Amazon Bedrock
Connect Amazon Bedrock to LLM-assisted labeling.
Create an Amazon Bedrock access policy
Create an IAM policy that grants permission to call Amazon Bedrock models. This is the only permission required for the extension.
Open the IAM page in AWS.
Go to Policies.
Click Create policy.

Switch to the JSON tab and paste the following:
Set up AWS credentials
Provide AWS credentials that include the policy created above. Choose one of the following options:
IAM User
Quick setup, personal use
Long-lived access keys you generate once
IAM Role
Production, shared environments
Temporary keys
IAM User
Create a dedicated IAM user and generate permanent access keys.
Open the IAM page in AWS.
Go to Users, then click Create user.
Attach the policy created earlier (either directly or through a group).

Go to the Security credentials tab.
Under Access keys, click Create access key.
Copy the Access Key ID and Secret Access Key.
IAM Role (Recommended)
IAM roles use temporary credentials that expire automatically, making them more secure for production use. This approach requires the AWS CLI.
Open the IAM in AWS.
Go to Roles, then click Create role.
Attach the policy you created earlier.
Generate temporary credentials:
Install and configure the AWS CLI (if you haven't already):
Ensure your CLI credentials have permission to assume the role.
Generate temporary credentials by running the following command. Replace
ACCOUNT_IDwith your 12-digit AWS account ID.
You'll get a response like this:
Start prediction
You should now have the required credentials. Copy the values from the response, enter them into the extension, then click Predict labels.
Access Key ID
AccessKeyId from the response
Secret Access Key
SecretAccessKey from the response
Session Token
SessionToken from the response, empty if you are using IAM User

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