CfnPromptVersion

class aws_cdk.aws_bedrock.CfnPromptVersion(scope, id, *, prompt_arn, description=None, tags=None)

Bases: CfnResource

Creates a static snapshot of your prompt that can be deployed to production.

For more information, see Deploy prompts using Prompt management by creating versions in the Amazon Bedrock User Guide.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-bedrock-promptversion.html
CloudformationResource:: AWS::Bedrock::PromptVersion
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

cfn_prompt_version = bedrock.CfnPromptVersion(self, "MyCfnPromptVersion",
    prompt_arn="promptArn",

    # the properties below are optional
    description="description",
    tags={
        "tags_key": "tags"
    }
)

Parameters:

scope (Construct) – Scope in which this resource is defined.
id (str) – Construct identifier for this resource (unique in its scope).
prompt_arn (str) – The Amazon Resource Name (ARN) of the version of the prompt.
description (Optional[str]) – The description of the prompt version.
tags (Optional[Mapping[str, str]]) – A map of tag keys and values.

Methods

add_deletion_override(path)

Syntactic sugar for addOverride(path, undefined).

Parameters:: path (str) – The path of the value to delete.
Return type:: None

add_dependency(target)

Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.

This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.

Parameters:

target (CfnResource) –

Return type:

None

add_depends_on(target)

(deprecated) Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.

Parameters:

target (CfnResource) –

Deprecated:

use addDependency

Stability:

deprecated

Return type:

None

add_metadata(key, value)

Add a value to the CloudFormation Resource Metadata.

Parameters:

key (str) –
value (Any) –

See:

Return type:

None

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html

Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.

add_override(path, value)

Adds an override to the synthesized CloudFormation resource.

To add a property override, either use addPropertyOverride or prefix path with “Properties.” (i.e. Properties.TopicName).

If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.

To include a literal . in the property name, prefix with a \. In most programming languages you will need to write this as "\\." because the \ itself will need to be escaped.

For example:

cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"])
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")

would add the overrides Example:

"Properties": {
  "GlobalSecondaryIndexes": [
    {
      "Projection": {
        "NonKeyAttributes": [ "myattribute" ]
        ...
      }
      ...
    },
    {
      "ProjectionType": "INCLUDE"
      ...
    },
  ]
  ...
}

The value argument to addOverride will not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.

Parameters:

path (str) –
- The path of the property, you can use dot notation to override values in complex types. Any intermediate keys will be created as needed.
value (Any) –
- The value. Could be primitive or complex.

Return type:

None

add_property_deletion_override(property_path)

Adds an override that deletes the value of a property from the resource definition.

Parameters:: property_path (str) – The path to the property.
Return type:: None

add_property_override(property_path, value)

Adds an override to a resource property.

Syntactic sugar for addOverride("Properties.<...>", value).

Parameters:

property_path (str) – The path of the property.
value (Any) – The value.

Return type:

None

apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)

Sets the deletion policy of the resource based on the removal policy specified.

The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.

The resource can be deleted (RemovalPolicy.DESTROY), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN). In some cases, a snapshot can be taken of the resource prior to deletion (RemovalPolicy.SNAPSHOT). A list of resources that support this policy can be found in the following link:

Parameters:

policy (Optional[RemovalPolicy]) –
apply_to_update_replace_policy (Optional[bool]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: true
default (Optional[RemovalPolicy]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resource, please consult that specific resource’s documentation.

See:

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-deletionpolicy.html#aws-attribute-deletionpolicy-options

Return type:

None

get_att(attribute_name, type_hint=None)

Returns a token for an runtime attribute of this resource.

Ideally, use generated attribute accessors (e.g. resource.arn), but this can be used for future compatibility in case there is no generated attribute.

Parameters:

attribute_name (str) – The name of the attribute.
type_hint (Optional[ResolutionTypeHint]) –

Return type:

Reference

get_metadata(key)

Retrieve a value value from the CloudFormation Resource Metadata.

Parameters:

key (str) –

See:

Return type:

Any

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html

Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.

inspect(inspector)

Examines the CloudFormation resource and discloses attributes.

Parameters:: inspector (TreeInspector) – tree inspector to collect and process attributes.
Return type:: None

obtain_dependencies()

Retrieves an array of resources this resource depends on.

This assembles dependencies on resources across stacks (including nested stacks) automatically.

Return type:: List[Union[Stack, CfnResource]]

obtain_resource_dependencies()

Get a shallow copy of dependencies between this resource and other resources in the same stack.

Return type:: List[CfnResource]

override_logical_id(new_logical_id)

Overrides the auto-generated logical ID with a specific ID.

Parameters:: new_logical_id (str) – The new logical ID to use for this stack element.
Return type:: None

remove_dependency(target)

Indicates that this resource no longer depends on another resource.

This can be used for resources across stacks (including nested stacks) and the dependency will automatically be removed from the relevant scope.

Parameters:

target (CfnResource) –

Return type:

None

replace_dependency(target, new_target)

Replaces one dependency with another.

Parameters:

target (CfnResource) – The dependency to replace.
new_target (CfnResource) – The new dependency to add.

Return type:

None

to_string()

Returns a string representation of this construct.

Return type:: str
Returns:: a string representation of this resource

Attributes

CFN_RESOURCE_TYPE_NAME = 'AWS::Bedrock::PromptVersion'

attr_arn

The Amazon Resource Name (ARN) of the prompt or the prompt version (if you specified a version in the request).

CloudformationAttribute:: Arn

attr_created_at

The time at which the prompt was created.

CloudformationAttribute:: CreatedAt

attr_customer_encryption_key_arn

A KMS key ARN.

CloudformationAttribute:: CustomerEncryptionKeyArn

attr_default_variant

The name of the default variant for the prompt.

This value must match the name field in the relevant PromptVariant object.

CloudformationAttribute:: DefaultVariant

attr_name

The name of the prompt.

CloudformationAttribute:: Name

attr_prompt_id

The unique identifier of the prompt.

CloudformationAttribute:: PromptId

attr_updated_at

The time at which the prompt was last updated.

CloudformationAttribute:: UpdatedAt

attr_variants

A list of objects, each containing details about a variant of the prompt.

CloudformationAttribute:: Variants

attr_version

The version of the prompt that this summary applies to.

CloudformationAttribute:: Version

cdk_tag_manager: Tag Manager which manages the tags for this resource.

cfn_options: Options for this resource, such as condition, update policy etc.

cfn_resource_type: AWS resource type.

creation_stack

return:

the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.

description: The description of the prompt version.

logical_id

The logical ID for this CloudFormation stack element.

The logical ID of the element is calculated from the path of the resource node in the construct tree.

To override this value, use overrideLogicalId(newLogicalId).

Returns:

the logical ID as a stringified token. This value will only get resolved during synthesis.

node: The tree node.

prompt_arn: The Amazon Resource Name (ARN) of the version of the prompt.

ref

Return a string that will be resolved to a CloudFormation { Ref } for this element.

If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through Lazy.any({ produce: resource.ref }).

stack

The stack in which this element is defined.

CfnElements must be defined within a stack scope (directly or indirectly).

tags: A map of tag keys and values.

Static Methods

classmethod is_cfn_element(x)

Returns true if a construct is a stack element (i.e. part of the synthesized cloudformation template).

Uses duck-typing instead of instanceof to allow stack elements from different versions of this library to be included in the same stack.

Parameters:

x (Any) –

Return type:

bool

Returns:

The construct as a stack element or undefined if it is not a stack element.

classmethod is_cfn_resource(x)

Check whether the given object is a CfnResource.

Parameters:

x (Any) –

Return type:

bool

classmethod is_construct(x)

Checks if x is a construct.

Use this method instead of instanceof to properly detect Construct instances, even when the construct library is symlinked.

Explanation: in JavaScript, multiple copies of the constructs library on disk are seen as independent, completely different libraries. As a consequence, the class Construct in each copy of the constructs library is seen as a different class, and an instance of one class will not test as instanceof the other class. npm install will not create installations like this, but users may manually symlink construct libraries together or use a monorepo tool: in those cases, multiple copies of the constructs library can be accidentally installed, and instanceof will behave unpredictably. It is safest to avoid using instanceof, and using this type-testing method instead.

Parameters:: x (Any) – Any object.
Return type:: bool
Returns:: true if x is an object created from a class which extends Construct.

PromptInferenceConfigurationProperty

class CfnPromptVersion.PromptInferenceConfigurationProperty(*, text)

Bases: object

Contains inference configurations for the prompt.

Parameters:: text (Union[IResolvable, PromptModelInferenceConfigurationProperty, Dict[str, Any]]) – Contains inference configurations for a text prompt.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptinferenceconfiguration.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

prompt_inference_configuration_property = bedrock.CfnPromptVersion.PromptInferenceConfigurationProperty(
    text=bedrock.CfnPromptVersion.PromptModelInferenceConfigurationProperty(
        max_tokens=123,
        stop_sequences=["stopSequences"],
        temperature=123,
        top_k=123,
        top_p=123
    )
)

Attributes

text

Contains inference configurations for a text prompt.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptinferenceconfiguration.html#cfn-bedrock-promptversion-promptinferenceconfiguration-text

PromptInputVariableProperty

class CfnPromptVersion.PromptInputVariableProperty(*, name=None)

Bases: object

Contains information about a variable in the prompt.

Parameters:: name (Optional[str]) – The name of the variable.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptinputvariable.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

prompt_input_variable_property = bedrock.CfnPromptVersion.PromptInputVariableProperty(
    name="name"
)

Attributes

name

The name of the variable.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptinputvariable.html#cfn-bedrock-promptversion-promptinputvariable-name

PromptModelInferenceConfigurationProperty

class CfnPromptVersion.PromptModelInferenceConfigurationProperty(*, max_tokens=None, stop_sequences=None, temperature=None, top_k=None, top_p=None)

Bases: object

Contains inference configurations related to model inference for a prompt.

For more information, see Inference parameters .

Parameters:

max_tokens (Union[int, float, None]) – The maximum number of tokens to return in the response.
stop_sequences (Optional[Sequence[str]]) – A list of strings that define sequences after which the model will stop generating.
temperature (Union[int, float, None]) – Controls the randomness of the response. Choose a lower value for more predictable outputs and a higher value for more surprising outputs.
top_k (Union[int, float, None]) – Sample from the k most likely next tokens.
top_p (Union[int, float, None]) – The percentage of most-likely candidates that the model considers for the next token.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptmodelinferenceconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

prompt_model_inference_configuration_property = bedrock.CfnPromptVersion.PromptModelInferenceConfigurationProperty(
    max_tokens=123,
    stop_sequences=["stopSequences"],
    temperature=123,
    top_k=123,
    top_p=123
)

Attributes

max_tokens

The maximum number of tokens to return in the response.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptmodelinferenceconfiguration.html#cfn-bedrock-promptversion-promptmodelinferenceconfiguration-maxtokens

stop_sequences

A list of strings that define sequences after which the model will stop generating.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptmodelinferenceconfiguration.html#cfn-bedrock-promptversion-promptmodelinferenceconfiguration-stopsequences

temperature

Controls the randomness of the response.

Choose a lower value for more predictable outputs and a higher value for more surprising outputs.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptmodelinferenceconfiguration.html#cfn-bedrock-promptversion-promptmodelinferenceconfiguration-temperature

top_k

Sample from the k most likely next tokens.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptmodelinferenceconfiguration.html#cfn-bedrock-promptversion-promptmodelinferenceconfiguration-topk

top_p

The percentage of most-likely candidates that the model considers for the next token.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptmodelinferenceconfiguration.html#cfn-bedrock-promptversion-promptmodelinferenceconfiguration-topp

PromptTemplateConfigurationProperty

class CfnPromptVersion.PromptTemplateConfigurationProperty(*, text)

Bases: object

Contains the message for a prompt.

For more information, see Prompt management in Amazon Bedrock .

Parameters:: text (Union[IResolvable, TextPromptTemplateConfigurationProperty, Dict[str, Any]]) – Contains configurations for the text in a message for a prompt.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-prompttemplateconfiguration.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

prompt_template_configuration_property = bedrock.CfnPromptVersion.PromptTemplateConfigurationProperty(
    text=bedrock.CfnPromptVersion.TextPromptTemplateConfigurationProperty(
        text="text",

        # the properties below are optional
        input_variables=[bedrock.CfnPromptVersion.PromptInputVariableProperty(
            name="name"
        )]
    )
)

Attributes

text

Contains configurations for the text in a message for a prompt.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-prompttemplateconfiguration.html#cfn-bedrock-promptversion-prompttemplateconfiguration-text

PromptVariantProperty

class CfnPromptVersion.PromptVariantProperty(*, name, template_type, inference_configuration=None, model_id=None, template_configuration=None)

Bases: object

Contains details about a variant of the prompt.

Parameters:

name (str) – The name of the prompt variant.
template_type (str) – The type of prompt template to use.
inference_configuration (Union[IResolvable, PromptInferenceConfigurationProperty, Dict[str, Any], None]) – Contains inference configurations for the prompt variant.
model_id (Optional[str]) – The unique identifier of the model or inference profile with which to run inference on the prompt.
template_configuration (Union[IResolvable, PromptTemplateConfigurationProperty, Dict[str, Any], None]) – Contains configurations for the prompt template.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptvariant.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

prompt_variant_property = bedrock.CfnPromptVersion.PromptVariantProperty(
    name="name",
    template_type="templateType",

    # the properties below are optional
    inference_configuration=bedrock.CfnPromptVersion.PromptInferenceConfigurationProperty(
        text=bedrock.CfnPromptVersion.PromptModelInferenceConfigurationProperty(
            max_tokens=123,
            stop_sequences=["stopSequences"],
            temperature=123,
            top_k=123,
            top_p=123
        )
    ),
    model_id="modelId",
    template_configuration=bedrock.CfnPromptVersion.PromptTemplateConfigurationProperty(
        text=bedrock.CfnPromptVersion.TextPromptTemplateConfigurationProperty(
            text="text",

            # the properties below are optional
            input_variables=[bedrock.CfnPromptVersion.PromptInputVariableProperty(
                name="name"
            )]
        )
    )
)

Attributes

inference_configuration

Contains inference configurations for the prompt variant.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptvariant.html#cfn-bedrock-promptversion-promptvariant-inferenceconfiguration

model_id

//docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html>`_ with which to run inference on the prompt.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptvariant.html#cfn-bedrock-promptversion-promptvariant-modelid
Type:: The unique identifier of the model or `inference profile <https

name

The name of the prompt variant.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptvariant.html#cfn-bedrock-promptversion-promptvariant-name

template_configuration

Contains configurations for the prompt template.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptvariant.html#cfn-bedrock-promptversion-promptvariant-templateconfiguration

template_type

The type of prompt template to use.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-promptvariant.html#cfn-bedrock-promptversion-promptvariant-templatetype

TextPromptTemplateConfigurationProperty

class CfnPromptVersion.TextPromptTemplateConfigurationProperty(*, text, input_variables=None)

Bases: object

Contains configurations for a text prompt template.

To include a variable, enclose a word in double curly braces as in {{variable}} .

Parameters:

text (str) – The message for the prompt.
input_variables (Union[IResolvable, Sequence[Union[IResolvable, PromptInputVariableProperty, Dict[str, Any]]], None]) – An array of the variables in the prompt template.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-textprompttemplateconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_bedrock as bedrock

text_prompt_template_configuration_property = bedrock.CfnPromptVersion.TextPromptTemplateConfigurationProperty(
    text="text",

    # the properties below are optional
    input_variables=[bedrock.CfnPromptVersion.PromptInputVariableProperty(
        name="name"
    )]
)

Attributes

input_variables

An array of the variables in the prompt template.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-textprompttemplateconfiguration.html#cfn-bedrock-promptversion-textprompttemplateconfiguration-inputvariables

text

The message for the prompt.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-bedrock-promptversion-textprompttemplateconfiguration.html#cfn-bedrock-promptversion-textprompttemplateconfiguration-text