Data store

ChromaDB data store with capability composition.

ChromaClientType

Bases: StrEnum

Enum for different types of ChromaDB clients.

ChromaDataStore(collection_name, client_type=ChromaClientType.MEMORY, persist_directory=None, host=None, port=None, headers=None, client_settings=None)

Bases: BaseDataStore

ChromaDB data store with multiple capability support.

Attributes:

Name	Type	Description
collection_name	str	The name of the ChromaDB collection.
client	ClientAPI	The ChromaDB client instance.

Initialize the ChromaDB data store.

Parameters:

Name	Type	Description	Default
collection_name	str	The name of the ChromaDB collection.	required
client_type	ChromaClientType	Type of ChromaDB client to use. Defaults to ChromaClientType.MEMORY.	MEMORY
persist_directory	str | None	Directory to persist vector store data. Required for PERSISTENT client type. Defaults to None.	None
host	str | None	Host address for ChromaDB server. Required for HTTP client type. Defaults to None.	None
port	int | None	Port for ChromaDB server. Required for HTTP client type. Defaults to None.	None
headers	dict | None	A dictionary of headers to send to the Chroma server. Used for authentication with the Chroma server for HTTP client type. Defaults to None.	None
client_settings	dict | None	A dictionary of additional settings for the Chroma client. Defaults to None.	None

fulltext property

Access fulltext capability if supported.

This method uses the logic of its parent class to return the fulltext capability handler. This method overrides the parent class to return the ChromaFulltextCapability handler for better type hinting.

Returns:

Name	Type	Description
ChromaFulltextCapability	ChromaFulltextCapability	Fulltext capability handler.

Raises:

Type	Description
NotSupportedException	If fulltext capability is not supported.

supported_capabilities property

Return list of currently supported capabilities.

Returns:

Type	Description
list[str]	list[str]: List of capability names that are supported.

vector property

Access vector capability if supported.

This method uses the logic of its parent class to return the vector capability handler. This method overrides the parent class to return the ChromaVectorCapability handler for better type hinting.

Returns:

Name	Type	Description
ChromaVectorCapability	ChromaVectorCapability	Vector capability handler.

Raises:

Type	Description
NotSupportedException	If vector capability is not supported.

get_size(filters=None) async

Get the total number of records in the datastore.

Examples:

1) Basic usage (no filters): python # Async usage count = await datastore.get_size()

2) With filters (using Query Filters): python from gllm_datastore.core.filters import filter as F count = await datastore.get_size(filters=F.eq("metadata.status", "active"))

Parameters:

Name	Type	Description	Default
filters	FilterClause | QueryFilter | None	Query filters to apply. Defaults to None.	None

Returns:

Name	Type	Description
int	int	The total number of records matching the filters.

translate_query_filter(query_filter) classmethod

Translate QueryFilter or FilterClause to ChromaDB native filter syntax.

This method uses ChromaQueryTranslator to translate filters and returns the result as a dictionary.

Examples:

1. Translate a simple FilterClause: ```python from gllm_datastore.core.filters import filter as F

   filter_clause = F.eq("metadata.status", "active") result = ChromaDataStore.translate_query_filter(filter_clause)

   result -> {"where": {"status": "active"}}

   ```

2. Translate QueryFilter with metadata filters: ```python from gllm_datastore.core.filters import filter as F

   filters = F.and_( F.eq("metadata.category", "tech"), F.gte("metadata.price", 10), ) result = ChromaDataStore.translate_query_filter(filters)

   result ->

   {

   "where": {

   "$and": [

   {"category": "tech"},

   {"price": {"$gte": 10}}

   ]

   }

   }

   ```

3. Translate QueryFilter with content filters: ```python from gllm_datastore.core.filters import filter as F

   filters = F.text_contains("content", "python") result = ChromaDataStore.translate_query_filter(filters)

   result -> {"where_document": {"$contains": "python"}}

   ```

4. Translate QueryFilter with id filters: ```python from gllm_datastore.core.filters import filter as F

   filters = F.in_("id", ["chunk_1", "chunk_2"]) result = ChromaDataStore.translate_query_filter(filters)

   result -> {"ids": ["chunk_1", "chunk_2"]}

   ```

5. Translate complex nested QueryFilter: ```python from gllm_datastore.core.filters import filter as F

   filters = F.and_( F.or_( F.eq("metadata.status", "active"), F.eq("metadata.status", "pending"), ), F.text_contains("content", "machine learning"), F.in_("id", ["chunk_1", "chunk_2"]), ) result = ChromaDataStore.translate_query_filter(filters)

   result ->

   {

   "where": {

   "$or": [

   {"status": "active"},

   {"status": "pending"}

   ]

   },

   "where_document": {"$contains": "machine learning"},

   "ids": ["chunk_1", "chunk_2"]

   }

   ```

Parameters:

Name	Type	Description	Default
query_filter	FilterClause | QueryFilter	The filter to translate. Can be a single FilterClause or a QueryFilter with multiple clauses.	required

Returns:

Type	Description
dict[str, Any] | None	dict[str, Any] | None: The translated filter as a ChromaDB query dict.

with_encryption(encryptor, fields)

Enable encryption for specified fields.

Note

Encrypted fields (content and metadata fields specified in encryption configuration) must be serializable to strings. Non-string values will be converted to strings before encryption.

Warning

When encryption is enabled for fields, some search and filter operations may be limited or broken. Encrypted fields cannot be used in filters for update or delete operations, as the filter values are not encrypted and will not match the encrypted data stored in the collection. Use non-encrypted fields (like 'id') for filtering when working with encrypted data.

Parameters:

Name	Type	Description	Default
encryptor	BaseEncryptor	The encryptor instance to use. Must not be None.	required
fields	set[str] | list[str]	Set or list of field names to encrypt. Must not be empty.	required

Returns:

Name	Type	Description
ChromaDataStore	ChromaDataStore	Self for method chaining.

Raises:

Type	Description
ValueError	If encryptor is None or fields is empty.

with_fulltext(collection_name=None, num_candidates=DEFAULT_NUM_CANDIDATES)

Configure fulltext capability and return datastore instance.

This method uses the logic of its parent class to configure the fulltext capability. This method overrides the parent class for better type hinting.

Parameters:

Name	Type	Description	Default
collection_name	str | None	Name of the collection to use in ChromaDB. Defaults to None, in which case the default class attribute will be utilized.	None
num_candidates	int	Maximum number of candidates to consider during search. Defaults to DEFAULT_NUM_CANDIDATES.	DEFAULT_NUM_CANDIDATES

Returns:

Name	Type	Description
Self	ChromaDataStore	Self for method chaining.

with_vector(em_invoker, collection_name=None, num_candidates=DEFAULT_NUM_CANDIDATES)

Configure vector capability and return datastore instance.

This method uses the logic of its parent class to configure the vector capability. This method overrides the parent class for better type hinting.

Parameters:

Name	Type	Description	Default
em_invoker	BaseEMInvoker	The embedding model to perform vectorization.	required
collection_name	str | None	Name of the collection to use in ChromaDB. Defaults to None, in which case the default class attribute will be utilized.	None
num_candidates	int	Maximum number of candidates to consider during search. Defaults to DEFAULT_NUM_CANDIDATES.	DEFAULT_NUM_CANDIDATES

Returns:

Name	Type	Description
Self	ChromaDataStore	Self for method chaining.