ractogateway.rag.stores.chroma_store

ChromaDB vector store (lazy import).

Install with: pip install ractogateway[rag-chroma]

class ractogateway.rag.stores.chroma_store.ChromaStore(collection='ractogateway', *, path=None, host=None, port=8000, distance_function='cosine')

Bases: BaseVectorStore

Vector store backed by ChromaDB.

Supports both in-process (path or None for ephemeral) and HTTP-client modes (host + port).

Parameters:

• collection (str) – Name of the ChromaDB collection.

• path (str | None) – Persist directory for a local persistent client. None = ephemeral.

• host (str | None) – ChromaDB server host (enables HTTP client mode).

• port (int) – ChromaDB server port (default 8000).

• distance_function (str) – "cosine", "l2", or "ip" (inner product).

add(chunks)

Add chunks (with embeddings) to the store.

Parameters:

chunks (list[Chunk]) – Chunks to index. Each chunk must have a non-None embedding.

Raises:

ValueError – If any chunk has embedding=None.

Return type:

None

search(embedding, top_k=5, filters=None)

Search for the top_k most similar chunks.

Parameters:

• embedding (list[float]) – Query embedding vector.

• top_k (int) – Number of results to return.

• filters (dict[str, Any] | None) – Optional metadata filters (store-specific format).

Return type:

list[RetrievalResult]

Returns:

list[RetrievalResult] – Ranked list of results (rank 1 = most similar).

delete(chunk_ids)

Remove chunks with the given IDs from the store.

Return type:

None

clear()

Remove all chunks from the store.

Return type:

None

count()

Return the total number of indexed chunks.

Return type:

int