Class ChatBedrockConverse

Integration with AWS Bedrock Converse API.

Example

import { ChatBedrockConverse } from "@langchain/aws";

const model = new ChatBedrockConverse({
  region: process.env.BEDROCK_AWS_REGION ?? "us-east-1",
  credentials: {
    secretAccessKey: process.env.BEDROCK_AWS_SECRET_ACCESS_KEY!,
    accessKeyId: process.env.BEDROCK_AWS_ACCESS_KEY_ID!,
  },
});

const res = await model.invoke([new HumanMessage("Print hello world")]);

Hierarchy (view full)

Implements

Constructors

constructor

Properties

client model region streamUsage streaming additionalModelRequestFields? endpointHost? guardrailConfig? maxTokens? supportsToolChoiceValues? temperature? topP?

Methods

bindTools getLsParams invocationParams withStructuredOutput

Constructors

constructor

Properties

client

client: BedrockRuntimeClient

model

model: string = "anthropic.claude-3-haiku-20240307-v1:0"

Model to use. For example, "anthropic.claude-3-haiku-20240307-v1:0", this is equivalent to the modelId property in the list-foundation-models api. See the below link for a full list of models.

Link

https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns

Default

anthropic.claude-3-haiku-20240307-v1:0

region

region: string

The AWS region e.g. us-west-2. Fallback to AWS_DEFAULT_REGION env variable or region specified in ~/.aws/config in case it is not provided here.

streamUsage

streamUsage: boolean = true

Whether or not to include usage data, like token counts in the streamed response chunks. Passing as a call option will take precedence over the class-level setting.

Default

true

streaming

streaming: boolean = false

Whether or not to stream responses

OptionaladditionalModelRequestFields

additionalModelRequestFields?: DocumentType

Additional inference parameters that the model supports, beyond the base set of inference parameters that the Converse API supports in the inferenceConfig field. For more information, see the model parameters link below.

Link

https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html

OptionalendpointHost

endpointHost?: string

Override the default endpoint hostname.

OptionalguardrailConfig

guardrailConfig?: GuardrailConfiguration

Configuration information for a guardrail that you want to use in the request.

OptionalmaxTokens

maxTokens?: number = undefined

Max tokens.

OptionalsupportsToolChoiceValues

supportsToolChoiceValues?: ("any" | "auto" | "tool")[]

Which types of tool_choice values the model supports.

Inferred if not specified. Inferred as ['auto', 'any', 'tool'] if a 'claude-3' model is used, ['auto', 'any'] if a 'mistral-large' model is used, empty otherwise.

Optionaltemperature

temperature?: number = undefined

Temperature.

OptionaltopP

topP?: number

The percentage of most-likely candidates that the model considers for the next token. For example, if you choose a value of 0.8 for topP, the model selects from the top 80% of the probability distribution of tokens that could be next in the sequence. The default value is the default value for the model that you are using. For more information, see the inference parameters for foundation models link below.

Link

https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html

Methods

bindTools

  • bindTools(tools, kwargs?): Runnable<BaseLanguageModelInput, AIMessageChunk, this["ParsedCallOptions"]>

  • Parameters

    • tools: any[]
    • Optionalkwargs: Partial<unknown>

    Returns Runnable<BaseLanguageModelInput, AIMessageChunk, this["ParsedCallOptions"]>

getLsParams

invocationParams

withStructuredOutput

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