Amazon
Bundles contain custom components that support specific third-party integrations with Langflow.
This page describes the components that are available in the Amazon bundle.
Amazon Bedrock
This component generates text using Amazon Bedrock LLMs.
It can output either a Model Response (Message) or a Language Model (LanguageModel).
Specifically, the Language Model output is an instance of ChatBedrock configured according to the component's parameters.
Use the Language Model output when you want to use an Amazon Bedrock model as the LLM for another LLM-driven component, such as an Agent or Smart Function component.
For more information, see Language Model components.
Amazon Bedrock parameters
Some parameters are hidden by default in the visual editor. You can modify all parameters through the Controls in the component's header menu.
| Name | Type | Description |
|---|---|---|
| input | String | Input parameter. The input string for text generation. |
| system_message | String | Input parameter. A system message to pass to the model. |
| stream | Boolean | Input parameter. Whether to stream the response. Only works in chat. Default: false. |
| model_id | String | Input parameter. The Amazon Bedrock model to use. |
| aws_access_key_id | SecretString | Input parameter. AWS Access Key for authentication. |
| aws_secret_access_key | SecretString | Input parameter. AWS Secret Key for authentication. |
| aws_session_token | SecretString | Input parameter. The session key for your AWS account. |
| credentials_profile_name | String | Input parameter. Name of the AWS credentials profile to use. |
| region_name | String | Input parameter. AWS region where your Bedrock resources are located. Default: us-east-1. |
| model_kwargs | Dictionary | Input parameter. Additional keyword arguments to pass to the model. |
| endpoint_url | String | Input parameter. Custom endpoint URL for a Bedrock service. |
Amazon Bedrock Embeddings
The Amazon Bedrock Embeddings component is used to load embedding models from Amazon Bedrock.
For more information about using embedding model components in flows, see Embedding Model components.
Amazon Bedrock Embeddings parameters
Some parameters are hidden by default in the visual editor. You can modify all parameters through the Controls in the component's header menu.
| Name | Type | Description |
|---|---|---|
| model_id | String | Input parameter. The ID of the model to call, such as amazon.titan-embed-text-v1. This is equivalent to the modelId property in the list-foundation-models API. |
| aws_access_key_id | SecretString | Input parameter. AWS Access Key for authentication. |
| aws_secret_access_key | SecretString | Input parameter. AWS Secret Key for authentication. |
| aws_session_token | SecretString | Input parameter. The session key for your AWS account. |
| credentials_profile_name | String | Input parameter. The name of the AWS credentials profile in ~/.aws/credentials or ~/.aws/config, which has access keys or role information. |
| region_name | String | Input parameter. The AWS region to use, such as us-west-2. Falls back to the AWS_DEFAULT_REGION environment variable or region specified in ~/.aws/config if not provided. |
| endpoint_url | String | Input parameter. The URL to set a specific service endpoint other than the default AWS endpoint. |
