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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

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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
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60
backend/services/blog_writer/research/research_service.py
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@@ -155,7 +155,7 @@ class ResearchService:
sources = raw_result.get('sources', [])
search_widget = "" # Exa doesn't provide search widgets
search_queries = raw_result.get('search_queries', [])
grounding_metadata = None # Exa doesn't provide grounding metadata
grounding_metadata = self._build_grounding_metadata_from_sources(sources, search_queries)
except RuntimeError as e:
# Fail fast - no fallback for testing/debugging
@@ -239,7 +239,7 @@ class ResearchService:
sources = raw_result.get('sources', [])
search_widget = "" # Tavily doesn't provide search widgets
search_queries = raw_result.get('search_queries', [])
grounding_metadata = None # Tavily doesn't provide grounding metadata
grounding_metadata = self._build_grounding_metadata_from_sources(sources, search_queries)
except RuntimeError as e:
# Fail fast - no fallback for testing/debugging
@@ -482,7 +482,7 @@ class ResearchService:
sources = raw_result.get('sources', []) or []
search_widget = "" # Exa doesn't provide search widgets
search_queries = raw_result.get('search_queries', []) or []
grounding_metadata = None # Exa doesn't provide grounding metadata
grounding_metadata = self._build_grounding_metadata_from_sources(sources, search_queries)
except RuntimeError as e:
# Fail fast - no fallback for testing/debugging
@@ -568,7 +568,7 @@ class ResearchService:
sources = raw_result.get('sources', []) or []
search_widget = "" # Tavily doesn't provide search widgets
search_queries = raw_result.get('search_queries', []) or []
grounding_metadata = None # Tavily doesn't provide grounding metadata
grounding_metadata = self._build_grounding_metadata_from_sources(sources, search_queries)
except RuntimeError as e:
# Fail fast - no fallback for testing/debugging
@@ -728,6 +728,58 @@ class ResearchService:
return sources
def _build_grounding_metadata_from_sources(self, sources: List[Dict[str, Any]], search_queries: List[str]) -> Optional[GroundingMetadata]:
"""Build GroundingMetadata from Exa/Tavily sources (which lack native Google grounding)."""
if not sources:
return None
grounding_chunks = []
grounding_supports = []
citations = []
for i, source in enumerate(sources):
score = source.get('credibility_score', 0.85)
chunk = GroundingChunk(
title=source.get('title', 'Untitled'),
url=source.get('url', ''),
confidence_score=score,
)
grounding_chunks.append(chunk)
highlights = source.get('highlights', [])
if highlights:
for h in highlights:
grounding_supports.append(GroundingSupport(
confidence_scores=[score],
grounding_chunk_indices=[i],
segment_text=h,
))
else:
excerpt = source.get('excerpt', '')
if excerpt:
grounding_supports.append(GroundingSupport(
confidence_scores=[score],
grounding_chunk_indices=[i],
segment_text=excerpt,
))
citations.append(Citation(
citation_type='inline',
start_index=0,
end_index=0,
text=(highlights[0] if highlights else source.get('excerpt', source.get('title', '')))[:200],
source_indices=[i],
reference=f'Source {i + 1}',
))
return GroundingMetadata(
grounding_chunks=grounding_chunks,
grounding_supports=grounding_supports,
citations=citations,
web_search_queries=search_queries or [],
)
def _normalize_cached_research_data(self, cached_data: Dict[str, Any]) -> Dict[str, Any]:
"""
Normalize cached research data to fix None values in confidence_scores.