diff --git a/database.py b/database.py index cfb50bd..796eada 100644 --- a/database.py +++ b/database.py @@ -1906,7 +1906,7 @@ class ZOPKNews(Base): ai_relevance_score = Column(Integer) # 1-5 stars: 1=weak match, 5=perfect match ai_evaluation_reason = Column(Text) # AI's explanation of relevance decision ai_evaluated_at = Column(DateTime) # When AI evaluation was performed - ai_model = Column(String(100)) # Which AI model was used (e.g., gemini-2.0-flash) + ai_model = Column(String(100)) # Which AI model was used (e.g., gemini-3-flash-preview) # Moderation workflow status = Column(String(20), default='pending', index=True) # pending, approved, rejected, auto_approved @@ -2128,7 +2128,7 @@ class ZOPKKnowledgeChunk(Base): verified_at = Column(DateTime) # Processing metadata - extraction_model = Column(String(100)) # gemini-2.0-flash, gpt-4, etc. + extraction_model = Column(String(100)) # gemini-3-flash-preview, gpt-4, etc. extracted_at = Column(DateTime, default=datetime.now) created_at = Column(DateTime, default=datetime.now) @@ -2350,7 +2350,7 @@ class ZOPKKnowledgeExtractionJob(Base): news_id = Column(Integer, ForeignKey('zopk_news.id'), nullable=False, index=True) # Configuration - extraction_model = Column(String(100)) # gemini-2.0-flash + extraction_model = Column(String(100)) # gemini-3-flash-preview chunk_size = Column(Integer, default=800) # Target tokens per chunk chunk_overlap = Column(Integer, default=100) # Overlap tokens @@ -2399,7 +2399,7 @@ class AIUsageLog(Base): # Request info request_type = Column(String(50), nullable=False) # chat, news_evaluation, user_creation, image_analysis - model = Column(String(100), nullable=False) # gemini-2.0-flash, gemini-1.5-pro, etc. + model = Column(String(100), nullable=False) # gemini-3-flash-preview, gemini-3-pro-preview, etc. # Token counts tokens_input = Column(Integer, default=0) diff --git a/zopk_knowledge_service.py b/zopk_knowledge_service.py index 4f19c29..4853f8e 100644 --- a/zopk_knowledge_service.py +++ b/zopk_knowledge_service.py @@ -2648,7 +2648,7 @@ def create_milestone_from_suggestion( def categorize_milestones_with_ai( db_session, suggestions: List[Dict], - model_name: str = "gemini-2.0-flash-exp" + model_name: str = "gemini-3-flash-preview" ) -> List[Dict]: """ Use Gemini AI to categorize and enhance milestone suggestions.