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story writer backend migration complete, Blog writer SEO and story writer backend migration complete, Blog writer SEO and story writer frontend migration complete

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This commit is contained in:
ajaysi
2025-11-13 16:14:26 +05:30
parent 7191c7e7f0
commit 3b9356e2c8
124 changed files with 20055 additions and 1208 deletions
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51
backend/services/blog_writer/research/research_service.py
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@@ -74,7 +74,9 @@ class ResearchService:
if cached_result:
logger.info(f"Returning cached research result for keywords: {request.keywords}")
blog_writer_logger.log_operation_end("research", 0, success=True, cache_hit=True)
return BlogResearchResponse(**cached_result)
# Normalize cached data to fix None values in confidence_scores
normalized_result = self._normalize_cached_research_data(cached_result)
return BlogResearchResponse(**normalized_result)
# User ID validation (validation logic is now in Google Grounding provider)
if not user_id:
@@ -421,7 +423,9 @@ class ResearchService:
if cached_result:
await task_manager.update_progress(task_id, "✅ Found cached research results! Returning instantly...")
logger.info(f"Returning cached research result for keywords: {request.keywords}")
return BlogResearchResponse(**cached_result)
# Normalize cached data to fix None values in confidence_scores
normalized_result = self._normalize_cached_research_data(cached_result)
return BlogResearchResponse(**normalized_result)
# User ID validation
if not user_id:
@@ -759,6 +763,49 @@ class ResearchService:
return sources
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.
Ensures all GroundingSupport objects have confidence_scores as a list.
"""
if not isinstance(cached_data, dict):
return cached_data
normalized = cached_data.copy()
# Normalize grounding_metadata if present
if "grounding_metadata" in normalized and normalized["grounding_metadata"]:
grounding_metadata = normalized["grounding_metadata"].copy() if isinstance(normalized["grounding_metadata"], dict) else {}
# Normalize grounding_supports
if "grounding_supports" in grounding_metadata and isinstance(grounding_metadata["grounding_supports"], list):
normalized_supports = []
for support in grounding_metadata["grounding_supports"]:
if isinstance(support, dict):
normalized_support = support.copy()
# Fix confidence_scores: ensure it's a list, not None
if normalized_support.get("confidence_scores") is None:
normalized_support["confidence_scores"] = []
elif not isinstance(normalized_support.get("confidence_scores"), list):
# If it's not a list, try to convert or default to empty list
normalized_support["confidence_scores"] = []
# Fix grounding_chunk_indices: ensure it's a list, not None
if normalized_support.get("grounding_chunk_indices") is None:
normalized_support["grounding_chunk_indices"] = []
elif not isinstance(normalized_support.get("grounding_chunk_indices"), list):
normalized_support["grounding_chunk_indices"] = []
# Ensure segment_text is a string
if normalized_support.get("segment_text") is None:
normalized_support["segment_text"] = ""
normalized_supports.append(normalized_support)
else:
normalized_supports.append(support)
grounding_metadata["grounding_supports"] = normalized_supports
normalized["grounding_metadata"] = grounding_metadata
return normalized
def _extract_grounding_metadata(self, gemini_result: Dict[str, Any]) -> GroundingMetadata:
"""Extract detailed grounding metadata from Gemini result."""
grounding_chunks = []