Blog SEO Analysis Modal - Updated with SEO Metadata Generator, Core Metadata Tab, and Metadata Display Components

2025-09-23 16:21:09 +05:30
parent 12119d418b
commit a91677782e
16 changed files with 3433 additions and 89 deletions
--- a/backend/test_seo_metadata_generator.py
+++ b/backend/test_seo_metadata_generator.py
@@ -0,0 +1,109 @@
+"""
+Test script for BlogSEOMetadataGenerator
+Run this to verify the service works correctly
+"""
+
+import asyncio
+import sys
+import os
+
+# Add the backend directory to the Python path
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+from services.blog_writer.seo.blog_seo_metadata_generator import BlogSEOMetadataGenerator
+
+
+async def test_metadata_generation():
+    """Test the metadata generation service"""
+    
+    # Sample blog content
+    blog_content = """
+    # The Future of AI in Content Marketing
+
+    Artificial Intelligence is revolutionizing the way we create and distribute content. 
+    From automated content generation to personalized marketing campaigns, AI is transforming 
+    the content marketing landscape.
+
+    ## Key Benefits of AI in Content Marketing
+
+    1. **Automated Content Creation**: AI can generate high-quality content at scale
+    2. **Personalization**: AI enables hyper-personalized content for different audiences
+    3. **Optimization**: AI helps optimize content for better performance
+    4. **Analytics**: AI provides deeper insights into content performance
+
+    ## The Road Ahead
+
+    As AI technology continues to evolve, we can expect even more sophisticated 
+    content marketing tools and strategies. The future is bright for AI-powered content marketing.
+    """
+    
+    blog_title = "The Future of AI in Content Marketing"
+    
+    # Sample research data
+    research_data = {
+        "keyword_analysis": {
+            "primary": ["AI content marketing", "artificial intelligence marketing", "content automation"],
+            "long_tail": ["AI content marketing tools 2024", "automated content generation benefits"],
+            "semantic": ["machine learning", "content strategy", "digital marketing", "automation"],
+            "search_intent": "informational",
+            "target_audience": "marketing professionals",
+            "industry": "technology"
+        }
+    }
+    
+    try:
+        print("🚀 Testing BlogSEOMetadataGenerator...")
+        
+        # Initialize the generator
+        generator = BlogSEOMetadataGenerator()
+        
+        # Generate metadata
+        print("📝 Generating comprehensive SEO metadata...")
+        results = await generator.generate_comprehensive_metadata(
+            blog_content=blog_content,
+            blog_title=blog_title,
+            research_data=research_data
+        )
+        
+        # Display results
+        print("\n✅ Metadata Generation Results:")
+        print("=" * 50)
+        
+        print(f"Success: {results.get('success', False)}")
+        print(f"SEO Title: {results.get('seo_title', 'N/A')}")
+        print(f"Meta Description: {results.get('meta_description', 'N/A')}")
+        print(f"URL Slug: {results.get('url_slug', 'N/A')}")
+        print(f"Blog Tags: {results.get('blog_tags', [])}")
+        print(f"Blog Categories: {results.get('blog_categories', [])}")
+        print(f"Social Hashtags: {results.get('social_hashtags', [])}")
+        print(f"Reading Time: {results.get('reading_time', 0)} minutes")
+        print(f"Focus Keyword: {results.get('focus_keyword', 'N/A')}")
+        print(f"Optimization Score: {results.get('metadata_summary', {}).get('optimization_score', 0)}%")
+        
+        print("\n📱 Social Media Metadata:")
+        print("-" * 30)
+        open_graph = results.get('open_graph', {})
+        print(f"OG Title: {open_graph.get('title', 'N/A')}")
+        print(f"OG Description: {open_graph.get('description', 'N/A')}")
+        
+        twitter_card = results.get('twitter_card', {})
+        print(f"Twitter Title: {twitter_card.get('title', 'N/A')}")
+        print(f"Twitter Description: {twitter_card.get('description', 'N/A')}")
+        
+        print("\n🔍 Structured Data:")
+        print("-" * 20)
+        json_ld = results.get('json_ld_schema', {})
+        print(f"Schema Type: {json_ld.get('@type', 'N/A')}")
+        print(f"Headline: {json_ld.get('headline', 'N/A')}")
+        
+        print(f"\n⏱️ Generation completed in: {results.get('generated_at', 'N/A')}")
+        print("🎉 Test completed successfully!")
+        
+    except Exception as e:
+        print(f"❌ Test failed: {e}")
+        import traceback
+        traceback.print_exc()
+
+
+if __name__ == "__main__":
+    asyncio.run(test_metadata_generation())