A list of dictionaries, where each dictionary represents an action with namespace names as keys and corresponding action strings as values. For instance, action = ToSelectFrom([{“namespace1”: [“action1”, “another identifier of action1”], “namespace2”: “action2”}, {“namespace1”: “action3”, “namespace2”: “action4”}]).
Extends:RLChain
feature_embedder¶
Is an advanced attribute. Responsible for embedding the BasedOn and ToSelectFrom inputs. If omitted, a default embedder is utilized.
Type
PickBestFeatureEmbedder, optional
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param active_policy: Policy = <langchain_experimental.rl_chain.base.RLChain._NoOpPolicy object>¶
param auto_embed: bool = False¶
param callback_manager: Optional[BaseCallbackManager] = None¶
Deprecated, use callbacks instead.
param callbacks: Callbacks = None¶
Optional list of callback handlers (or callback manager). Defaults to None.
Callback handlers are called throughout the lifecycle of a call to a chain,
starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
param llm_chain: Chain [Required]¶
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param metadata: Optional[Dict[str, Any]] = None¶