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Research component integration, Copilotkit implementation, SEO copilotkit implementation, Wix SEO metadata complete, Wix SEO metadata review

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This commit is contained in:
ajaysi
2025-11-03 16:01:44 +05:30
parent de4328175d
commit e69107b07c
94 changed files with 9748 additions and 1565 deletions
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51
backend/services/blog_writer/outline/outline_generator.py
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@@ -42,10 +42,20 @@ class OutlineGenerator:
self.response_processor = ResponseProcessor()
self.parallel_processor = ParallelProcessor(self.source_mapper, self.grounding_engine)
async def generate(self, request: BlogOutlineRequest) -> BlogOutlineResponse:
async def generate(self, request: BlogOutlineRequest, user_id: str) -> BlogOutlineResponse:
"""
Generate AI-powered outline using research results
Generate AI-powered outline using research results.
Args:
request: Outline generation request with research data
user_id: User ID (required for subscription checks and usage tracking)
Raises:
ValueError: If user_id is not provided
"""
if not user_id:
raise ValueError("user_id is required for outline generation (subscription checks and usage tracking)")
# Extract research insights
research = request.research
primary_keywords = research.keyword_analysis.get('primary', [])
@@ -68,15 +78,15 @@ class OutlineGenerator:
# Define schema with proper property ordering (critical for Gemini API)
outline_schema = self.prompt_builder.get_outline_schema()
# Generate outline using structured JSON response with retry logic
outline_data = await self.response_processor.generate_with_retry(outline_prompt, outline_schema)
# Generate outline using structured JSON response with retry logic (user_id required)
outline_data = await self.response_processor.generate_with_retry(outline_prompt, outline_schema, user_id)
# Convert to BlogOutlineSection objects
outline_sections = self.response_processor.convert_to_sections(outline_data, sources)
# Run parallel processing for speed optimization
# Run parallel processing for speed optimization (user_id required)
mapped_sections, grounding_insights = await self.parallel_processor.run_parallel_processing_async(
outline_sections, research
outline_sections, research, user_id
)
# Enhance sections with grounding insights
@@ -85,9 +95,9 @@ class OutlineGenerator:
mapped_sections, research.grounding_metadata, grounding_insights
)
# Optimize outline for better flow, SEO, and engagement
# Optimize outline for better flow, SEO, and engagement (user_id required)
logger.info("Optimizing outline for better flow and engagement...")
optimized_sections = await self.outline_optimizer.optimize(grounding_enhanced_sections, "comprehensive optimization")
optimized_sections = await self.outline_optimizer.optimize(grounding_enhanced_sections, "comprehensive optimization", user_id)
# Rebalance word counts for optimal distribution
target_words = request.word_count or 1500
@@ -118,10 +128,21 @@ class OutlineGenerator:
research_coverage=research_coverage
)
async def generate_with_progress(self, request: BlogOutlineRequest, task_id: str) -> BlogOutlineResponse:
async def generate_with_progress(self, request: BlogOutlineRequest, task_id: str, user_id: str) -> BlogOutlineResponse:
"""
Outline generation method with progress updates for real-time feedback.
Args:
request: Outline generation request with research data
task_id: Task ID for progress updates
user_id: User ID (required for subscription checks and usage tracking)
Raises:
ValueError: If user_id is not provided
"""
if not user_id:
raise ValueError("user_id is required for outline generation (subscription checks and usage tracking)")
from api.blog_writer.task_manager import task_manager
# Extract research insights
@@ -150,17 +171,17 @@ class OutlineGenerator:
await task_manager.update_progress(task_id, "🔄 Making AI request to generate structured outline...")
# Generate outline using structured JSON response with retry logic
outline_data = await self.response_processor.generate_with_retry(outline_prompt, outline_schema, task_id)
# Generate outline using structured JSON response with retry logic (user_id required for subscription checks)
outline_data = await self.response_processor.generate_with_retry(outline_prompt, outline_schema, user_id, task_id)
await task_manager.update_progress(task_id, "📝 Processing outline structure and validating sections...")
# Convert to BlogOutlineSection objects
outline_sections = self.response_processor.convert_to_sections(outline_data, sources)
# Run parallel processing for speed optimization
# Run parallel processing for speed optimization (user_id required for subscription checks)
mapped_sections, grounding_insights = await self.parallel_processor.run_parallel_processing(
outline_sections, research, task_id
outline_sections, research, user_id, task_id
)
# Enhance sections with grounding insights (depends on both previous tasks)
@@ -169,9 +190,9 @@ class OutlineGenerator:
mapped_sections, research.grounding_metadata, grounding_insights
)
# Optimize outline for better flow, SEO, and engagement
# Optimize outline for better flow, SEO, and engagement (user_id required for subscription checks)
await task_manager.update_progress(task_id, "🎯 Optimizing outline for better flow and engagement...")
optimized_sections = await self.outline_optimizer.optimize(grounding_enhanced_sections, "comprehensive optimization")
optimized_sections = await self.outline_optimizer.optimize(grounding_enhanced_sections, "comprehensive optimization", user_id)
# Rebalance word counts for optimal distribution
await task_manager.update_progress(task_id, "⚖️ Rebalancing word count distribution...")