ractogateway.rag.stores.pinecone_store

Pinecone vector store (lazy import).

Install with: pip install ractogateway[rag-pinecone]

class ractogateway.rag.stores.pinecone_store.PineconeStore(index_name, *, api_key=None, namespace='', batch_size=100)[source]

Vector store backed by Pinecone cloud.

Parameters:

index_name (str) – Name of the Pinecone index (must already exist).
api_key (str | None) – Pinecone API key. Falls back to PINECONE_API_KEY env var.
namespace (str) – Pinecone namespace for logical data isolation.
environment – Deprecated Pinecone environment string (for legacy pod-based indexes).
batch_size (int) – Number of vectors per upsert batch.

add(chunks)[source]

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)[source]

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)[source]

Remove chunks with the given IDs from the store.

Remove all chunks from the store.

Return the total number of indexed chunks.