To use an embedding model deployed to AWS Bedrock service, specify the model endpoint name prefixed with bedrock: in the from field and include the required parameters in the params section.
| Parameter | Description |
|---|---|
aws_region | AWS region. Default: us-east-1. |
aws_profile | Optional. AWS profile to load credentials. |
aws_access_key_id | Optional. AWS access key ID for authentication. If not provided, credentials will be loaded from environment variables or IAM roles |
aws_secret_access_key | Optional. AWS secret access key for authentication. If not provided, credentials will be loaded from environment variables or IAM roles |
aws_session_token | Optional. AWS session token for authentication |
These parameters are used for Amazon Titan Text embedding model
| Parameter | Description |
|---|---|
normalize | Whether or not to normalize the output embedding. Defaults to true. |
dimensions | The number of dimensions the output embedding should have. The following values are accepted: 1024 (default), 512, 256. |
| Parameter | Description |
|---|---|
truncate | Specifies how the API handles inputs longer than the maximum token length. One of: START, END or NONE (default). |
input_type | Use the Cohere embeddings model optimized for different types of inputs. One of: search_document (default), search_query, classification or clustering. |
spicepod.yaml configuration, Cohere modelspicepod.yaml configuration, Titan modelRefer to the Amazon Bedrock documentation for more details on available models and configurations.