langchain_community.llms.bedrock.BedrockBase

class langchain_community.llms.bedrock.BedrockBase[source]

Bases: BaseModel, ABC

Bedrock模型的基类。

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 config: Any = None

一个可选的botocore.config.Config实例，用于传递给客户端。

param credentials_profile_name: Optional[str] = None

~/.aws/credentials 或 ~/.aws/config 文件中配置文件的名称，其中指定了访问密钥或角色信息。 如果未指定，则将使用默认凭据配置文件，或者如果在EC2实例上，则将使用来自IMDS的凭据。 参见：https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html

param endpoint_url: Optional[str] = None

如果不想使用默认的us-east-1端点，则需要这个。

param guardrails: Optional[Mapping[str, Any]] = {'id': None, 'trace': False, 'version': None}

一个可选的字典，用于配置Bedrock的防护栏。

该字段’guardrails’包含两个键：’id’和’version’，应为字符串，但初始化为None。它用于确定特定的防护栏是否已启用并正确设置。

类型：

Optional[Mapping[str, str]]：具有’id’和’version’键的映射。

示例： llm = Bedrock(model_id=”<model_id>”, client=<bedrock_client>,

model_kwargs={}, guardrails={

“id”: “<guardrail_id>”, “version”: “<guardrail_version>”})

要为防护栏启用跟踪，请将’trace’键设置为True，并将回调处理程序传递给’generate’、’_call’方法的’run_manager’参数。

示例： llm = Bedrock(model_id=”<model_id>”, client=<bedrock_client>,

model_kwargs={}, guardrails={

“id”: “<guardrail_id>”, “version”: “<guardrail_version>”, “trace”: True},

callbacks=[BedrockAsyncCallbackHandler()])

有关回调处理程序的更多信息，请访问[https://python.langchain.com/docs/modules/callbacks/]。

class BedrockAsyncCallbackHandler(AsyncCallbackHandler):
async def on_llm_error(

self, error: BaseException, **kwargs: Any,

) -> Any:

reason = kwargs.get(“reason”) if reason == “GUARDRAIL_INTERVENED”:

…处理防护栏干预的逻辑…

param model_id: str [Required]

要调用的模型的ID，例如amazon.titan-text-express-v1，这相当于list-foundation-models api中的modelId属性。对于自定义和预置模型，预期值为ARN。

param model_kwargs: Optional[Dict] = None

传递给模型的关键字参数。

param provider: Optional[str] = None

模型提供者，例如，亚马逊，cohere，ai21等。当未提供时，提供者从模型ID的第一部分中提取，例如，在’amazon.titan-text-express-v1’中提取’亚马逊’。对于没有提供者的模型ID，例如具有与其关联的ARN的自定义和预配模型，应提供此值。

param provider_stop_sequence_key_name_map: Mapping[str, str] = {'ai21': 'stop_sequences', 'amazon': 'stopSequences', 'anthropic': 'stop_sequences', 'cohere': 'stop_sequences', 'mistral': 'stop'}
param region_name: Optional[str] = None

AWS区域，例如`us-west-2`。如果未提供，则回退到AWS_DEFAULT_REGION环境变量 或在~/.aws/config中指定的区域。

param streaming: bool = False

是否流式传输结果。

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model

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

Parameters

  • _fields_set (Optional[SetStr]) –

  • values (Any) –

Return type

Model

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model

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

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 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

  • self (Model) –

Returns

new model instance

Return type

Model

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny

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

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

Return type

DictStrAny

classmethod from_orm(obj: Any) → Model
Parameters

obj (Any) –

Return type

Model

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode

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().

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

  • encoder (Optional[Callable[[Any], Any]]) –

  • models_as_dict (bool) –

  • dumps_kwargs (Any) –

Return type

unicode

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
Parameters

  • path (Union[str, Path]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

classmethod parse_obj(obj: Any) → Model
Parameters

obj (Any) –

Return type

Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
Parameters

  • b (Union[str, bytes]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny
Parameters

  • by_alias (bool) –

  • ref_template (unicode) –

Return type

DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode
Parameters

  • by_alias (bool) –

  • ref_template (unicode) –

  • dumps_kwargs (Any) –

Return type

unicode

classmethod update_forward_refs(**localns: Any) → None

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

Parameters

localns (Any) –

Return type

None

classmethod validate(value: Any) → Model
Parameters

value (Any) –

Return type

Model