OF GOOD CATEGORIES:
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- Marketing, Social Media, Strategy
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- Finance, Personal Budgeting, Money Management
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- Productivity, Remote Work, Business
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CONTENT TO ANALYZE:
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"{snippet}"
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Reply with ONLY the categories as a comma-separated list (e.g., "Category1, Category2, Category3"). Provide 2-3 categories total.
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"""
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try:
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categories = llm_text_gen(prompt)
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# Clean up any quotes or extra commas
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categories = categories.strip('"\'').strip()
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if categories.endswith(','):
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categories = categories[:-1]
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logger.info(f"Generated categories: {categories}")
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return categories
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except Exception as err:
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logger.error(f"Failed to generate blog categories: {err}")
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return "General, Information" # Fallback categories
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def generate_blog_hashtags(blog_article):
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"""
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Generate social media hashtags for promoting the blog article.
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Args:
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blog_article (str): The content of the blog article
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Returns:
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str: Space-separated list of hashtags starting with #
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"""
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logger.info("Generating social media hashtags")
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# Extract the first 2000 characters for hashtag generation
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snippet = blog_article[:2000] if len(blog_article) > 2000 else blog_article
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prompt = f"""As a social media strategist, create 5-7 effective hashtags for this blog content.
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REQUIREMENTS:
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1. Mix of popular and niche hashtags for better visibility
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2. Include industry-specific and trending hashtags where relevant
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3. Avoid overly generic hashtags (like #content or #blog)
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4. Format each hashtag with # symbol and camelCase or separate words
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5. Include at least one branded or campaign-style hashtag
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EXAMPLES OF EFFECTIVE HASHTAG SETS:
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- #EmailMarketing #ROITips #DigitalStrategy #MarketingTips #GrowthHacking #EmailROI
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- #RemoteWork #ProductivityTips #FutureOfWork #WorkFromHome #RemoteProductivity #HRInsights
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CONTENT TO ANALYZE:
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"{snippet}"
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Reply with ONLY the hashtags, each starting with # and separated by spaces. Provide 5-7 hashtags total.
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"""
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try:
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hashtags = llm_text_gen(prompt)
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# Clean up any quotes or extra spaces
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hashtags = hashtags.strip('"\'').strip()
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# Ensure all hashtags start with #
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if not hashtags.startswith('#'):
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hashtags = ' '.join([f"#{tag.strip('#')}" for tag in hashtags.split()])
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logger.info(f"Generated hashtags: {hashtags}")
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return hashtags
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except Exception as err:
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logger.error(f"Failed to generate blog hashtags: {err}")
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return "#content #blog" # Fallback hashtags
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def generate_blog_slug(blog_title):
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"""
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Generate an SEO-friendly URL slug from the blog title.
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Args:
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blog_title (str): The title of the blog article
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Returns:
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str: An SEO-friendly URL slug
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"""
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logger.info("Generating SEO-friendly URL slug")
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try:
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# Use a prompt to generate a customized slug
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prompt = f"""As an SEO specialist, create an SEO-friendly URL slug for this blog title: "{blog_title}"
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REQUIREMENTS:
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1. Keep it under 60 characters
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2. Use only lowercase letters, numbers, and hyphens
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3. Include primary keywords near the beginning
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4. Remove all unnecessary words (a, the, and, or, but, etc.)
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5. Ensure it's human-readable and descriptive
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EXAMPLES:
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- Title: "10 Effective Ways to Improve Your Email Marketing ROI This Quarter"
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Slug: "improve-email-marketing-roi"
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- Title: "Why Most Remote Workers Are More Productive According to New Research"
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Slug: "remote-workers-productivity-research"
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Reply with ONLY the slug and no other text or explanation.
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"""
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slug = llm_text_gen(prompt)
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# Clean up and normalize the slug
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slug = slug.strip('"\'').strip()
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# If the LLM didn't create a proper slug, do it programmatically
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if not re.match(r'^[a-z0-9-]+$', slug):
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# Fallback to simple programmatic slug creation
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slug = blog_title.lower()
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# Remove special characters
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slug = re.sub(r'[^a-z0-9\s-]', '', slug)
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# Replace spaces with hyphens
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slug = re.sub(r'\s+', '-', slug)
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# Remove redundant hyphens
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slug = re.sub(r'-+', '-', slug)
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# Limit length to 60 characters
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slug = slug[:60].strip('-')
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logger.info(f"Generated slug: {slug}")
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return slug
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except Exception as err:
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logger.error(f"Failed to generate blog slug: {err}")
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# Create a simple slug programmatically as fallback
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slug = blog_title.lower()
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slug = re.sub(r'[^a-z0-9\s-]', '', slug)
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slug = re.sub(r'\s+', '-', slug)
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slug = re.sub(r'-+', '-', slug)
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slug = slug[:60].strip('-')
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return slug
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# Helper function to run the asyncio event loop within Streamlit
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def run_async(coro):
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