embed#
- langchain_experimental.rl_chain.helpers.embed(to_embed: str | _Embed | Dict | List[str | _Embed] | List[Dict], model: Any, namespace: str | None = None) List[Dict[str, str | List[str]]] [source]#
Embed the actions or context using the SentenceTransformer model (or a model that has an encode function).
- langchain_experimental.rl_chain.helpers.to_embed#
(Union[Union(str, _Embed(str)), Dict, List[Union(str, _Embed(str))], List[Dict]], required) The text to be embedded, either a string, a list of strings or a dictionary or a list of dictionaries.
- langchain_experimental.rl_chain.helpers.namespace#
(str, optional) The default namespace to use when dictionary or list of dictionaries not provided.
- langchain_experimental.rl_chain.helpers.model#
(Any, required) The model to use for embedding
- Returns:
A list of dictionaries where each dictionary has the namespace as the key and the embedded string as the value
- Return type:
List[Dict[str, str]]
- Parameters:
to_embed (str | _Embed | Dict | List[str | _Embed] | List[Dict]) –
model (Any) –
namespace (str | None) –