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ALwrity LinkedIn Writer: Brainstorm Flow, Copilot Actions, Feature Carousel, Info Modals, Welcome Message

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This commit is contained in:
ajaysi
2025-09-10 13:58:56 +05:30
parent 489a60e4a2
commit da091f7c47
26 changed files with 5029 additions and 1893 deletions
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19
backend/services/llm_providers/gemini_grounded_provider.py
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@@ -254,12 +254,8 @@ class GeminiGroundedProvider:
result['sources'] = sources
logger.info(f"Extracted {len(sources)} sources")
else:
logger.error("❌ CRITICAL: No grounding chunks found in response")
logger.error(f"Grounding metadata structure: {dir(grounding_metadata)}")
if hasattr(grounding_metadata, 'grounding_chunks'):
logger.error(f"Grounding chunks type: {type(grounding_metadata.grounding_chunks)}")
logger.error(f"Grounding chunks value: {grounding_metadata.grounding_chunks}")
raise ValueError("No grounding chunks found - grounding is not working properly")
logger.warning("⚠️ No grounding chunks found in response. Proceeding with available data (search queries/content).")
# Keep sources empty but continue. This avoids hard failure when Google Search tool returns queries only.
# Extract citations from grounding supports
if hasattr(grounding_metadata, 'grounding_supports') and grounding_metadata.grounding_supports:
@@ -278,12 +274,7 @@ class GeminiGroundedProvider:
result['citations'] = citations
logger.info(f"Extracted {len(citations)} citations")
else:
logger.error("❌ CRITICAL: No grounding supports found in response")
logger.error(f"Grounding metadata structure: {dir(grounding_metadata)}")
if hasattr(grounding_metadata, 'grounding_supports'):
logger.error(f"Grounding supports type: {type(grounding_metadata.grounding_supports)}")
logger.error(f"Grounding supports value: {grounding_metadata.grounding_supports}")
raise ValueError("No grounding supports found - grounding is not working properly")
logger.warning("⚠️ No grounding supports found in response. Continuing without inline citations.")
logger.info(f"✅ Successfully extracted {len(result['sources'])} sources and {len(result['citations'])} citations from grounding metadata")
logger.info(f"Sources: {result['sources']}")
@@ -294,9 +285,7 @@ class GeminiGroundedProvider:
logger.error(f"First candidate structure: {dir(candidates[0]) if candidates else 'No candidates'}")
raise ValueError("No grounding metadata found - grounding is not working properly")
else:
logger.error("❌ CRITICAL: No candidates found in response")
logger.error(f"Response structure: {dir(response)}")
raise ValueError("No candidates found in response - grounding is not working properly")
logger.warning("⚠️ No candidates found in response. Returning content without sources.")
# Add content-specific processing
if content_type == "linkedin_post":