John C Fitzpatrick 85bd6bc012 Fix multi-dimensional vector hybrid search functions (#681) ... Fixes critical bug where hybrid search functions referenced non-existent cp.embedding and ce.embedding columns instead of dimension-specific columns. Changes: - Add new multi-dimensional hybrid search functions with dynamic column selection - Maintain backward compatibility with existing legacy functions - Support all embedding dimensions: 384, 768, 1024, 1536, 3072 - Proper error handling for unsupported dimensions Resolves: #675 - RAG queries now work with multi-dimensional embeddings 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Claude <noreply@anthropic.com>		2025-09-18 10:06:10 -07:00
..
add_hybrid_search_tsvector.sql	Fix multi-dimensional vector hybrid search functions (#681)	2025-09-18 10:06:10 -07:00
add_priority_column_to_tasks.sql	feat: decouple task priority from task order (#652)	2025-09-17 13:44:25 +03:00
add_source_url_display_name.sql	Fix race condition in concurrent crawling with unique source IDs (#472)	2025-08-29 14:54:16 +03:00
backup_database.sql	feat: Ollama Integration with Separate LLM/Embedding Model Support (#643)	2025-09-15 06:38:02 -07:00
complete_setup.sql	Fix multi-dimensional vector hybrid search functions (#681)	2025-09-18 10:06:10 -07:00
DB_UPGRADE_INSTRUCTIONS.md	feat: Ollama Integration with Separate LLM/Embedding Model Support (#643)	2025-09-15 06:38:02 -07:00
RESET_DB.sql	Enhanced the hybrid search strategy with tsvector keyword matching (#539)	2025-09-10 14:23:49 +03:00
upgrade_database.sql	feat: Ollama Integration with Separate LLM/Embedding Model Support (#643)	2025-09-15 06:38:02 -07:00
validate_migration.sql	feat: Ollama Integration with Separate LLM/Embedding Model Support (#643)	2025-09-15 06:38:02 -07:00