PgVector - Agno

Parameter	Type	Default	Description
`table_name`	`str`	Required	Name of the table to store vectors and metadata
`schema`	`str`	`"ai"`	Database schema name
`db_url`	`Optional[str]`	`None`	Database connection URL
`db_engine`	`Optional[Engine]`	`None`	SQLAlchemy database engine
`embedder`	`Optional[Embedder]`	`OpenAIEmbedder()`	Embedder instance to generate embeddings
`search_type`	`SearchType`	`SearchType.vector`	Type of search to perform (vector, keyword, or hybrid)
`vector_index`	`Union[Ivfflat, HNSW]`	`HNSW()`	Vector index configuration
`distance`	`Distance`	`Distance.cosine`	Distance metric for vector comparisons
`prefix_match`	`bool`	`False`	Enable prefix matching for full-text search
`vector_score_weight`	`float`	`0.5`	Weight for vector similarity in hybrid search
`content_language`	`str`	`"english"`	Language for full-text search
`schema_version`	`int`	`1`	Version of the database schema
`auto_upgrade_schema`	`bool`	`False`	Automatically upgrade schema if True
`reranker`	`Optional[Reranker]`	`None`	Reranker instance for post-processing search results