langchain_experimental.rl_chain.pick_best_chain.PickBestFeatureEmbedder¶
class langchain_experimental.rl_chain.pick_best_chain.PickBestFeatureEmbedder(auto_embed: bool, model: Optional[Any] = None, *args: Any, **kwargs: Any)[source]¶
Text Embedder class that embeds the BasedOn and ToSelectFrom inputs into a format that can be used by the learning policy
model name
The type of embeddings to be used for feature representation. Defaults to BERT SentenceTransformer.
Type
Any, optional
Methods
__init__(auto_embed[, model])
format(event)
format_auto_embed_off(event)
Converts the BasedOn and ToSelectFrom into a format that can be used by VW
format_auto_embed_on(event)
get_context_and_action_embeddings(event)
get_indexed_dot_product(context_emb, action_embs)
get_label(event)
__init__(auto_embed: bool, model: Optional[Any] = None, *args: Any, **kwargs: Any)[source]¶
format(event: PickBestEvent) → str[source]¶
format_auto_embed_off(event: PickBestEvent) → str[source]¶
Converts the BasedOn and ToSelectFrom into a format that can be used by VW
format_auto_embed_on(event: PickBestEvent) → str[source]¶
get_context_and_action_embeddings(event: PickBestEvent) → tuple[source]¶
get_indexed_dot_product(context_emb: List, action_embs: List) → Dict[source]¶
get_label(event: PickBestEvent) → tuple[source]¶