AI Blog Writer - Implement modular architecture with research, outline, and core services

2025-09-12 16:53:16 +05:30
parent c0a366269d
commit 2ae0c4a8b9
29 changed files with 3210 additions and 907 deletions
--- a/backend/services/blog_writer/outline/section_enhancer.py
+++ b/backend/services/blog_writer/outline/section_enhancer.py
@@ -0,0 +1,81 @@
+"""
+Section Enhancer - AI-powered section enhancement and improvement.
+
+Enhances individual outline sections for better engagement and value.
+"""
+
+from loguru import logger
+
+from models.blog_models import BlogOutlineSection
+
+
+class SectionEnhancer:
+    """Enhances individual outline sections using AI."""
+    
+    async def enhance(self, section: BlogOutlineSection, focus: str = "general improvement") -> BlogOutlineSection:
+        """Enhance a section using AI with research context."""
+        enhancement_prompt = f"""
+        Enhance the following blog section to make it more engaging, comprehensive, and valuable:
+        
+        Current Section:
+        Heading: {section.heading}
+        Subheadings: {', '.join(section.subheadings)}
+        Key Points: {', '.join(section.key_points)}
+        Target Words: {section.target_words}
+        Keywords: {', '.join(section.keywords)}
+        
+        Enhancement Focus: {focus}
+        
+        Improve:
+        1. Make subheadings more specific and actionable
+        2. Add more comprehensive key points with data/insights
+        3. Include practical examples and case studies
+        4. Address common questions and objections
+        5. Optimize for SEO with better keyword integration
+        
+        Respond with JSON:
+        {{
+            "heading": "Enhanced heading",
+            "subheadings": ["enhanced subheading 1", "enhanced subheading 2"],
+            "key_points": ["enhanced point 1", "enhanced point 2"],
+            "target_words": 400,
+            "keywords": ["keyword1", "keyword2"]
+        }}
+        """
+        
+        try:
+            from services.llm_providers.gemini_provider import gemini_structured_json_response
+            
+            enhancement_schema = {
+                "type": "object",
+                "properties": {
+                    "heading": {"type": "string"},
+                    "subheadings": {"type": "array", "items": {"type": "string"}},
+                    "key_points": {"type": "array", "items": {"type": "string"}},
+                    "target_words": {"type": "integer"},
+                    "keywords": {"type": "array", "items": {"type": "string"}}
+                },
+                "required": ["heading", "subheadings", "key_points", "target_words", "keywords"]
+            }
+            
+            enhanced_data = gemini_structured_json_response(
+                prompt=enhancement_prompt,
+                schema=enhancement_schema,
+                temperature=0.4,
+                max_tokens=1000
+            )
+            
+            if isinstance(enhanced_data, dict) and 'error' not in enhanced_data:
+                return BlogOutlineSection(
+                    id=section.id,
+                    heading=enhanced_data.get('heading', section.heading),
+                    subheadings=enhanced_data.get('subheadings', section.subheadings),
+                    key_points=enhanced_data.get('key_points', section.key_points),
+                    references=section.references,
+                    target_words=enhanced_data.get('target_words', section.target_words),
+                    keywords=enhanced_data.get('keywords', section.keywords)
+                )
+        except Exception as e:
+            logger.warning(f"AI section enhancement failed: {e}")
+        
+        return section