kunthawat/ALwrity
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: image generation overhaul (model-aware text, dim clamping, \.30 pricing), event-driven dashboard cache invalidation, SEO insights (AI visibility, GSC, keyword gap), YouTube OAuth/publish, blog writer & content planning improvements, scheduler monitoring updates

Browse Source
This commit is contained in:
ajaysi
2026-05-30 07:58:22 +05:30
parent aaf94049da
commit 64f1f88cdd
129 changed files with 8796 additions and 8755 deletions
Download Patch File Download Diff File Expand all files Collapse all files

49
backend/services/blog_writer/outline/outline_generator.py
View File

@@ -1,7 +1,8 @@
"""
Outline Generator - AI-powered outline generation from research data.
Generates comprehensive, SEO-optimized outlines using research intelligence.
Generates comprehensive, SEO-optimized outlines using research intelligence
and a keyword-curation engine that prevents keyword stuffing.
"""
from typing import Dict, Any, List, Tuple
@@ -23,6 +24,7 @@ from .metadata_collector import MetadataCollector
from .prompt_builder import PromptBuilder
from .response_processor import ResponseProcessor
from .parallel_processor import ParallelProcessor
from .keyword_curator import KeywordCurator
class OutlineGenerator:
@@ -41,6 +43,14 @@ class OutlineGenerator:
self.prompt_builder = PromptBuilder()
self.response_processor = ResponseProcessor()
self.parallel_processor = ParallelProcessor(self.source_mapper, self.grounding_engine)
# Keyword curation engine
self.keyword_curator = KeywordCurator()
def _curate_keywords(self, research) -> Dict[str, Any]:
"""Run keyword curation on the research data's keyword_analysis."""
raw_analysis = research.keyword_analysis if research else {}
return self.keyword_curator.curate(raw_analysis)
async def generate(self, request: BlogOutlineRequest, user_id: str) -> BlogOutlineResponse:
"""
@@ -59,18 +69,24 @@ class OutlineGenerator:
# Extract research insights
research = request.research
primary_keywords = research.keyword_analysis.get('primary', [])
secondary_keywords = research.keyword_analysis.get('secondary', [])
content_angles = research.suggested_angles
sources = research.sources
search_intent = research.keyword_analysis.get('search_intent', 'informational')
# Curate keywords — reduces 40+ raw keywords to ~13 locked, role-assigned keywords
curated_keywords = self._curate_keywords(research)
# Check for custom instructions
custom_instructions = getattr(request, 'custom_instructions', None)
# Selected (prioritized) content angle and competitive advantage, if any
selected_content_angle = getattr(request, 'selected_content_angle', None)
selected_competitive_advantage = getattr(request, 'selected_competitive_advantage', None)
# Build comprehensive outline generation prompt with rich research data
# Build comprehensive outline generation prompt with curated keyword payload
outline_prompt = self.prompt_builder.build_outline_prompt(
primary_keywords, secondary_keywords, content_angles, sources,
search_intent, request, custom_instructions
curated_keywords, content_angles, sources,
search_intent, request, custom_instructions, selected_content_angle,
selected_competitive_advantage
)
logger.info("Generating AI-powered outline using research results")
@@ -107,7 +123,7 @@ class OutlineGenerator:
ai_title_options = outline_data.get('title_options', [])
content_angle_titles = self.title_generator.extract_content_angle_titles(research)
# Combine AI-generated titles with content angles
# Combine AI-generated titles with content angles (full primary keywords for title variety)
title_options = self.title_generator.combine_title_options(ai_title_options, content_angle_titles, primary_keywords)
logger.info(f"Generated optimized outline with {len(balanced_sections)} sections and {len(title_options)} title options")
@@ -115,7 +131,6 @@ class OutlineGenerator:
# Collect metadata for enhanced UI
source_mapping_stats = self.metadata_collector.collect_source_mapping_stats(mapped_sections, research)
grounding_insights_data = self.metadata_collector.collect_grounding_insights(grounding_insights)
optimization_results = self.metadata_collector.collect_optimization_results(optimized_sections, "comprehensive optimization")
research_coverage = self.metadata_collector.collect_research_coverage(research)
return BlogOutlineResponse(
@@ -124,7 +139,6 @@ class OutlineGenerator:
outline=balanced_sections,
source_mapping_stats=source_mapping_stats,
grounding_insights=grounding_insights_data,
optimization_results=optimization_results,
research_coverage=research_coverage
)
@@ -148,20 +162,26 @@ class OutlineGenerator:
# Extract research insights
research = request.research
primary_keywords = research.keyword_analysis.get('primary', [])
secondary_keywords = research.keyword_analysis.get('secondary', [])
content_angles = research.suggested_angles
sources = research.sources
search_intent = research.keyword_analysis.get('search_intent', 'informational')
# Curate keywords — reduces 40+ raw keywords to ~13 locked, role-assigned keywords
curated_keywords = self._curate_keywords(research)
# Check for custom instructions
custom_instructions = getattr(request, 'custom_instructions', None)
# Selected (prioritized) content angle and competitive advantage, if any
selected_content_angle = getattr(request, 'selected_content_angle', None)
selected_competitive_advantage = getattr(request, 'selected_competitive_advantage', None)
await task_manager.update_progress(task_id, "📊 Analyzing research data and building content strategy...")
# Build comprehensive outline generation prompt with rich research data
# Build comprehensive outline generation prompt with curated keyword payload
outline_prompt = self.prompt_builder.build_outline_prompt(
primary_keywords, secondary_keywords, content_angles, sources,
search_intent, request, custom_instructions
curated_keywords, content_angles, sources,
search_intent, request, custom_instructions, selected_content_angle,
selected_competitive_advantage
)
await task_manager.update_progress(task_id, "🤖 Generating AI-powered outline with research insights...")
@@ -203,7 +223,7 @@ class OutlineGenerator:
ai_title_options = outline_data.get('title_options', [])
content_angle_titles = self.title_generator.extract_content_angle_titles(research)
# Combine AI-generated titles with content angles
# Combine AI-generated titles with content angles (full primary keywords for title variety)
title_options = self.title_generator.combine_title_options(ai_title_options, content_angle_titles, primary_keywords)
await task_manager.update_progress(task_id, "✅ Outline generation and optimization completed successfully!")
@@ -211,7 +231,6 @@ class OutlineGenerator:
# Collect metadata for enhanced UI
source_mapping_stats = self.metadata_collector.collect_source_mapping_stats(mapped_sections, research)
grounding_insights_data = self.metadata_collector.collect_grounding_insights(grounding_insights)
optimization_results = self.metadata_collector.collect_optimization_results(optimized_sections, "comprehensive optimization")
research_coverage = self.metadata_collector.collect_research_coverage(research)
return BlogOutlineResponse(
@@ -220,7 +239,6 @@ class OutlineGenerator:
outline=balanced_sections,
source_mapping_stats=source_mapping_stats,
grounding_insights=grounding_insights_data,
optimization_results=optimization_results,
research_coverage=research_coverage
)
@@ -320,4 +338,3 @@ class OutlineGenerator:
return insights