Vector

ChromaDB implementation of vector search and CRUD capability.

This module provides a ChromaDB implementation of the VectorCapability protocol using langchain-chroma integration.

ChromaVectorCapability(collection_name, em_invoker, client, num_candidates=DEFAULT_NUM_CANDIDATES, encryption=None, default_batch_size=None)

Bases: BaseVectorCapability

ChromaDB implementation of VectorCapability protocol.

This class provides document CRUD operations and vector search using ChromaDB.

Attributes:

Name	Type	Description
collection_name	str	The name of the ChromaDB collection.
collection	Collection	The ChromaDB collection instance.
vector_store	Chroma	The langchain Chroma vector store instance.
num_candidates	int	The maximum number of candidates to consider during search.

Initialize the ChromaDB vector capability.

Parameters:

Name	Type	Description	Default
collection_name	str	The name of the ChromaDB collection.	required
em_invoker	BaseEMInvoker	The embedding model to perform vectorization.	required
client	ClientAPI	The ChromaDB client instance.	required
num_candidates	int	Maximum number of candidates to consider during search. Defaults to 50.	DEFAULT_NUM_CANDIDATES
encryption	EncryptionCapability | None	Encryption capability for field-level encryption. Defaults to None.	None
default_batch_size	int | None	Default batch size for batching operations. Defaults to None.	None

ensure_index(**kwargs) async

Ensure ChromaDB collection exists, creating it if necessary.

This method is idempotent - if the collection already exists, it will return the existing collection. The collection is automatically created during initialization, but this method can be called explicitly to ensure it exists.

Parameters:

Name	Type	Description	Default
**kwargs	Any	Unused; for interface compatibility.	{}

Raises:

Type	Description
RuntimeError	If collection creation fails.