package database
import "fmt"
// dynamicSchema returns schema DDL using the configured embedding dimension
func dynamicSchema(embeddingDims int) []string {
if embeddingDims <= 0 {
embeddingDims = 4
}
return []string{
// Create entities table
fmt.Sprintf(`CREATE TABLE IF NOT EXISTS entities (
name TEXT PRIMARY KEY,
entity_type TEXT NOT NULL,
embedding F32_BLOB(%d),
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
)`, embeddingDims),
// Create observations table
`CREATE TABLE IF NOT EXISTS observations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
entity_name TEXT NOT NULL,
content TEXT NOT NULL,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (entity_name) REFERENCES entities(name)
)`,
// Create relations table
`CREATE TABLE IF NOT EXISTS relations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
source TEXT NOT NULL,
target TEXT NOT NULL,
relation_type TEXT NOT NULL,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (source) REFERENCES entities(name),
FOREIGN KEY (target) REFERENCES entities(name)
)`,
// Create indexes
`CREATE INDEX IF NOT EXISTS idx_entities_name ON entities(name)`,
`CREATE INDEX IF NOT EXISTS idx_entities_created_at ON entities(created_at)`,
`CREATE INDEX IF NOT EXISTS idx_observations_entity ON observations(entity_name)`,
`CREATE INDEX IF NOT EXISTS idx_relations_source ON relations(source)`,
`CREATE INDEX IF NOT EXISTS idx_relations_target ON relations(target)`,
`CREATE INDEX IF NOT EXISTS idx_relations_src_tgt_type ON relations(source, target, relation_type)`,
`CREATE INDEX IF NOT EXISTS idx_relations_type_source ON relations(relation_type, source)`,
// Create vector index for similarity search
`CREATE INDEX IF NOT EXISTS idx_entities_embedding ON entities(libsql_vector_idx(embedding))`,
// Soft cascade via triggers to keep referential integrity without table rebuilds
`CREATE TRIGGER IF NOT EXISTS trg_entities_delete_cascade AFTER DELETE ON entities BEGIN
DELETE FROM observations WHERE entity_name = old.name;
DELETE FROM relations WHERE source = old.name OR target = old.name;
END;`,
}
}
