Update app.py

app.py

@@ -1,63 +1,7 @@
-# -*- coding: utf-8 -*-
-"""Seo_Blog_Finale.ipynb
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1QI2D7IKD5MNQKverCCzA9-Mq_pkxD4PX
-"""
-
-# ======================== INSTALL DEPENDENCIES ========================
-# Install required packages
-def install_package(package):
-    try:
-        import subprocess
-        import sys
-        subprocess.check_call([sys.executable, "-m", "pip", "install", package])
-        print(f"✅ {package} installed successfully")
-    except:
-        print(f"⚠️ Could not install {package}")
-
-packages = [
-    "openai", "requests", "beautifulsoup4", "pandas", "gradio", "openpyxl", "spacy", "python-docx", "google-search-results"
-]
-for package in packages:
-    try:
-        if package == "openai":
-            from openai import OpenAI
-        elif package == "requests":
-            import requests
-        elif package == "beautifulsoup4":
-            import bs4
-        elif package == "pandas":
-            import pandas
-        elif package == "gradio":
-            import gradio
-        elif package == "openpyxl":
-            import openpyxl
-        elif package == "spacy":
-            import spacy
-        elif package == "python-docx":
-            from docx import Document
-        elif package == "google-search-results":
-            from serpapi import GoogleSearch
-    except ImportError:
-        install_package(package)
-
-# Download spaCy model if needed
-try:
-    import spacy
-    nlp = spacy.load("en_core_web_sm")
-except:
-    print("Installing spaCy English model...")
-    import subprocess
-    import sys
-    subprocess.check_call([sys.executable, "-m", "spacy", "download", "en_core_web_sm"])
-    nlp = spacy.load("en_core_web_sm")
-
+# MODIFIED: Removed all runtime installation code. Dependencies are now in requirements.txt
 import subprocess
 import sys
-import os # MODIFIED: Ensure 'os' is imported
+import os
 import re
 import time
 import json
@@ -77,6 +21,10 @@ from docx.oxml import OxmlElement
 from docx.oxml.ns import qn
 from itertools import cycle
 from serpapi import GoogleSearch
+import spacy # MODIFIED: Directly import spacy
+
+# MODIFIED: Load the spacy model directly, as it's installed via requirements.txt
+nlp = spacy.load("en_core_web_sm")
 
 # ======================== CONFIGURE OPENAI & SERPAPI ========================
 # MODIFIED: Get API keys from Hugging Face Secrets and add error handling
@@ -92,7 +40,6 @@ if not serpapi_key:
 client = OpenAI(api_key=openai_api_key)
 SERPAPI_KEY = serpapi_key
 
-
 # ======================== BLOG CONTENT TYPES ========================
 BLOG_TYPES = {
     "How-To Guide 📚": "step-by-step tutorials",
@@ -141,6 +88,7 @@ Now, generate the FAQs for the current blog topic following these rules and the
 """
 
 BLOG_STRUCTURES = {
+    # ... (Your entire BLOG_STRUCTURES dictionary remains here, unchanged)
     "How-To Guide": [
         ("Intro Hook", "Problem Hook", 40, 60, "Hook the reader by presenting a common, relatable problem they're struggling with. Frame it as a challenge that many in their position face."),
         ("Intro Hook", "Promise the Outcome", 20, 30, "In one single, powerful sentence, promise the specific, tangible skill the reader will have after finishing this guide. Be extremely concise. Example: 'By the end of this guide, you will be able to build a high-performing global team from scratch.'"),
@@ -320,6 +268,7 @@ BLOG_STRUCTURES = {
 }
 
 # ======================== RESEARCH FUNCTIONS ========================
+# ... (All your functions from search_web down to the line before WordDocumentGenerator remain here, unchanged)
 def search_web(query): # This is now a fallback
     try:
         search_query = quote_plus(query)
@@ -776,7 +725,7 @@ def format_faq_content(text):
             answer = line[2:].strip()
             qa_pairs.append(f"Q. {current_q}\nA. {answer}")
             current_q = None  # Reset to find the next question
-
+    
     return "\n\n".join(qa_pairs)
 
 
@@ -906,17 +855,17 @@ class WordDocumentGenerator:
             for _, item_row in item_sections.iterrows():
                 persona = next(self.ai_personas)
                 yield f"    -> Analyzing Item: '{item_row['Section Content'][:40]}...' (as {persona.split(',')[0]})"
-
+                
                 content = item_row['Section Content']
                 # Extract the actual generated title from the first line of the content
                 generated_title = content.split('\n')[0].strip() if content else 'Untitled Item'
-
+                
                 # Get the analysis for 'ideal_for' and 'business_benefit' from the AI
                 details = self._extract_item_details(content, persona)
-
+                
                 # OVERRIDE the name with the actual generated title to ensure consistency
                 details['name'] = generated_title
-
+                
                 listicle_items_data.append(details)
 
         toc_items = []
@@ -975,11 +924,11 @@ class WordDocumentGenerator:
                     continue
 
                 cleaned_content = clean_blog_content(section_content)
-
+                
                 # --- MODIFIED: Apply special FAQ formatting function ---
                 if section_name == "FAQs":
                     cleaned_content = format_faq_content(cleaned_content)
-
+                
                 if section_name == "At-a-Glance Matrix" and "Comparison" in content_type:
                     header, data = parse_comparison_table(cleaned_content)
                     if data: self.add_comparison_table(header, data); self.doc.add_paragraph(); continue
@@ -1044,6 +993,7 @@ def process_excel_to_word(excel_file_path):
 
 # ======================== GRADIO INTERFACE ========================
 def create_interface():
+    # ... (Your entire Gradio interface layout remains here, unchanged)
     generator = BlogGenerator()
     with gr.Blocks(title="🎯 Digiworks Unified Blog Generator", theme=gr.themes.Soft()) as interface:
         gr.HTML("""<div style='text-align: center; padding: 25px; background: linear-gradient(135deg, #1a365d 0%, #2d3748 100%); color: white; margin-bottom: 25px; border-radius: 15px;'><h1 style='margin: 0; font-size: 2.5em; font-weight: 900;'>🎯 Digiworks Unified Blog Generator</h1><p style='margin: 15px 0 0 0; font-size: 1.2em;'>Idea Generation → Blog Post Creation → Word Document Formatting</p></div>""")
@@ -1098,134 +1048,135 @@ def create_interface():
                         download_word_btn = gr.File(label="📥 Download Formatted Word Document", visible=False)
                         gr.HTML("""<div style='background: #065f46; color: white; padding: 15px; border-radius: 8px; text-align: center; margin-left: 15px; border: 1px solid #10b981;'><strong style='color: #6ee7b7;'>💡 WordPress Tip:</strong><span style='color: white;'>Copy sections directly from Word to WordPress editor!</span></div>""")
 
-        # --- HANDLER FUNCTIONS (MODIFIED for Incremental Save) ---
-        def toggle_content_type(mode): return gr.update(visible=(mode == "Single Type"))
-        def handle_idea_generation(mode, content_type_val, num_topics_val):
-            try:
-                if mode == "Single Type": result, df, status = generate_blog_topics(content_type_val, num_topics_val)
-                else: result, df, status = generate_all_types(num_topics_val)
-                download_file, download_visible = None, False
-                if not df.empty:
-                    timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
-                    filename = f"digiworks_blog_ideas_{timestamp}.xlsx"
-                    temp_path = os.path.join(tempfile.gettempdir(), filename)
-                    with pd.ExcelWriter(temp_path, engine='openpyxl') as writer: df.to_excel(writer, sheet_name='Blog Ideas', index=False)
-                    download_file, download_visible = temp_path, True
-                return status, result, df, gr.update(value=download_file, visible=download_visible)
-            except Exception as e: return f"❌ Error: {str(e)}", f"❌ Generation failed: {str(e)}", pd.DataFrame(), gr.update(visible=False)
-        def load_excel_and_create_checklist(file_path):
-            if not file_path: return gr.update(choices=[], value=[]), pd.DataFrame(), "Please upload an Excel file"
-            try:
-                df = pd.read_excel(file_path)
-                required_cols = ['Content Type', 'Headline']
-                if missing_cols := [col for col in required_cols if col not in df.columns]: return gr.update(choices=[], value=[]), pd.DataFrame(), f"Missing columns: {', '.join(missing_cols)}"
-                choices = []
-                for i, row in df.iterrows():
-                    content_type = row.get('Content Type', '').replace(' 📚', '').replace(' 📋', '').replace(' ⚖️', '').replace(' 📈', '').replace(' 📊', '').replace(' 💡', '')
-                    headline = row.get('Headline', '')[:60]; keywords = row.get('Keywords', '')[:50]
-                    choices.append(f"#{i+1} [{content_type}] {headline}... | Keywords: {keywords}...")
-                return gr.update(choices=choices, value=choices), df, f"✅ Loaded {len(df)} topics. Select topics to generate blog posts."
-            except Exception as e: return gr.update(choices=[], value=[]), pd.DataFrame(), f"❌ Error: {str(e)}"
-        def reset_topic_counter():
-            generator.reset_counter()
-            return "🔄 Topic counter reset to 0. Next generation will start from Topic #1."
-
-        def generate_selected_posts(file_path, selected_choices, df):
-            if not file_path or not selected_choices:
-                yield "Please upload an Excel file and select at least one topic to generate.", pd.DataFrame(), gr.update(visible=False)
-                return
-            all_sections_data, status_log = [], ["🚀 Starting blog post generation..."]
-            latest_file_path = None
-            yield "\n".join(status_log), pd.DataFrame(), gr.update(value=None, visible=False)
-            try:
-                for topic_counter, choice in enumerate(selected_choices, 1):
-                    choice_index = int(choice.split('#')[1].split(' ')[0]) - 1
-                    if choice_index < len(df):
-                        topic_data = df.iloc[choice_index].to_dict()
-                        generation_iterator = generator.generate_blog_from_topic_data(topic_data, topic_index=topic_counter)
-
-                        topic_sections = []
-                        for update_type, update_value, *rest in generation_iterator:
-                            if update_type == 'status':
-                                message = update_value
-                                status_log.append(message)
-                                yield "\n".join(status_log), pd.DataFrame(all_sections_data), gr.update(value=latest_file_path, visible=bool(latest_file_path))
-                            elif update_type == 'result':
-                                sections, msg = update_value, rest[0]
-                                if sections:
-                                    topic_sections.extend(sections)
-                                status_log.append(msg)
-
-                        if topic_sections:
-                            all_sections_data.extend(topic_sections)
-                            intermediate_df = pd.DataFrame(all_sections_data)
-                            intermediate_file = create_excel_export(all_sections_data)
-                            latest_file_path = intermediate_file
-                            status_log.append(f"📦 Intermediate file for Topic #{topic_counter} ready.")
-                            yield "\n".join(status_log), intermediate_df, gr.update(value=latest_file_path, visible=True)
-
-                if all_sections_data:
-                    final_df = pd.DataFrame(all_sections_data)
-                    total_topics, total_sections = len(selected_choices), len(all_sections_data)
-                    successful_sections = len([s for s in all_sections_data if s['Word Count'] > 0])
-                    total_words = sum(s['Word Count'] for s in all_sections_data if s['Word Count'] > 0)
-                    final_status = f"""🎉 ALL TOPICS COMPLETE!\n--------------------\n📊 Generated {total_sections} sections across {total_topics} topics\n✅ Successful sections: {successful_sections}/{total_sections}\n📝 Total words generated: {total_words:,}\n🔢 Topics indexed: 1-{total_topics}\n\nFull Log:\n""" + "\n".join(status_log)
-                    yield final_status, final_df, gr.update(value=latest_file_path, visible=True)
-                else:
-                    yield "❌ No sections were generated.", pd.DataFrame(), gr.update(visible=False)
-            except Exception as e:
-                import traceback
-                tb_str = traceback.format_exc()
-                yield f"❌ An unexpected error occurred: {str(e)}\n\nTraceback:\n{tb_str}", pd.DataFrame(), gr.update(visible=False)
-
-        def process_excel_file(excel_file):
-            if not excel_file: return "Please upload an Excel file", "", gr.update(visible=False)
-            try:
-                df = pd.read_excel(excel_file); preview = "No content preview available"
-                if not df.empty and 'Section Content' in df.columns:
-                    cleaned_sample = clean_blog_content(df.iloc[0]['Section Content'])
-                    preview = cleaned_sample[:500] + "..." if len(cleaned_sample) > 500 else cleaned_sample
-                status = f"✅ Excel loaded: {len(df)} sections found\n📊 Topics: {df['Topic Number'].nunique() if 'Topic Number' in df.columns else 'Unknown'}\n🔄 Ready to generate Word document"
-                return status, preview, gr.update(visible=False)
-            except Exception as e: return f"❌ Error reading Excel: {str(e)}", "", gr.update(visible=False)
-
-        def generate_word_document(excel_file):
-            if not excel_file:
-                yield "Please upload an Excel file.", "", gr.update(visible=False)
-                return
-            status_log = ["🚀 Starting Word document generation..."]
-            yield "\n".join(status_log), "", gr.update(visible=False)
-            try:
-                processing_generator = process_excel_to_word(excel_file)
-                for type, val1, *val2 in processing_generator:
-                    if type == 'status':
-                        status_log.append(val1)
-                        yield "\n".join(status_log), "", gr.update(visible=False)
-                    elif type == 'complete':
-                        word_file_path, result_message = val1, val2[0]
-                        df = pd.read_excel(excel_file)
-                        preview = "Document generated successfully"
-                        if not df.empty and 'Section Content' in df.columns:
-                            cleaned_sample = clean_blog_content(df.iloc[0]['Section Content'])
-                            preview = cleaned_sample[:500] + "..." if len(cleaned_sample) > 500 else cleaned_sample
-                        yield result_message, preview, gr.update(value=word_file_path, visible=True)
-                    elif type == 'error':
-                        yield val1, "", gr.update(visible=False)
-            except Exception as e:
-                import traceback
-                yield f"❌ An unexpected error occurred: {str(e)}\n{traceback.format_exc()}", "", gr.update(visible=False)
-
-        # --- EVENT LISTENERS ---
-        mode_choice.change(fn=toggle_content_type, inputs=[mode_choice], outputs=[content_type])
-        generate_ideas_btn.click(fn=handle_idea_generation, inputs=[mode_choice, content_type, num_topics], outputs=[ideas_status, ideas_results, ideas_df, download_ideas_btn])
-        excel_upload.change(fn=load_excel_and_create_checklist, inputs=[excel_upload], outputs=[topics_checklist, loaded_data, posts_status])
-        reset_counter_btn.click(fn=reset_topic_counter, inputs=[], outputs=[posts_status])
-        generate_posts_btn.click(fn=generate_selected_posts, inputs=[excel_upload, topics_checklist, loaded_data], outputs=[posts_status, posts_dataframe, download_posts_btn])
-        word_excel_input.change(fn=process_excel_file, inputs=[word_excel_input], outputs=[word_status, word_preview, download_word_btn])
-        generate_word_btn.click(fn=generate_word_document, inputs=[word_excel_input], outputs=[word_status, word_preview, download_word_btn])
-        gr.HTML("""<div style='text-align: center; padding: 20px; margin-top: 25px; border-top: 1px solid #e0e0e0;'><p style='color: #666; margin: 0;'>🎯 <strong>Digiworks Unified Blog Generator</strong> | Idea Generation → Blog Post Creation → Word Document Formatting<br><small>Perfect for content teams and marketers</small></p></div>""")
-
-        return interface
+    # --- HANDLER FUNCTIONS (MODIFIED for Incremental Save) ---
+    def toggle_content_type(mode): return gr.update(visible=(mode == "Single Type"))
+    def handle_idea_generation(mode, content_type_val, num_topics_val):
+        try:
+            if mode == "Single Type": result, df, status = generate_blog_topics(content_type_val, num_topics_val)
+            else: result, df, status = generate_all_types(num_topics_val)
+            download_file, download_visible = None, False
+            if not df.empty:
+                timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
+                filename = f"digiworks_blog_ideas_{timestamp}.xlsx"
+                temp_path = os.path.join(tempfile.gettempdir(), filename)
+                with pd.ExcelWriter(temp_path, engine='openpyxl') as writer: df.to_excel(writer, sheet_name='Blog Ideas', index=False)
+                download_file, download_visible = temp_path, True
+            return status, result, df, gr.update(value=download_file, visible=download_visible)
+        except Exception as e: return f"❌ Error: {str(e)}", f"❌ Generation failed: {str(e)}", pd.DataFrame(), gr.update(visible=False)
+    def load_excel_and_create_checklist(file_path):
+        if not file_path: return gr.update(choices=[], value=[]), pd.DataFrame(), "Please upload an Excel file"
+        try:
+            df = pd.read_excel(file_path)
+            required_cols = ['Content Type', 'Headline']
+            if missing_cols := [col for col in required_cols if col not in df.columns]: return gr.update(choices=[], value=[]), pd.DataFrame(), f"Missing columns: {', '.join(missing_cols)}"
+            choices = []
+            for i, row in df.iterrows():
+                content_type = row.get('Content Type', '').replace(' 📚', '').replace(' 📋', '').replace(' ⚖️', '').replace(' 📈', '').replace(' 📊', '').replace(' 💡', '')
+                headline = row.get('Headline', '')[:60]; keywords = row.get('Keywords', '')[:50]
+                choices.append(f"#{i+1} [{content_type}] {headline}... | Keywords: {keywords}...")
+            return gr.update(choices=choices, value=choices), df, f"✅ Loaded {len(df)} topics. Select topics to generate blog posts."
+        except Exception as e: return gr.update(choices=[], value=[]), pd.DataFrame(), f"❌ Error: {str(e)}"
+    def reset_topic_counter():
+        generator.reset_counter()
+        return "🔄 Topic counter reset to 0. Next generation will start from Topic #1."
+
+    def generate_selected_posts(file_path, selected_choices, df):
+        if not file_path or not selected_choices:
+            yield "Please upload an Excel file and select at least one topic to generate.", pd.DataFrame(), gr.update(visible=False)
+            return
+        all_sections_data, status_log = [], ["🚀 Starting blog post generation..."]
+        latest_file_path = None
+        yield "\n".join(status_log), pd.DataFrame(), gr.update(value=None, visible=False)
+        try:
+            for topic_counter, choice in enumerate(selected_choices, 1):
+                choice_index = int(choice.split('#')[1].split(' ')[0]) - 1
+                if choice_index < len(df):
+                    topic_data = df.iloc[choice_index].to_dict()
+                    generation_iterator = generator.generate_blog_from_topic_data(topic_data, topic_index=topic_counter)
+
+                    topic_sections = []
+                    for update_type, update_value, *rest in generation_iterator:
+                        if update_type == 'status':
+                            message = update_value
+                            status_log.append(message)
+                            yield "\n".join(status_log), pd.DataFrame(all_sections_data), gr.update(value=latest_file_path, visible=bool(latest_file_path))
+                        elif update_type == 'result':
+                            sections, msg = update_value, rest[0]
+                            if sections:
+                                topic_sections.extend(sections)
+                            status_log.append(msg)
+
+                    if topic_sections:
+                        all_sections_data.extend(topic_sections)
+                        intermediate_df = pd.DataFrame(all_sections_data)
+                        intermediate_file = create_excel_export(all_sections_data)
+                        latest_file_path = intermediate_file
+                        status_log.append(f"📦 Intermediate file for Topic #{topic_counter} ready.")
+                        yield "\n".join(status_log), intermediate_df, gr.update(value=latest_file_path, visible=True)
+
+            if all_sections_data:
+                final_df = pd.DataFrame(all_sections_data)
+                total_topics, total_sections = len(selected_choices), len(all_sections_data)
+                successful_sections = len([s for s in all_sections_data if s['Word Count'] > 0])
+                total_words = sum(s['Word Count'] for s in all_sections_data if s['Word Count'] > 0)
+                final_status = f"""🎉 ALL TOPICS COMPLETE!\n--------------------\n📊 Generated {total_sections} sections across {total_topics} topics\n✅ Successful sections: {successful_sections}/{total_sections}\n📝 Total words generated: {total_words:,}\n🔢 Topics indexed: 1-{total_topics}\n\nFull Log:\n""" + "\n".join(status_log)
+                yield final_status, final_df, gr.update(value=latest_file_path, visible=True)
+            else:
+                yield "❌ No sections were generated.", pd.DataFrame(), gr.update(visible=False)
+        except Exception as e:
+            import traceback
+            tb_str = traceback.format_exc()
+            yield f"❌ An unexpected error occurred: {str(e)}\n\nTraceback:\n{tb_str}", pd.DataFrame(), gr.update(visible=False)
+
+    def process_excel_file(excel_file):
+        if not excel_file: return "Please upload an Excel file", "", gr.update(visible=False)
+        try:
+            df = pd.read_excel(excel_file); preview = "No content preview available"
+            if not df.empty and 'Section Content' in df.columns:
+                cleaned_sample = clean_blog_content(df.iloc[0]['Section Content'])
+                preview = cleaned_sample[:500] + "..." if len(cleaned_sample) > 500 else cleaned_sample
+            status = f"✅ Excel loaded: {len(df)} sections found\n📊 Topics: {df['Topic Number'].nunique() if 'Topic Number' in df.columns else 'Unknown'}\n🔄 Ready to generate Word document"
+            return status, preview, gr.update(visible=False)
+        except Exception as e: return f"❌ Error reading Excel: {str(e)}", "", gr.update(visible=False)
+
+    def generate_word_document(excel_file):
+        if not excel_file:
+            yield "Please upload an Excel file.", "", gr.update(visible=False)
+            return
+        status_log = ["🚀 Starting Word document generation..."]
+        yield "\n".join(status_log), "", gr.update(visible=False)
+        try:
+            processing_generator = process_excel_to_word(excel_file)
+            for type, val1, *val2 in processing_generator:
+                if type == 'status':
+                    status_log.append(val1)
+                    yield "\n".join(status_log), "", gr.update(visible=False)
+                elif type == 'complete':
+                    word_file_path, result_message = val1, val2[0]
+                    df = pd.read_excel(excel_file)
+                    preview = "Document generated successfully"
+                    if not df.empty and 'Section Content' in df.columns:
+                        cleaned_sample = clean_blog_content(df.iloc[0]['Section Content'])
+                        preview = cleaned_sample[:500] + "..." if len(cleaned_sample) > 500 else cleaned_sample
+                    yield result_message, preview, gr.update(value=word_file_path, visible=True)
+                elif type == 'error':
+                    yield val1, "", gr.update(visible=False)
+        except Exception as e:
+            import traceback
+            yield f"❌ An unexpected error occurred: {str(e)}\n{traceback.format_exc()}", "", gr.update(visible=False)
+
+    # --- EVENT LISTENERS ---
+    mode_choice.change(fn=toggle_content_type, inputs=[mode_choice], outputs=[content_type])
+    generate_ideas_btn.click(fn=handle_idea_generation, inputs=[mode_choice, content_type, num_topics], outputs=[ideas_status, ideas_results, ideas_df, download_ideas_btn])
+    excel_upload.change(fn=load_excel_and_create_checklist, inputs=[excel_upload], outputs=[topics_checklist, loaded_data, posts_status])
+    reset_counter_btn.click(fn=reset_topic_counter, inputs=[], outputs=[posts_status])
+    generate_posts_btn.click(fn=generate_selected_posts, inputs=[excel_upload, topics_checklist, loaded_data], outputs=[posts_status, posts_dataframe, download_posts_btn])
+    word_excel_input.change(fn=process_excel_file, inputs=[word_excel_input], outputs=[word_status, word_preview, download_word_btn])
+    generate_word_btn.click(fn=generate_word_document, inputs=[word_excel_input], outputs=[word_status, word_preview, download_word_btn])
+    gr.HTML("""<div style='text-align: center; padding: 20px; margin-top: 25px; border-top: 1px solid #e0e0e0;'><p style='color: #666; margin: 0;'>🎯 <strong>Digiworks Unified Blog Generator</strong> | Idea Generation → Blog Post Creation → Word Document Formatting<br><small>Perfect for content teams and marketers</small></p></div>""")
+
+    return interface
+
 
 # ======================== MAIN EXECUTION ========================
 if __name__ == "__main__":
@@ -1239,7 +1190,6 @@ if __name__ == "__main__":
     print("🔄 Optimized comparison tables for 'At-a-Glance Matrix' sections")
     print("="*70)
     interface = create_interface()
-    # MODIFIED: Add authentication with a username and password tuple
-    interface.launch(auth=("your_username", "your_password"), share=True, debug=True)
-    print("✅ Unified blog generator launched!")
-
+    # MODIFIED: Launch call is simplified for Hugging Face deployment
+    interface.launch(auth=("your_username", "your_password"))
+    print("✅ Unified blog generator launched!")