Qdrant

Import from @anvia/qdrant.

QdrantVectorStoreConnectOptions

type QdrantDistance = "Cosine" | "Dot" | "Euclid";

type QdrantVectorStoreConnectOptions = {
  client?: QdrantClientLike;
  collectionName: string;
  vectorSize: number;
  createIfMissing?: boolean;
  distance?: QdrantDistance;
};

Purpose: connection options for a Qdrant collection.

Return behavior: consumed by QdrantVectorStore.connect(...).

Notable errors: missing collections reject when createIfMissing is false; collection creation requires vectorSize.

Design note: connect(...) performs async collection lookup or creation before returning a store. This keeps constructors synchronous and side-effect free while making connection and configuration failures happen before ingestion or search.

QdrantVectorStore

class QdrantVectorStore<T, Metadata extends VectorMetadata = VectorMetadata> {
  static connect<T, Metadata extends VectorMetadata = VectorMetadata>(
    options: QdrantVectorStoreConnectOptions,
  ): Promise<QdrantVectorStore<T, Metadata>>;
  upsertDocuments(documents: Array<EmbeddedDocument<T, Metadata>>): Promise<void>;
  index(model: EmbeddingModel): QdrantVectorIndex<T, Metadata>;
}

Purpose: Qdrant-backed document storage.

Return behavior: connect(...) resolves a store; index(...) binds it to an embedding model.

Notable errors: connection and upsert calls reject on Qdrant errors; upsertDocuments(...) throws when a document has no embeddings or metadata uses reserved __anvia_* keys.

QdrantVectorIndex

class QdrantVectorIndex<T, Metadata extends VectorMetadata = VectorMetadata>
  implements VectorSearchIndex<T, Metadata> {
  search(request: VectorSearchRequest): Promise<Array<VectorSearchResult<T, Metadata>>>;
  searchIds(request: VectorSearchRequest): Promise<Array<{ score: number; id: string }>>;
  asTool(options: VectorSearchToolOptions): Tool<{ query: string; topK?: number }, unknown>;
}

Purpose: query-time Qdrant search adapter.

Return behavior: embeds the query, calls Qdrant, deduplicates multi-embedding document IDs, and returns normalized results.

Notable errors: embedding or Qdrant query failures reject.

filterToQdrantFilter

function filterToQdrantFilter(filter: VectorFilter | undefined): unknown;

Purpose: convert Anvia vector filters to Qdrant payload filters.

Return behavior: returns undefined when no filter is supplied.

Notable errors: none directly.