Data store

Redis data store with capability composition.

RedisDataStore(index_name, url=None, client=None)

Bases: BaseDataStore

Redis data store with fulltext capability support.

Attributes:

Name	Type	Description
index_name	str	Name for the Redis index.
client	Redis	Redis client instance.

Initialize the Redis data store.

Parameters:

Name	Type	Description	Default
index_name	str	Name of the Redis index to use.	required
url	str | None	URL for Redis connection. Defaults to None. Format: redis://[[username]:[password]]@host:port/database	None
client	Redis | None	Redis client instance to use. Defaults to None. in which case the url parameter will be used to create a new Redis client.	None

Raises:

Type	Description
ValueError	If neither url nor client is provided, or if URL is invalid.
TypeError	If client is not a Redis instance.
ConnectionError	If Redis connection fails.

fulltext property

Access fulltext capability if registered.

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

Returns:

Name	Type	Description
RedisFulltextCapability	RedisFulltextCapability	Fulltext capability handler.

Raises:

Type	Description
NotRegisteredException	If fulltext capability is not registered.

supported_capabilities property

Return list of currently supported capabilities.

Returns:

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

vector property

Access vector capability if registered.

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

Returns:

Name	Type	Description
RedisVectorCapability	RedisVectorCapability	Vector capability handler.

Raises:

Type	Description
NotRegisteredException	If vector capability is not registered.

get_size(filters=None) async

Get the total number of records in the datastore.

Examples:

# Async usage
count = await datastore.get_size()

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

Parameters:

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

Returns:

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

translate_query_filter(query_filter)

Translate QueryFilter or FilterClause to Redis native filter syntax.

This method delegates to the existing RedisQueryTranslator in the redis.query_translator module and returns the result as a string. It uses the instance's index_name and client to detect field types for accurate Redis Search query syntax.

Examples:

from gllm_datastore.core.filters import filter as F

# Create datastore instance
datastore = RedisDataStore(index_name="my_index", url="redis://localhost:6379")

# Single FilterClause (field types detected from index schema)
clause = F.eq("metadata.status", "active")
result = datastore.translate_query_filter(clause)
# Returns: "@metadata_status:{active}" if status is a TAG field
# Returns: "@metadata_status:active" if status is a TEXT field

# QueryFilter with multiple clauses (AND condition)
filter_obj = F.and_(
    F.eq("metadata.status", "active"),
    F.gt("metadata.age", 25),
)
result = datastore.translate_query_filter(filter_obj)
# Returns: "@metadata_status:{active} @metadata_age:[(25 +inf]"

# QueryFilter with OR condition
filter_obj = F.or_(
    F.eq("metadata.status", "active"),
    F.eq("metadata.status", "pending"),
)
result = datastore.translate_query_filter(filter_obj)
# Returns: "@metadata_status:{active} | @metadata_status:{pending}"

# IN operator (produces parentheses syntax)
filter_obj = F.in_("metadata.category", ["tech", "science"])
result = datastore.translate_query_filter(filter_obj)
# Returns: "@metadata_category:(tech|science)"

# Empty filter returns None
result = datastore.translate_query_filter(None)
# Returns: None

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:

Name	Type	Description
str	str	The translated filter as a Redis Search query string.

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 index. 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
RedisDataStore	RedisDataStore	Self for method chaining.

Raises:

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

with_fulltext(index_name=None)

Configure fulltext capability and return datastore instance.

Schema will be automatically inferred from chunks when creating a new index, or auto-detected from an existing index when performing operations.

Parameters:

Name	Type	Description	Default
index_name	str | None	The name of the Redis index. Defaults to None, in which case the default class attribute will be utilized.	None

Returns:

Name	Type	Description
RedisDataStore	RedisDataStore	RedisDataStore instance for method chaining.

with_vector(em_invoker, index_name=None)

Configure vector capability and return datastore instance.

Schema will be automatically inferred from chunks when creating a new index, or auto-detected from an existing index when performing operations.

Parameters:

Name	Type	Description	Default
em_invoker	BaseEMInvoker	The embedding model to perform vectorization.	required
index_name	str | None	The name of the Redis index. Defaults to None, in which case the default class attribute will be utilized.	None

Returns:

Name	Type	Description
RedisDataStore	RedisDataStore	RedisDataStore instance for method chaining.

Raises:

Type	Description
ValueError	If em_invoker is not provided.