97 lines
3.7 KiB
Python
97 lines
3.7 KiB
Python
"""
|
|
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, user_id: str) -> BlogOutlineSection:
|
|
"""Enhance a section using AI with research context.
|
|
|
|
Args:
|
|
section: Outline section to enhance
|
|
focus: Enhancement focus (e.g., "general improvement")
|
|
user_id: User ID (required for subscription checks and usage tracking)
|
|
|
|
Returns:
|
|
Enhanced outline section
|
|
|
|
Raises:
|
|
ValueError: If user_id is not provided
|
|
"""
|
|
if not user_id:
|
|
raise ValueError("user_id is required for section enhancement (subscription checks and usage tracking)")
|
|
|
|
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.main_text_generation import llm_text_gen
|
|
|
|
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 = llm_text_gen(
|
|
prompt=enhancement_prompt,
|
|
json_struct=enhancement_schema,
|
|
system_prompt=None,
|
|
user_id=user_id
|
|
)
|
|
|
|
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
|