Amazon Bedrock provides the ability to create and save prompts using Prompt management so that you can save time by applying the same prompt to different workflows. You can include variables in the prompt so that you can adjust the prompt for different use case.
The Prompt resource allows you to create a new prompt.
const cmk = new kms.Key(this, 'cmk', {});
const claudeModel = BedrockFoundationModel.ANTHROPIC_CLAUDE_SONNET_V1_0;
const variant1 = PromptVariant.text({
variantName: 'variant1',
model: claudeModel,
promptVariables: ['topic'],
promptText: 'This is my first text prompt. Please summarize our conversation on: .',
inferenceConfiguration: {
temperature: 1.0,
topP: 0.999,
maxTokens: 2000,
},
});
const prompt1 = new Prompt(this, 'prompt1', {
promptName: 'prompt1',
description: 'my first prompt',
defaultVariant: variant1,
variants: [variant1],
kmsKey: cmk,
});
cmk = kms.Key(self, "cmk")
claude_model = bedrock.BedrockFoundationModel.ANTHROPIC_CLAUDE_SONNET_V1_0
variant1 = bedrock.PromptVariant.text(
variant_name="variant1",
model=claude_model,
prompt_variables=["topic"],
prompt_text="This is my first text prompt. Please summarize our conversation on: .",
inference_configuration={
"temperature": 1.0,
"top_p": 0.999,
"maxTokens": 2000,
}
)
prompt = bedrock.Prompt(
self,
"myprompt",
prompt_name="prompt1",
description="my first prompt",
default_variant=variant1,
variants=[variant1],
kms_key=cmk
)
Use this template type when the model supports the Converse API or the Anthropic Claude Messages API. This allows you to include a System prompt and previous User messages and Assistant messages for context.
const cmk = new kms.Key(this, 'cmk', {});
const variantChat = PromptVariant.chat({
variantName: 'variant1',
model: BedrockFoundationModel.ANTHROPIC_CLAUDE_3_5_SONNET_V1_0,
messages: [
ChatMessage.userMessage('From now on, you speak Japanese!'),
ChatMessage.assistantMessage('Konnichiwa!'),
ChatMessage.userMessage('From now on, you speak !'),
],
system: 'You are a helpful assistant that only speaks the language you`re told.',
promptVariables: ['language'],
toolConfiguration: {
toolChoice: ToolChoice.AUTO,
tools: [
{
toolSpec: {
name: 'top_song',
description: 'Get the most popular song played on a radio station.',
inputSchema: {
json: {
type: 'object',
properties: {
sign: {
type: 'string',
description:
'The call sign for the radio station for which you want the most popular song. Example calls signs are WZPZ and WKR.',
},
},
required: ['sign'],
},
},
},
},
],
},
});
new Prompt(stack, 'prompt1', {
promptName: 'prompt-chat',
description: 'my first chat prompt',
defaultVariant: variantChat,
variants: [variantChat],
kmsKey: cmk,
});
# Create KMS key
cmk = kms.Key(self, "cmk")
# Create tool specification
tool_spec = CfnPrompt.ToolSpecificationProperty(
name="top_song",
description="Get the most popular song played on a radio station.",
input_schema=CfnPrompt.ToolInputSchemaProperty(
json={
"type": "object",
"properties": {
"sign": {
"type": "string",
"description": "The call sign for the radio station for which you want the most popular song. Example calls signs are WZPZ and WKR."
}
},
"required": ["sign"]
}
)
)
# Create tool configuration
tool_config = bedrock.ToolConfiguration(
tool_choice=bedrock.ToolChoice.AUTO,
tools=[
CfnPrompt.ToolProperty(
tool_spec=tool_spec
)
]
)
# Create chat variant
variant_chat = bedrock.PromptVariant.chat(
variant_name="variant1",
model=bedrock.BedrockFoundationModel.ANTHROPIC_CLAUDE_3_5_SONNET_V1_0,
messages=[
bedrock.ChatMessage.user("From now on, you speak Japanese!"),
bedrock.ChatMessage.assistant("Konnichiwa!"),
bedrock.ChatMessage.user("From now on, you speak !"),
],
system="You are a helpful assistant that only speaks the language you're told.",
prompt_variables=["language"],
tool_configuration=tool_config
)
# Create prompt
prompt = bedrock.Prompt(
self,
"prompt1",
prompt_name="prompt-chat",
description="my first chat prompt",
default_variant=variant_chat,
variants=[variant_chat],
kms_key=cmk
)
| Property | Type | Required | Description |
|---|---|---|---|
| promptName | string | Yes | The name of the prompt |
| description | string | No | A description of the prompt |
| defaultVariant | PromptVariant | Yes | The default variant to use for the prompt |
| variants | PromptVariant[] | No | Additional variants for the prompt |
| kmsKey | kms.IKey | No | The KMS key to use for encrypting the prompt. Defaults to AWS managed key |
| tags | Record<string, string> | No | Tags to apply to the prompt |
Prompt variants in the context of Amazon Bedrock refer to alternative configurations of a prompt, including its message or the model and inference configurations used. Prompt variants allow you to create different versions of a prompt, test them, and save the variant that works best for your use case. You can add prompt variants to a prompt by creating a PromptVariant object and specify the variants on prompt creation, or by using the .addVariant(..) method on a Prompt object.
const variant2 = PromptVariant.text({
variantName: "variant2",
model: claudeModel,
promptVariables: [ "topic" ],
promptText: "This is my second text prompt. Please summarize our conversation on: .",
inferenceConfiguration: {
temperature: 0.5,
topP: 0.999,
maxTokens: 2000,
},
});
prompt1.addVariant(variant2);
variant2 = bedrock.PromptVariant.text(
variant_name="variant2",
model=claude_model,
prompt_variables=["topic"],
prompt_text="This is my second text prompt. Please summarize our conversation on: .",
inference_configuration={
"temperature": 0.5,
"topP": 0.999,
"maxTokens": 2000,
}
)
prompt.add_variant(variant2)
A prompt version is a snapshot of a prompt at a specific point in time that you create when you are satisfied with a set of configurations. Versions allow you to deploy your prompt and easily switch between different configurations for your prompt and update your application with the most appropriate version for your use-case.
You can create a Prompt version by using the PromptVersion class or by using the .createVersion(..) on a Prompt object. It is recommended to use the .createVersion(..) method. It uses a hash based mechanism to update the version whenever a certain configuration property changes.
new PromptVersion(prompt1, 'my first version');
bedrock.PromptVersion(self, "my first version")
or alternatively:
prompt1.createVersion('my first version');
prompt.create_version("version1", "my first version")
Amazon Bedrock intelligent prompt routing provides a single serverless endpoint for efficiently routing requests between different foundational models within the same model family. It can help you optimize for response quality and cost. They offer a comprehensive solution for managing multiple AI models through a single serverless endpoint, simplifying the process for you. Intelligent prompt routing predicts the performance of each model for each request, and dynamically routes each request to the model that it predicts is most likely to give the desired response at the lowest cost.
const variant = PromptVariant.text({
variantName: 'variant1',
promptText: 'What is the capital of France?',
model: PromptRouter.fromDefaultId(DefaultPromptRouterIdentifier.ANTHROPIC_CLAUDE_V1, region),
});
new Prompt(stack, 'Prompt', {
promptName: 'prompt-router-test',
variants: [variant],
});
variant = bedrock.PromptVariant.text(
variant_name='variant1',
prompt_text='What is the capital of France?',
model=bedrock.PromptRouter.from_default_id(bedrock.DefaultPromptRouterIdentifier.ANTHROPIC_CLAUDE_V1, region),
)
bedrock.Prompt(self, 'Prompt',
prompt_name='prompt-router-test',
variants=[variant],
)
| Method | Description |
|---|---|
addVariant(variant) |
Adds a variant to the prompt |
createVersion(description?) |
Creates a new version of the prompt with an optional description |
grantGet(grantee) |
Grants the given identity permissions to get the prompt |
| Method | Description |
|---|---|
PromptVariant.text(props) |
Creates a text prompt variant |
PromptVariant.chat(props) |
Creates a chat prompt variant |
PromptVariant.agent(props) |
Creates an agent prompt variant |
| Method | Description |
|---|---|
ChatMessage.user(text) |
Creates a user message |
ChatMessage.assistant(text) |
Creates an assistant message |
| Method | Description |
|---|---|
ToolChoice.ANY |
Allows the model to use any tool |
ToolChoice.AUTO |
Allows the model to automatically decide which tool to use |
ToolChoice.specificTool(toolName) |
Forces the model to use a specific tool |
You can use the fromPromptAttributes method to import an existing Bedrock Prompt into your CDK application.
// Import an existing prompt by ARN
const importedPrompt = bedrock.Prompt.fromPromptAttributes(this, 'ImportedPrompt', {
promptArn: 'arn:aws:bedrock:region:account:prompt/prompt-id',
kmsKeyArn: 'arn:aws:kms:region:account:key/key-id', // optional
promptVersion: '1', // optional, defaults to 'DRAFT'
});
# Import an existing prompt by ARN
imported_prompt = bedrock.Prompt.from_prompt_attributes(
self,
'ImportedPrompt',
prompt_arn='arn:aws:bedrock:region:account:prompt/prompt-id',
kms_key_arn='arn:aws:kms:region:account:key/key-id', # optional
prompt_version='1' # optional, defaults to 'DRAFT'
)