diff --git a/lib/ai_writers/gpt_blog_sections.py b/lib/ai_writers/gpt_blog_sections.py
index c0f93829..a266a31c 100644
--- a/lib/ai_writers/gpt_blog_sections.py
+++ b/lib/ai_writers/gpt_blog_sections.py
@@ -2,8 +2,8 @@ import sys
 import os
 import json
 
-from ..gpt_providers.openai_chat_completion import openai_chatgpt
-from ..gpt_providers.gemini_pro_text import gemini_text_response
+from ..gpt_providers.text_generation.openai_text_gen import openai_text_generation
+from ..gpt_providers.text_generation.gemini_pro_text import gemini_text_generation
 
 from loguru import logger
 logger.remove()
diff --git a/lib/ai_writers/keywords_to_blog_streamlit.py b/lib/ai_writers/keywords_to_blog_streamlit.py
index 4f286c7e..35b53fd1 100644
--- a/lib/ai_writers/keywords_to_blog_streamlit.py
+++ b/lib/ai_writers/keywords_to_blog_streamlit.py
@@ -25,25 +25,12 @@ from ..ai_web_researcher.gpt_online_researcher import (
         do_tavily_ai_search as gpt_do_tavily_ai_search,
         do_metaphor_ai_research, do_google_pytrends_analysis)
 from .blog_from_google_serp import write_blog_google_serp, blog_with_research
-from ..ai_web_researcher.you_web_reseacher import get_rag_results, search_ydc_index
 from ..blog_metadata.get_blog_metadata import blog_metadata
 from ..blog_postprocessing.save_blog_to_file import save_blog_to_file
 from ..gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
-
-
-# Function to convert text to speech and save as an audio file
-def text_to_speech(text, lang='en'):
-    tts = gTTS(text=text, lang=lang)
-    tts.save("output.mp3")
-    return "output.mp3"
-
-
-# Function to get audio file as a downloadable link
-def get_audio_file(audio_file):
-    with open(audio_file, "rb") as file:
-        data = file.read()
-        b64_data = base64.b64encode(data).decode()
-        return f'<a href="data:audio/mp3;base64,{b64_data}" download="output.mp3">Download audio file</a>'
+from ..ai_seo_tools.content_title_generator import generate_blog_titles
+from ..ai_seo_tools.meta_desc_generator import generate_blog_metadesc
+from ..ai_seo_tools.seo_structured_data import ai_structured_data
 
 
 def initialize_parameters(search_params=None, blog_params=None):
@@ -285,21 +272,22 @@ def generate_blog_metadata(blog_markdown_str, search_keywords, status):
         status: Streamlit status object
         
     Returns:
-        tuple: (blog_title, blog_meta_desc, blog_tags, blog_categories)
+        tuple: (blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug)
     """
-    status.update(label="🔍 Generating title, meta description, tags, and categories...")
+    status.update(label="🔍 Generating title, meta description, tags, categories, hashtags, and slug...")
     try:
-        blog_title, blog_meta_desc, blog_tags, blog_categories = asyncio.run(blog_metadata(blog_markdown_str))
+        # Get all 6 metadata values from blog_metadata
+        blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug = asyncio.run(blog_metadata(blog_markdown_str))
         status.update(label="✅ Generated blog metadata successfully")
-        return blog_title, blog_meta_desc, blog_tags, blog_categories
+        return blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug
     except Exception as err:
         st.error(f"Failed to get blog metadata: {err}")
         logger.error(f"Failed to get blog metadata: {err}")
         status.update(label="❌ Failed to get blog metadata", state="error")
-        return None, None, None, None
+        return None, None, None, None, None, None
     
 
-def generate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, status):
+def generate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, status, blog_tags=None):
     """
     Generate a featured image for the blog.
     
@@ -308,6 +296,7 @@ def generate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, status):
         blog_meta_desc (str): Blog meta description
         blog_markdown_str (str): Blog content
         status: Streamlit status object
+        blog_tags (list, optional): Blog tags to use for image prompt enhancement
         
     Returns:
         str: Path to the generated image or None if generation failed
@@ -337,8 +326,17 @@ def generate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, status):
         logger.info(f"Generating image with prompt: {text_to_image}")
         status.update(label=f"🖼️ Creating image with prompt: \"{text_to_image[:50]}...\"")
         
-        # Attempt image generation
-        generated_image_filepath = generate_image(text_to_image)
+        # Extract blog tags if available
+        blog_tags_list = blog_tags if isinstance(blog_tags, list) else []
+        
+        # Attempt image generation with all available parameters
+        generated_image_filepath = generate_image(
+            user_prompt=text_to_image,
+            title=blog_title,
+            description=blog_meta_desc,
+            tags=blog_tags_list,
+            content=blog_markdown_str[:2000]  # Limit content length to avoid too large payloads
+        )
         
         # If first attempt failed, try with a simplified prompt
         if not generated_image_filepath:
@@ -347,7 +345,13 @@ def generate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, status):
             
             # Create a simpler prompt
             simplified_prompt = " ".join(text_to_image.split()[:10])
-            generated_image_filepath = generate_image(simplified_prompt)
+            generated_image_filepath = generate_image(
+                user_prompt=simplified_prompt,
+                title=blog_title,
+                description=blog_meta_desc,
+                tags=blog_tags_list,
+                content=blog_markdown_str[:1000]  # Use even shorter content for the retry
+            )
         
         if generated_image_filepath:
             status.update(label="✅ Successfully generated featured image")
@@ -363,7 +367,7 @@ def generate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, status):
         return None
 
 
-def regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str):
+def regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, blog_tags=None):
     """
     Regenerate a blog image on demand.
     
@@ -371,6 +375,7 @@ def regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str):
         blog_title (str): Blog title
         blog_meta_desc (str): Blog meta description
         blog_markdown_str (str): Blog content
+        blog_tags (list, optional): Blog tags to use for image prompt enhancement
         
     Returns:
         str: Path to the generated image or None if generation failed
@@ -390,8 +395,17 @@ def regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str):
                 
             status.update(label=f"🖼️ Generating new image with prompt: \"{prompt}\"")
             
-            # Generate the image
-            generated_image_filepath = generate_image(prompt)
+            # Extract any tags if available - will be passed as empty list otherwise
+            blog_tags_list = blog_tags if isinstance(blog_tags, list) else []
+            
+            # Generate the image with all parameters
+            generated_image_filepath = generate_image(
+                user_prompt=prompt,
+                title=blog_title,
+                description=blog_meta_desc,
+                tags=blog_tags_list,
+                content=blog_markdown_str[:2000]  # Limit content length to avoid too large payloads
+            )
             
             if generated_image_filepath:
                 status.update(label="✅ Successfully generated new image", state="complete")
@@ -407,7 +421,7 @@ def regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str):
             return None
 
 
-def save_blog_content(blog_markdown_str, blog_title, blog_meta_desc, blog_tags, blog_categories, generated_image_filepath, status):
+def save_blog_content(blog_markdown_str, blog_title, blog_meta_desc, blog_tags, blog_categories, generated_image_filepath, status, blog_hashtags=None, blog_slug=None):
     """
     Save the blog content to a file.
     
@@ -419,6 +433,8 @@ def save_blog_content(blog_markdown_str, blog_title, blog_meta_desc, blog_tags,
         blog_categories (list): Blog categories
         generated_image_filepath (str): Path to the generated image
         status: Streamlit status object
+        blog_hashtags (str, optional): Social media hashtags
+        blog_slug (str, optional): SEO-friendly URL slug
         
     Returns:
         str: Path to the saved file or None if saving failed
@@ -632,51 +648,172 @@ def write_blog_from_keywords(search_keywords, url=None, search_params=None, blog
         with st.status("Enhancing content...", expanded=True) as status:
             # Generate metadata
             status.update(label="🏷️ Generating SEO metadata (title, description, tags)...")
-            blog_title, blog_meta_desc, blog_tags, blog_categories = generate_blog_metadata(
+            blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug = generate_blog_metadata(
                 blog_markdown_str, search_keywords, status
             )
             
+            # Check if there are updated values in session state
+            if 'blog_title' in st.session_state:
+                blog_title = st.session_state.blog_title
+                status.update(label=f"✅ Using refined title: \"{blog_title}\"")
+                
+            if 'blog_meta_desc' in st.session_state:
+                blog_meta_desc = st.session_state.blog_meta_desc
+                status.update(label=f"✅ Using refined meta description")
+            
             if blog_title and blog_meta_desc:
                 status.update(label=f"✅ Generated metadata: \"{blog_title}\"")
                 
                 # Generate featured image
                 status.update(label="🖼️ Creating featured image...")
                 generated_image_filepath = generate_blog_image(
-                    blog_title, blog_meta_desc, blog_markdown_str, status
+                    blog_title, blog_meta_desc, blog_markdown_str, status, blog_tags
                 )
                 
                 # Save blog content to file
                 status.update(label="💾 Saving blog content...")
                 saved_blog_to_file = save_blog_content(
                     blog_markdown_str, blog_title, blog_meta_desc, blog_tags, 
-                    blog_categories, generated_image_filepath, status
+                    blog_categories, generated_image_filepath, status, blog_hashtags, blog_slug
                 )
                 
                 status.update(label="✅ Content enhancement complete", state="complete")
             else:
                 status.update(label="⚠️ Metadata generation had issues, using simplified format", state="warning")
-    
-    # STEP 4: Final presentation
-    update_progress(4, 5, "Preparing final blog presentation")
-    
-    # Now display the final blog content
-    with final_content_placeholder.container():
-        st.markdown("---")
-        st.header("📝 Generated Blog Content")
-        
-        # Display metadata
-        if blog_title:
-            st.title(blog_title)
-        
-        if blog_meta_desc:
-            st.markdown(f"*{blog_meta_desc}*")
             
-        if blog_tags:
-            st.markdown(f"**Tags:** {', '.join(blog_tags)}")
+            # Add buttons in columns for refining metadata
+            col1, col2 = st.columns(2)
+            with col1:
+                refine_title_button = st.button("🔄 Refine Blog Title", use_container_width=True)
+            with col2:
+                refine_meta_button = st.button("🔄 Refine Meta Description", use_container_width=True)
             
-        if blog_categories:
-            st.markdown(f"**Categories:** {', '.join(blog_categories)}")
+            # Add a row for structured data
+            st.markdown("---")
+            structured_data_col1, structured_data_col2 = st.columns([3, 1])
             
+            with structured_data_col1:
+                # Educational popover explaining why rich snippets are important
+                with st.expander("ℹ️ Why Rich Snippets Are Important for SEO"):
+                    st.markdown("""
+                    ### Rich Snippets: Boosting Your SEO and Click-Through Rates
+                    
+                    **What are Rich Snippets?**
+                    
+                    Rich snippets are enhanced search results that display additional information directly in search engine results pages (SERPs). They're created using structured data markup (JSON-LD) that helps search engines understand your content better.
+                    
+                    **Why are they important?**
+                    
+                    1. **Increased Visibility**: Rich snippets stand out in search results with stars, images, and additional information
+                    
+                    2. **Higher Click-Through Rates (CTR)**: Studies show rich snippets can increase CTR by 30-150%
+                    
+                    3. **Improved SEO**: They help search engines understand your content better, potentially improving rankings
+                    
+                    4. **Enhanced User Experience**: Users can see key information before clicking, leading to more qualified traffic
+                    
+                    5. **Mobile-Friendly**: Rich snippets are especially effective on mobile searches
+                    
+                    **Common types of rich snippets include:**
+                    - Articles/Blogs (with author, date, image)
+                    - Products (with ratings, price, availability)
+                    - Recipes (with cooking time, ratings, calories)
+                    - Events (with date, location, ticket info)
+                    - Local Business (with address, hours, ratings)
+                    
+                    Adding structured data to your content is a powerful SEO technique that requires minimal effort but provides significant benefits.
+                    """)
+            
+            with structured_data_col2:
+                # Button to generate rich snippet
+                generate_snippet_button = st.button("📊 Generate Rich Snippet", use_container_width=True)
+            
+            # Dialog for generating structured data
+            if generate_snippet_button:
+                with st.expander("Structured Data Generation Tool", expanded=True):
+                    st.subheader("Generate Structured Data (Rich Snippets)")
+                    
+                    # Simplified blog URL input
+                    blog_url = st.text_input(
+                        "Blog URL:",
+                        placeholder="https://yourblog.com/your-article",
+                        help="Enter the URL where this blog will be published"
+                    )
+                    
+                    # Auto-fill content type to "Article" since we're working with a blog
+                    content_type = "Article"
+                    st.info(f"Content Type: {content_type} (Auto-selected for blog content)")
+                    
+                    # Create details dictionary with blog metadata
+                    today = datetime.now().strftime("%Y-%m-%d")
+                    
+                    # Form for additional article details
+                    with st.form(key="structured_data_form"):
+                        st.markdown("#### Article Details")
+                        
+                        # Pre-fill with blog title and other metadata
+                        article_title = st.text_input("Headline:", value=blog_title if blog_title else "")
+                        article_author = st.text_input("Author:", value="")
+                        article_date = st.date_input("Date Published:", value=datetime.now())
+                        article_keywords = st.text_input("Keywords:", value=blog_tags if blog_tags else "")
+                        
+                        submit_structured_data = st.form_submit_button("Generate JSON-LD")
+                    
+                    if submit_structured_data:
+                        if not blog_url:
+                            st.error("Please enter a blog URL to generate structured data.")
+                        else:
+                            # Create details dictionary
+                            details = {
+                                "Headline": article_title,
+                                "Author": article_author,
+                                "Date Published": article_date,
+                                "Keywords": article_keywords
+                            }
+                            
+                            # Call the imported ai_structured_data function or recreate its functionality
+                            with st.spinner("Generating structured data..."):
+                                # Import and use the function from the module directly
+                                from ..ai_seo_tools.seo_structured_data import generate_json_data
+                                
+                                # Generate the structured data
+                                structured_data = generate_json_data(content_type, details, blog_url)
+                                
+                                if structured_data:
+                                    st.success("✅ Structured data generated successfully!")
+                                    st.markdown("### Generated JSON-LD Code")
+                                    st.code(structured_data, language="json")
+                                    
+                                    # Download button
+                                    st.download_button(
+                                        label="📥 Download JSON-LD",
+                                        data=structured_data,
+                                        file_name=f"{content_type}_structured_data.json",
+                                        mime="application/json",
+                                    )
+                                    
+                                    # Implementation instructions
+                                    with st.expander("How to Implement This Code"):
+                                        st.markdown("""
+                                        ### Adding this JSON-LD to your website:
+                                        
+                                        1. **Copy the generated JSON-LD code** above
+                                        
+                                        2. **Add it to the `<head>` section of your HTML** like this:
+                                        ```html
+                                        <script type="application/ld+json">
+                                        [PASTE YOUR JSON-LD CODE HERE]
+                                        </script>
+                                        ```
+                                        
+                                        3. **Verify the implementation** using Google's Rich Results Test tool:
+                                        [https://search.google.com/test/rich-results](https://search.google.com/test/rich-results)
+                                        
+                                        4. **Monitor your search appearance** in Google Search Console
+                                        """)
+                                else:
+                                    st.error("Failed to generate structured data. Please check your inputs and try again.")
+
         # Image section with regeneration option
         st.subheader("🖼️ Featured Image")
         image_container = st.container()
@@ -688,14 +825,14 @@ def write_blog_from_keywords(search_keywords, url=None, search_params=None, blog
                 
                 # Add regenerate button
                 if st.button("🔄 Regenerate Image", key="regenerate_image"):
-                    new_image_path = regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str)
+                    new_image_path = regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, blog_tags)
                     if new_image_path:
                         generated_image_filepath = new_image_path
                         st.rerun()  # Refresh the page to show the new image
             else:
                 st.info("No featured image was generated. Click below to generate one.")
                 if st.button("🖼️ Generate Image", key="generate_image"):
-                    new_image_path = regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str)
+                    new_image_path = regenerate_blog_image(blog_title, blog_meta_desc, blog_markdown_str, blog_tags)
                     if new_image_path:
                         generated_image_filepath = new_image_path
                         st.rerun()  # Refresh the page to show the new image
@@ -718,6 +855,303 @@ def write_blog_from_keywords(search_keywords, url=None, search_params=None, blog
             if generate_audio_button:
                 generate_audio_version(blog_markdown_str)
     
+    # STEP 4: Final presentation
+    update_progress(4, 5, "Preparing final blog presentation")
+    
+    # Now display the final blog content
+    with final_content_placeholder.container():
+        st.markdown("---")
+        # Display tabular data of metadata
+        st.subheader("🏷️ Metadata")
+        metadata_container = st.container()
+        with metadata_container:
+            st.table({
+                "Metadata": ["Blog Title", "Meta Description", "Tags", "Categories", "Hashtags", "Slug"],
+                "Value": [blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug]
+            })
+
+            # Add buttons in columns for refining metadata
+            col1, col2 = st.columns(2)
+            with col1:
+                refine_title_button = st.button("🔄 Refine Blog Title", use_container_width=True)
+            with col2:
+                refine_meta_button = st.button("🔄 Refine Meta Description", use_container_width=True)
+            
+            # Add a row for structured data with a "Generate Rich Snippet" button
+            st.markdown("---")
+            st.markdown("### Get Structured Data")
+            
+            structured_data_col1, structured_data_col2 = st.columns([3, 1])
+            
+            with structured_data_col1:
+                # Educational popover explaining why rich snippets are important
+                with st.expander("ℹ️ Why Rich Snippets Are Important for SEO"):
+                    st.markdown("""
+                    ### Rich Snippets: Boosting Your SEO and Click-Through Rates
+                    
+                    **What are Rich Snippets?**
+                    
+                    Rich snippets are enhanced search results that display additional information directly in search engine results pages (SERPs). They're created using structured data markup (JSON-LD) that helps search engines understand your content better.
+                    
+                    **Why are they important?**
+                    
+                    1. **Increased Visibility**: Rich snippets stand out in search results with stars, images, and additional information
+                    
+                    2. **Higher Click-Through Rates (CTR)**: Studies show rich snippets can increase CTR by 30-150%
+                    
+                    3. **Improved SEO**: They help search engines understand your content better, potentially improving rankings
+                    
+                    4. **Enhanced User Experience**: Users can see key information before clicking, leading to more qualified traffic
+                    
+                    5. **Mobile-Friendly**: Rich snippets are especially effective on mobile searches
+                    
+                    **Common types of rich snippets include:**
+                    - Articles/Blogs (with author, date, image)
+                    - Products (with ratings, price, availability)
+                    - Recipes (with cooking time, ratings, calories)
+                    - Events (with date, location, ticket info)
+                    - Local Business (with address, hours, ratings)
+                    
+                    Adding structured data to your content is a powerful SEO technique that requires minimal effort but provides significant benefits.
+                    """)
+            
+            with structured_data_col2:
+                # Button to generate rich snippet
+                generate_snippet_button = st.button("📊 Generate Rich Snippet", use_container_width=True)
+            
+            # Dialog for generating structured data
+            if generate_snippet_button:
+                with st.expander("Structured Data Generation Tool", expanded=True):
+                    st.subheader("Generate Structured Data (Rich Snippets)")
+                    
+                    # Simplified blog URL input
+                    blog_url = st.text_input(
+                        "Blog URL:",
+                        placeholder="https://yourblog.com/your-article",
+                        help="Enter the URL where this blog will be published"
+                    )
+                    
+                    # Auto-fill content type to "Article" since we're working with a blog
+                    content_type = "Article"
+                    st.info(f"Content Type: {content_type} (Auto-selected for blog content)")
+                    
+                    # Form for additional article details
+                    with st.form(key="structured_data_form"):
+                        st.markdown("#### Article Details")
+                        
+                        # Pre-fill with blog title and other metadata
+                        article_title = st.text_input("Headline:", value=blog_title if blog_title else "")
+                        article_author = st.text_input("Author:", value="")
+                        article_date = st.date_input("Date Published:", value=datetime.now())
+                        article_keywords = st.text_input("Keywords:", value=blog_tags if blog_tags else "")
+                        
+                        submit_structured_data = st.form_submit_button("Generate JSON-LD")
+                    
+                    if submit_structured_data:
+                        if not blog_url:
+                            st.error("Please enter a blog URL to generate structured data.")
+                        else:
+                            # Create details dictionary
+                            details = {
+                                "Headline": article_title,
+                                "Author": article_author,
+                                "Date Published": article_date,
+                                "Keywords": article_keywords
+                            }
+                            
+                            # Call the imported ai_structured_data function or recreate its functionality
+                            with st.spinner("Generating structured data..."):
+                                # Import and use the function from the module directly
+                                from ..ai_seo_tools.seo_structured_data import generate_json_data
+                                
+                                # Generate the structured data
+                                structured_data = generate_json_data(content_type, details, blog_url)
+                                
+                                if structured_data:
+                                    st.success("✅ Structured data generated successfully!")
+                                    st.markdown("### Generated JSON-LD Code")
+                                    st.code(structured_data, language="json")
+                                    
+                                    # Download button
+                                    st.download_button(
+                                        label="📥 Download JSON-LD",
+                                        data=structured_data,
+                                        file_name=f"{content_type}_structured_data.json",
+                                        mime="application/json",
+                                    )
+                                    
+                                    # Implementation instructions
+                                    with st.expander("How to Implement This Code"):
+                                        st.markdown("""
+                                        ### Adding this JSON-LD to your website:
+                                        
+                                        1. **Copy the generated JSON-LD code** above
+                                        
+                                        2. **Add it to the `<head>` section of your HTML** like this:
+                                        ```html
+                                        <script type="application/ld+json">
+                                        [PASTE YOUR JSON-LD CODE HERE]
+                                        </script>
+                                        ```
+                                        
+                                        3. **Verify the implementation** using Google's Rich Results Test tool:
+                                        [https://search.google.com/test/rich-results](https://search.google.com/test/rich-results)
+                                        
+                                        4. **Monitor your search appearance** in Google Search Console
+                                        """)
+                                else:
+                                    st.error("Failed to generate structured data. Please check your inputs and try again.")
+
+            # Dialog for refining blog title
+            if refine_title_button:
+                with st.expander("Blog Title Refinement Tool", expanded=True):
+                    st.subheader("Refine Your Blog Title")
+                    
+                    # Store the current title in session state for later reference
+                    if 'current_title' not in st.session_state:
+                        st.session_state.current_title = blog_title
+                    
+                    # Extract keywords from tags and content
+                    keywords_from_tags = blog_tags if blog_tags else ""
+                    blog_content_sample = blog_markdown_str[:3000] if blog_markdown_str else ""
+                    
+                    # Title generation form
+                    with st.form(key="title_form"):
+                        st.markdown("#### Provide information to generate new title suggestions")
+                        title_keywords = st.text_input(
+                            "Main Keywords:", 
+                            value=keywords_from_tags,
+                            help="Enter main keywords separated by commas"
+                        )
+                        
+                        title_type = st.selectbox(
+                            "Blog Type:", 
+                            options=['General', 'How-to Guides', 'Tutorials', 'Listicles', 'Newsworthy Posts', 'FAQs', 'Checklists/Cheat Sheets'],
+                            index=0
+                        )
+                        
+                        intent_type = st.selectbox(
+                            "Search Intent:", 
+                            options=['Informational Intent', 'Commercial Intent', 'Transactional Intent', 'Navigational Intent'],
+                            index=0
+                        )
+                        
+                        language = st.selectbox(
+                            "Language:", 
+                            options=["English", "Spanish", "French", "German", "Chinese", "Japanese", "Other"],
+                            index=0
+                        )
+                        
+                        if language == "Other":
+                            language = st.text_input("Specify Language:", placeholder="e.g., Italian, Dutch")
+                        
+                        submit_title = st.form_submit_button("Generate Title Suggestions")
+                    
+                    if submit_title:
+                        with st.spinner("Generating title suggestions..."):
+                            # Use the imported generate_blog_titles function
+                            title_suggestions = generate_blog_titles(
+                                title_keywords, 
+                                blog_content_sample, 
+                                title_type, 
+                                intent_type, 
+                                language
+                            )
+                            
+                            if title_suggestions:
+                                st.success("✅ Title suggestions generated!")
+                                st.markdown("### Title Suggestions")
+                                st.markdown(title_suggestions)
+                                
+                                # Allow selecting a title
+                                st.markdown("#### Select or enter a new title")
+                                new_title = st.text_input("New Blog Title", value=st.session_state.current_title)
+                                
+                                if st.button("Apply New Title"):
+                                    # Store the new title in the session state
+                                    st.session_state.blog_title = new_title
+                                    st.success(f"✅ Title updated to: {new_title}")
+                                    # Return to main page with updated title
+                                    st.experimental_rerun()
+                            else:
+                                st.error("Failed to generate title suggestions.")
+
+            # Dialog for refining meta description
+            if refine_meta_button:
+                with st.expander("Meta Description Refinement Tool", expanded=True):
+                    st.subheader("Refine Your Meta Description")
+                    
+                    # Store the current meta description in session state
+                    if 'current_meta_desc' not in st.session_state:
+                        st.session_state.current_meta_desc = blog_meta_desc
+                    
+                    # Extract keywords from tags and content
+                    keywords_from_tags = blog_tags if blog_tags else ""
+                    
+                    # Meta description generation form
+                    with st.form(key="meta_desc_form"):
+                        st.markdown("#### Provide information to generate new meta description suggestions")
+                        meta_keywords = st.text_input(
+                            "Target Keywords:", 
+                            value=keywords_from_tags,
+                            help="Enter target keywords separated by commas"
+                        )
+                        
+                        tone_options = ["General", "Informative", "Engaging", "Humorous", "Intriguing", "Playful"]
+                        tone = st.selectbox(
+                            "Desired Tone:", 
+                            options=tone_options,
+                            index=0
+                        )
+                        
+                        search_type = st.selectbox(
+                            "Search Intent:", 
+                            options=['Informational Intent', 'Commercial Intent', 'Transactional Intent', 'Navigational Intent'],
+                            index=0
+                        )
+                        
+                        language_options = ["English", "Spanish", "French", "German", "Other"]
+                        language_choice = st.selectbox(
+                            "Preferred Language:", 
+                            options=language_options,
+                            index=0
+                        )
+                        
+                        if language_choice == "Other":
+                            language = st.text_input("Specify Language:", placeholder="e.g., Italian, Chinese")
+                        else:
+                            language = language_choice
+                        
+                        submit_meta = st.form_submit_button("Generate Meta Description Suggestions")
+                    
+                    if submit_meta:
+                        with st.spinner("Generating meta description suggestions..."):
+                            # Use the imported generate_blog_metadesc function
+                            meta_suggestions = generate_blog_metadesc(
+                                meta_keywords,
+                                tone,
+                                search_type,
+                                language
+                            )
+                            
+                            if meta_suggestions:
+                                st.success("✅ Meta description suggestions generated!")
+                                st.markdown("### Meta Description Suggestions")
+                                st.markdown(meta_suggestions)
+                                
+                                # Allow selecting a meta description
+                                st.markdown("#### Select or enter a new meta description")
+                                new_meta_desc = st.text_area("New Meta Description", value=st.session_state.current_meta_desc)
+                                
+                                if st.button("Apply New Meta Description"):
+                                    # Store the new meta description in the session state
+                                    st.session_state.blog_meta_desc = new_meta_desc
+                                    st.success(f"✅ Meta description updated!")
+                                    # Return to main page with updated meta description
+                                    st.experimental_rerun()
+                            else:
+                                st.error("Failed to generate meta description suggestions.")
+
     # Final progress update
     update_progress(5, 5, "Blog generation complete!")
     
diff --git a/lib/blog_metadata/get_blog_metadata.py b/lib/blog_metadata/get_blog_metadata.py
index d2751c72..b74c1b73 100644
--- a/lib/blog_metadata/get_blog_metadata.py
+++ b/lib/blog_metadata/get_blog_metadata.py
@@ -72,10 +72,10 @@ async def blog_metadata(blog_article):
 
         # Present the result in a table format
         status_container.success("✅ Metadata generation complete")
-        st.table({
-            "Metadata": ["Blog Title", "Meta Description", "Tags", "Categories", "Social Hashtags", "URL Slug"],
-            "Value": [blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug]
-        })
+        #st.table({
+        #    "Metadata": ["Blog Title", "Meta Description", "Tags", "Categories", "Social Hashtags", "URL Slug"],
+        #    "Value": [blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug]
+        #})
 
         return blog_title, blog_meta_desc, blog_tags, blog_categories, blog_hashtags, blog_slug
     
diff --git a/lib/gpt_providers/text_to_image_generation/gen_gemini_images.py b/lib/gpt_providers/text_to_image_generation/gen_gemini_images.py
index bfb6d852..2b60daf2 100644
--- a/lib/gpt_providers/text_to_image_generation/gen_gemini_images.py
+++ b/lib/gpt_providers/text_to_image_generation/gen_gemini_images.py
@@ -190,6 +190,14 @@ def generate_gemini_image(prompt, keywords=None, style=None, focus=None, enhance
     """
     logger.info(f"Generating image with prompt: '{prompt[:100]}...'")
     
+    # Check if the GEMINI_API_KEY is available
+    api_key = os.getenv("GEMINI_API_KEY")
+    if not api_key:
+        error_msg = "GEMINI_API_KEY is missing. Please set it in your environment variables."
+        logger.error(error_msg)
+        st.error(f"🔑 {error_msg}")
+        return None
+    
     # Enhance the prompt if requested
     if enhance_prompt and keywords:
         prompt_generator = AIPromptGenerator()
@@ -209,7 +217,7 @@ def generate_gemini_image(prompt, keywords=None, style=None, focus=None, enhance
     
     while retry_count <= max_retries:
         try:
-            client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
+            client = genai.Client(api_key=api_key)
             contents = (prompt)
 
             logger.info("Sending request to Gemini API")
diff --git a/lib/gpt_providers/text_to_image_generation/main_generate_image_from_prompt.py b/lib/gpt_providers/text_to_image_generation/main_generate_image_from_prompt.py
index a16d9897..4be8560a 100644
--- a/lib/gpt_providers/text_to_image_generation/main_generate_image_from_prompt.py
+++ b/lib/gpt_providers/text_to_image_generation/main_generate_image_from_prompt.py
@@ -27,7 +27,7 @@ from .gen_stabl_diff_img import generate_stable_diffusion_image
 from ..text_generation.main_text_generation import llm_text_gen
 from .gen_gemini_images import generate_gemini_image
 
-def generate_image(user_prompt):
+def generate_image(user_prompt, title=None, description=None, tags=None, content=None):
     """
     The generation API endpoint creates an image based on a text prompt.
 
@@ -49,7 +49,8 @@ def generate_image(user_prompt):
 
     if user_prompt:
         try:
-            img_prompt = generate_img_prompt(user_prompt)
+            # Use enhanced prompt generator with all available parameters
+            img_prompt = generate_enhanced_img_prompt(user_prompt, title, description, tags, content)
             if 'Dalle3' in image_engine:
                 logger.info(f"Calling Dalle3 text-to-image with prompt: {img_prompt}")
                 image_stored_at = generate_dalle3_images(img_prompt)
@@ -85,3 +86,72 @@ def generate_img_prompt(user_prompt):
 
     response = llm_text_gen(prompt)
     return response
+
+
+def generate_enhanced_img_prompt(user_prompt, title=None, description=None, tags=None, content=None):
+    """
+    Given user prompt and additional context (title, description, tags, content),
+    this function generates an enhanced prompt for better image generation.
+    
+    Args:
+        user_prompt (str): Base prompt from the user
+        title (str, optional): Blog title or content title
+        description (str, optional): Blog or content description/summary
+        tags (list, optional): List of tags related to the content
+        content (str, optional): Actual content or excerpt
+        
+    Returns:
+        str: Enhanced prompt for image generation
+    """
+    # Start with the base prompt
+    context_parts = [user_prompt]
+    
+    # Add relevant context if available
+    if title:
+        context_parts.append(f"Title: {title}")
+    
+    if description:
+        context_parts.append(f"Description: {description}")
+    
+    if tags and len(tags) > 0:
+        tag_text = ", ".join(tags[:5])  # Limit to 5 tags to avoid too much noise
+        context_parts.append(f"Tags: {tag_text}")
+    
+    # Create a combined context
+    combined_context = "\n".join(context_parts)
+    
+    # Add some content excerpt if available (limited to avoid token limits)
+    content_excerpt = ""
+    if content:
+        # Just use the first few hundred characters as excerpt
+        content_excerpt = content[:300] + "..." if len(content) > 300 else content
+    
+    # Create the prompt for LLM
+    prompt = f"""
+        As an expert prompt engineer for AI image generation models, create a detailed, creative prompt
+        for generating a high-quality, relevant image based on the following context:
+        
+        {combined_context}
+        
+        Additional content excerpt:
+        {content_excerpt}
+        
+        Your task is to:
+        1. Analyze the context and content to understand the main theme and subject
+        2. Create a rich, detailed prompt for image generation (50-75 words)
+        3. Include specific visual details, art style, mood, lighting, composition
+        4. Make sure the prompt is highly relevant to the original context
+        5. Avoid prohibited content or anything that violates image generation guidelines
+        
+        Reply with ONLY the final prompt. No explanations or other text.
+    """
+    
+    # Generate the enhanced prompt
+    try:
+        enhanced_prompt = llm_text_gen(prompt)
+        logger.info(f"Generated enhanced image prompt: {enhanced_prompt[:100]}...")
+        return enhanced_prompt
+    except Exception as e:
+        logger.error(f"Error generating enhanced prompt: {e}")
+        # Fall back to the simple prompt generation if enhanced fails
+        return generate_img_prompt(user_prompt)
diff --git a/lib/gpt_providers/text_to_image_generation/save_image.py b/lib/gpt_providers/text_to_image_generation/save_image.py
index 4bdd7a10..3aab258c 100644
--- a/lib/gpt_providers/text_to_image_generation/save_image.py
+++ b/lib/gpt_providers/text_to_image_generation/save_image.py
@@ -12,8 +12,16 @@ def save_generated_image(img_generation_response):
     logging.basicConfig(level=logging.INFO)
     logger = logging.getLogger(__name__)
 
+    # Get image save directory with fallback to a local directory
+    image_save_dir = os.getenv('IMG_SAVE_DIR', 'generated_images')
+    
+    # Create the directory if it doesn't exist
+    if not os.path.exists(image_save_dir):
+        logger.info(f"Creating image save directory: {image_save_dir}")
+        os.makedirs(image_save_dir, exist_ok=True)
+
     generated_image_name = f"generated_image_{datetime.datetime.now():%Y-%m-%d-%H-%M-%S}.webp"
-    generated_image_filepath = os.path.join(os.getenv('IMG_SAVE_DIR'), generated_image_name)
+    generated_image_filepath = os.path.join(image_save_dir, generated_image_name)
 
     try:
         for i, image in enumerate(img_generation_response["artifacts"]):
@@ -22,6 +30,9 @@ def save_generated_image(img_generation_response):
     except requests.exceptions.RequestException as e:
         logger.error(f"Failed to get generated image content: {e}")
         return None
+    except Exception as e:
+        logger.error(f"Error saving image: {e}")
+        return None
 
     logger.info(f"Saved image at path: {generated_image_filepath}")