semantic_router.encoders.bedrock.BedrockEncoder#

class semantic_router.encoders.bedrock.BedrockEncoder(name='amazon.titan-embed-image-v1', input_type='search_query', score_threshold=0.3, access_key_id=None, secret_access_key=None, session_token=None, region=None)#

Bases: BaseEncoder

__init__(name='amazon.titan-embed-image-v1', input_type='search_query', score_threshold=0.3, access_key_id=None, secret_access_key=None, session_token=None, region=None)#

Initializes the BedrockEncoder.

Args:

name: The name of the pre-trained model to use for embedding.: If not provided, the default model specified in EncoderDefault will be used.

score_threshold: The threshold for similarity scores. access_key_id: The AWS access key id for an IAM principle.

If not provided, it will be retrieved from the access_key_id environment variable.

secret_access_key: The secret access key for an IAM principle.: If not provided, it will be retrieved from the AWS_SECRET_KEY environment variable.
session_token: The session token for an IAM principle.: If not provided, it will be retrieved from the AWS_SESSION_TOKEN environment variable.
region: The location of the Bedrock resources.: If not provided, it will be retrieved from the AWS_REGION environment variable, defaulting to “us-west-1”

Raises:

ValueError: If the Bedrock Platform client fails to initialize.

Methods

`__init__`([name, input_type, ...])	Initializes the BedrockEncoder.
`acall`(docs)	rtype: `Coroutine`[`Any`, `Any`, `List`[`List`[`float`]]]
`chunk_strings`(strings[, MAX_WORDS])	Breaks up a list of strings into smaller chunks.
`construct`([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
`copy`(*[, include, exclude, update, deep])	Duplicate a model, optionally choose which fields to include, exclude and change.
`dict`(*[, include, exclude, by_alias, ...])	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
`from_orm`(obj)	rtype: Model
`get_env_variable`(var_name, provided_value[, ...])	Retrieves environment variable or uses a provided value.
`json`(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
`parse_file`(path, *[, content_type, ...])	rtype: Model
`parse_obj`(obj)	rtype: Model
`parse_raw`(b, *[, content_type, encoding, ...])	rtype: Model
`schema`([by_alias, ref_template])	rtype: DictStrAny
`schema_json`(*[, by_alias, ref_template])	rtype: `str`
`set_score_threshold`(v)
`update_forward_refs`(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
`validate`(value)	rtype: Model

Attributes

`client`
`type`
`input_type`
`name`
`access_key_id`
`secret_access_key`
`session_token`
`region`
`score_threshold`

chunk_strings(strings, MAX_WORDS=20)#

Breaks up a list of strings into smaller chunks.

Args:: strings (list): A list of strings to be chunked. max_chunk_size (int): The maximum size of each chunk. Default is 20.
Returns:: list: A list of lists, where each inner list contains a chunk of strings.

classmethod construct(_fields_set=None, **values)#

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Return type:: Model

copy(*, include=None, exclude=None, update=None, deep=False)#

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

include (Union[AbstractSetIntStr, MappingIntStrAny, None]) – fields to include in new model
exclude (Union[AbstractSetIntStr, MappingIntStrAny, None]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model

Return type:

Model

Returns:

new model instance

dict(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude_defaults=False, exclude_none=False)#

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Return type:: DictStrAny

static get_env_variable(var_name, provided_value, default=None)#

Retrieves environment variable or uses a provided value.

Args:: var_name (str): The name of the environment variable. provided_value (Optional[str]): The provided value to use if not None. default (Optional[str]): The default value if the environment variable is not set.
Returns:: str: The value of the environment variable or the provided/default value. None: Where AWS_SESSION_TOKEN is not set or provided
Raises:: ValueError: If no value is provided and the environment variable is not set.

json(*, include=None, exclude=None, by_alias=False, skip_defaults=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=None, models_as_dict=True, **dumps_kwargs)#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

Return type:: str

classmethod update_forward_refs(**localns)#

Try to update ForwardRefs on fields based on this Model, globalns and localns.

Return type:: None