| Step Details |
| Introduced in Version | 9.0.0 |
| Last Modified in Version | 9.12.0 |
| Location | AI > AWS Bedrock |
The Get Embedding for Text step obtains numerical vector representations (embeddings) for the given text input data. Text embeddings represent the semantic meaning of text, enabling various downstream natural language processing (NLP) tasks, such as text classification, clustering, or similarity analysis.
Prerequisites
This step requires the AWS Bedrock module to be installed before it will be available in the toolbox.
Version 9 users must install the AWS Bedrock dependency in order for these steps to appear.
Properties
AWS Bedrock Settings
| Property | Description | Data Type |
|---|
| Specify Model Name | When enabled, makes a dropdown box appear permitting the user to select the model that gets utilized. | Boolean |
| Specify Model Prefix Name | If the model name requires a prefix, enable this setting and add the prefix to the box that appears. | Boolean |
AWS Settings
| Property | Description | Data Type |
|---|
| Specify AWS Credentials | When enabled, creates two new inputs, AWS API Access Key and AWS API Secret Key forcing the user to input required credentials prior to a prompt running. | Boolean |
| AWS Region | Allows for region selection. | AmazonAWSRegion |
Inputs
| Property | Description | Data Type |
|---|
| Text to Process | The text that needs to be represented as vector embeddings. | String |
Outputs
| Property | Description | Data Type |
|---|
| Done |
|
|
| Resulting Embeddings | Numerical vector representations (embeddings) of the input text. | AITextEmbedding |
Example Inputs and Outputs
Step Changes
| Description | Version | Release Date | Developer Task |
|---|
A new property has been added to all AWS Bedrock steps called Specify Model Prefix Name.
| 9.12 | June 2025 | [DT-044585] |