langchain_community.cache.CassandraCache

class langchain_community.cache.CassandraCache(session: Optional[CassandraSession] = None, keyspace: Optional[str] = None, table_name: str = 'langchain_llm_cache', ttl_seconds: Optional[int] = None, skip_provisioning: bool = False)

Cache that uses Cassandra / Astra DB as a backend.

It uses a single Cassandra table. The lookup keys (which get to form the primary key) are:

• prompt, a string

• llm_string, a deterministic str representation of the model parameters. (needed to prevent collisions same-prompt-different-model collisions)

Initialize with a ready session and a keyspace name. :param session: an open Cassandra session :type session: cassandra.cluster.Session :param keyspace: the keyspace to use for storing the cache :type keyspace: str :param table_name: name of the Cassandra table to use as cache :type table_name: str :param ttl_seconds: time-to-live for cache entries

(default: None, i.e. forever)

Parameters

• session (Optional[CassandraSession]) –

• keyspace (Optional[str]) –

• table_name (str) –

• ttl_seconds (optional int) –

• skip_provisioning (bool) –

Methods

__init__([session, keyspace, table_name, ...])	Initialize with a ready session and a keyspace name. :param session: an open Cassandra session :type session: cassandra.cluster.Session :param keyspace: the keyspace to use for storing the cache :type keyspace: str :param table_name: name of the Cassandra table to use as cache :type table_name: str :param ttl_seconds: time-to-live for cache entries (default: None, i.e. forever) :type ttl_seconds: optional int.
aclear(**kwargs)	Clear cache that can take additional keyword arguments.
alookup(prompt, llm_string)	Look up based on prompt and llm_string.
aupdate(prompt, llm_string, return_val)	Update cache based on prompt and llm_string.
clear(**kwargs)	Clear cache.
delete(prompt, llm_string)	Evict from cache if there's an entry.
delete_through_llm(prompt, llm[, stop])	A wrapper around delete with the LLM being passed.
lookup(prompt, llm_string)	Look up based on prompt and llm_string.
update(prompt, llm_string, return_val)	Update cache based on prompt and llm_string.

__init__(session: Optional[CassandraSession] = None, keyspace: Optional[str] = None, table_name: str = 'langchain_llm_cache', ttl_seconds: Optional[int] = None, skip_provisioning: bool = False)

Initialize with a ready session and a keyspace name. :param session: an open Cassandra session :type session: cassandra.cluster.Session :param keyspace: the keyspace to use for storing the cache :type keyspace: str :param table_name: name of the Cassandra table to use as cache :type table_name: str :param ttl_seconds: time-to-live for cache entries

(default: None, i.e. forever)

Parameters

• session (Optional[CassandraSession]) –

• keyspace (Optional[str]) –

• table_name (str) –

• ttl_seconds (optional int) –

• skip_provisioning (bool) –

async aclear(**kwargs: Any) → None

Clear cache that can take additional keyword arguments.

Parameters

kwargs (Any) –

Return type

None

async alookup(prompt: str, llm_string: str) → Optional[Sequence[Generation]]

Look up based on prompt and llm_string.

Parameters

• prompt (str) –

• llm_string (str) –

Return type

Optional[Sequence[Generation]]

async aupdate(prompt: str, llm_string: str, return_val: Sequence[Generation]) → None

Update cache based on prompt and llm_string.

Parameters

• prompt (str) –

• llm_string (str) –

• return_val (Sequence[Generation]) –

Return type

None

clear(**kwargs: Any) → None

Clear cache. This is for all LLMs at once.

Parameters

kwargs (Any) –

Return type

None

delete(prompt: str, llm_string: str) → None

Evict from cache if there’s an entry.

Parameters

• prompt (str) –

• llm_string (str) –

Return type

None

delete_through_llm(prompt: str, llm: LLM, stop: Optional[List[str]] = None) → None

A wrapper around delete with the LLM being passed. In case the llm(prompt) calls have a stop param, you should pass it here

Parameters

• prompt (str) –

• llm (LLM) –

• stop (Optional[List[str]]) –

Return type

None

lookup(prompt: str, llm_string: str) → Optional[Sequence[Generation]]

Look up based on prompt and llm_string.

Parameters

• prompt (str) –

• llm_string (str) –

Return type

Optional[Sequence[Generation]]

update(prompt: str, llm_string: str, return_val: Sequence[Generation]) → None

Update cache based on prompt and llm_string.

Parameters

• prompt (str) –

• llm_string (str) –

• return_val (Sequence[Generation]) –

Return type

None