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Scheduled research persona generation

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This commit is contained in:
ajaysi
2025-11-05 08:51:00 +05:30
parent 55087c4f37
commit d99c7c83a7
98 changed files with 14518 additions and 828 deletions
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48
backend/services/blog_writer/research/research_service.py
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@@ -389,10 +389,19 @@ class ResearchService:
exa_provider.track_exa_usage(user_id, cost)
# Extract content for downstream analysis
# Handle None result case
if raw_result is None:
logger.error("raw_result is None after Exa search - this should not happen if HTTPException was raised")
raise ValueError("Exa research result is None - search operation failed unexpectedly")
if not isinstance(raw_result, dict):
logger.warning(f"raw_result is not a dict (type: {type(raw_result)}), using defaults")
raw_result = {}
content = raw_result.get('content', '')
sources = raw_result.get('sources', [])
sources = raw_result.get('sources', []) or []
search_widget = "" # Exa doesn't provide search widgets
search_queries = raw_result.get('search_queries', [])
search_queries = raw_result.get('search_queries', []) or []
grounding_metadata = None # Exa doesn't provide grounding metadata
except RuntimeError as e:
@@ -423,10 +432,15 @@ class ResearchService:
await task_manager.update_progress(task_id, "📊 Processing research results and extracting insights...")
# Extract sources and content
# Handle None result case
if gemini_result is None:
logger.error("gemini_result is None after search - this should not happen if HTTPException was raised")
raise ValueError("Research result is None - search operation failed unexpectedly")
sources = self._extract_sources_from_grounding(gemini_result)
content = gemini_result.get("content", "")
search_widget = gemini_result.get("search_widget", "") or ""
search_queries = gemini_result.get("search_queries", []) or []
content = gemini_result.get("content", "") if isinstance(gemini_result, dict) else ""
search_widget = gemini_result.get("search_widget", "") or "" if isinstance(gemini_result, dict) else ""
search_queries = gemini_result.get("search_queries", []) or [] if isinstance(gemini_result, dict) else []
grounding_metadata = self._extract_grounding_metadata(gemini_result)
# Continue with common analysis (same for both providers)
@@ -548,8 +562,17 @@ class ResearchService:
"""Extract sources from Gemini grounding metadata."""
sources = []
# Handle None or invalid gemini_result
if not gemini_result or not isinstance(gemini_result, dict):
logger.warning("gemini_result is None or not a dict, returning empty sources")
return sources
# The Gemini grounded provider already extracts sources and puts them in the 'sources' field
raw_sources = gemini_result.get("sources", [])
# Ensure raw_sources is a list (handle None case)
if raw_sources is None:
raw_sources = []
for src in raw_sources:
source = ResearchSource(
title=src.get("title", "Untitled"),
@@ -570,6 +593,15 @@ class ResearchService:
grounding_supports = []
citations = []
# Handle None or invalid gemini_result
if not gemini_result or not isinstance(gemini_result, dict):
logger.warning("gemini_result is None or not a dict, returning empty grounding metadata")
return GroundingMetadata(
grounding_chunks=grounding_chunks,
grounding_supports=grounding_supports,
citations=citations
)
# Extract grounding chunks from the raw grounding metadata
raw_grounding = gemini_result.get("grounding_metadata", {})
@@ -577,7 +609,11 @@ class ResearchService:
if hasattr(raw_grounding, 'grounding_chunks'):
raw_chunks = raw_grounding.grounding_chunks
else:
raw_chunks = raw_grounding.get("grounding_chunks", [])
raw_chunks = raw_grounding.get("grounding_chunks", []) if isinstance(raw_grounding, dict) else []
# Ensure raw_chunks is a list (handle None case)
if raw_chunks is None:
raw_chunks = []
for chunk in raw_chunks:
if "web" in chunk: