Struct LanceDatabase 

pub struct LanceDatabase { /* private fields */ }

Unified LanceDB database backend.

Holds a single lancedb::Connection and implements both StorageBackend (for domain stores) and VectorDatabase (for RAG).

Example

let db = Arc::new(LanceDatabase::new("/path/to/db").await?);

// Use as StorageBackend
let messages = MessageStore::new(db.clone(), embeddings);

// Use as VectorDatabase
db.initialize(384).await?;
db.store_embeddings(embeddings, metadata, contents, root_path).await?;

Implementations

impl LanceDatabase

pub async fn new(db_path: impl Into<String>) -> Result<Self>

Create a new LanceDB database at the given path.

The path can be a local directory. Parent directories are created automatically.

pub async fn with_default_path() -> Result<Self>

Create with the platform default LanceDB path.

pub fn with_scorer(self, scorer: Arc<dyn SearchScorer>) -> Self

Set a custom search scorer for hybrid result fusion.

pub fn connection(&self) -> &Connection

Get the underlying LanceDB connection (for legacy code).

pub fn db_path(&self) -> &str

Get the database path.

pub fn capabilities(&self) -> BackendCapabilities

Report backend capabilities.

pub fn default_lancedb_path() -> String

Get default database path.

Trait Implementations

impl StorageBackend for LanceDatabase

fn ensure_table<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, table_name: &'life1 str, schema: &'life2 [FieldDef], ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Ensure a table exists with the given schema.

fn insert<'life0, 'life1, 'async_trait>( &'life0 self, table_name: &'life1 str, records: Vec<Record>, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Insert one or more records into a table.

fn query<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, table_name: &'life1 str, filter: Option<&'life2 Filter>, limit: Option<usize>, ) -> Pin<Box<dyn Future<Output = Result<Vec<Record>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Query records matching an optional filter.

fn delete<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, table_name: &'life1 str, filter: &'life2 Filter, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Delete records matching a filter.

fn count<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, table_name: &'life1 str, filter: Option<&'life2 Filter>, ) -> Pin<Box<dyn Future<Output = Result<usize>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Count records matching an optional filter.

fn vector_search<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, table_name: &'life1 str, _vector_column: &'life2 str, vector: Vec<f32>, limit: usize, filter: Option<&'life3 Filter>, ) -> Pin<Box<dyn Future<Output = Result<Vec<ScoredRecord>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait,

Vector similarity search.

impl VectorDatabase for LanceDatabase

fn initialize<'life0, 'async_trait>( &'life0 self, dimension: usize, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Initialize the database and create collections if needed.

fn store_embeddings<'life0, 'life1, 'async_trait>( &'life0 self, embeddings: Vec<Vec<f32>>, metadata: Vec<ChunkMetadata>, contents: Vec<String>, root_path: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<usize>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Store embeddings with metadata.

fn search<'life0, 'life1, 'async_trait>( &'life0 self, query_vector: Vec<f32>, query_text: &'life1 str, limit: usize, min_score: f32, project: Option<String>, root_path: Option<String>, hybrid: bool, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Search for similar vectors.

fn search_filtered<'life0, 'life1, 'async_trait>( &'life0 self, query_vector: Vec<f32>, query_text: &'life1 str, limit: usize, min_score: f32, project: Option<String>, root_path: Option<String>, hybrid: bool, file_extensions: Vec<String>, languages: Vec<String>, path_patterns: Vec<String>, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Search with additional filters (extensions, languages, path patterns).

fn delete_by_file<'life0, 'life1, 'async_trait>( &'life0 self, file_path: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<usize>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Delete embeddings for a specific file.

fn clear<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Clear all embeddings.

fn get_statistics<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<DatabaseStats>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Get statistics about the stored data.

fn flush<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Flush/save changes to disk.

fn count_by_root_path<'life0, 'life1, 'async_trait>( &'life0 self, root_path: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<usize>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Count embeddings for a specific root path.

fn get_indexed_files<'life0, 'life1, 'async_trait>( &'life0 self, root_path: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Vec<String>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Get unique file paths indexed for a specific root path.

fn search_with_embeddings<'life0, 'life1, 'async_trait>( &'life0 self, query_vector: Vec<f32>, query_text: &'life1 str, limit: usize, min_score: f32, project: Option<String>, root_path: Option<String>, hybrid: bool, ) -> Pin<Box<dyn Future<Output = Result<(Vec<SearchResult>, Vec<Vec<f32>>)>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Search and return results together with their embedding vectors.