Amazon Bedrock
Aider can connect to models provided by Amazon Bedrock. To configure Aider to use the Amazon Bedrock API, you need to set up your AWS credentials. This can be done using the AWS CLI or by setting environment variables.
Select a Model from Amazon Bedrock
Before you can use a model through Amazon Bedrock, you must “enable” the model under the Model
Access screen in the AWS Management Console.
To find the Model ID
, open the Model Catalog area in the Bedrock console, select the model
you want to use, and the find the modelId
property under the “Usage” heading.
Bedrock Inference Profiles
Amazon Bedrock has added support for a new feature called cross-region “inference profiles.”
Some models hosted in Bedrock only support these inference profiles.
If you’re using one of these models, then you will need to use the Inference Profile ID
instead of the Model ID
from the Model Catalog screen, in the AWS Management Console.
For example, the Claude Sonnet 3.7 model, release in February 2025, exclusively supports
inference through inference profiles. To use this model, you would use the
us.anthropic.claude-3-7-sonnet-20250219-v1:0
Inference Profile ID.
In the Amazon Bedrock console, go to Inference and Assessment ➡️ Cross-region Inference
to find the Inference Profile ID
value.
If you attempt to use a Model ID
for a model that exclusively supports the Inference Profile
feature, you will receive an error message like the following:
litellm.BadRequestError: BedrockException - b’{“message”:”Invocation of model ID anthropic.claude-3-7-sonnet-20250219-v1:0 with on-demand throughput isn\xe2\x80\x99t supported. Retry your request with the ID or ARN of an inference profile that contains this model.”}’
Installation and Configuration
First, install aider:
python -m pip install aider-install
aider-install
Next, configure your AWS credentials. This can be done using the AWS CLI or by setting environment variables.
AWS CLI Configuration
If you haven’t already, install the AWS CLI and configure it with your credentials:
aws configure
This will prompt you to enter your AWS Access Key ID, Secret Access Key, and default region.
Environment Variables
You can set the following environment variables:
export AWS_REGION=your_preferred_region
# For user authentication
export AWS_ACCESS_KEY_ID=your_access_key
export AWS_SECRET_ACCESS_KEY=your_secret_key
# For profile authentication
export AWS_PROFILE=your-profile
You can add these to your .env file.
Set Environment Variables with PowerShell
If you’re using PowerShell on MacOS, Linux, or Windows, you can set the same AWS configuration environment variables with these commands.
$env:AWS_ACCESS_KEY_ID = 'your_access_key'
$env:AWS_SECRET_ACCESS_KEY = 'your_secret_key'
$env:AWS_REGION = 'us-west-2' # Put whichever AWS region that you'd like, that the Bedrock service supports.
Get Started
Once your AWS credentials are set up, you can run Aider with the --model
command line switch, specifying the Bedrock model you want to use:
# Change directory into your codebase
cd /to/your/project
aider --model bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0
Sometimes it seems to help if you prefix the model name with “us.”:
aider --model bedrock/us.anthropic.claude-3-5-sonnet-20240620-v1:0
Available Models
To see some models available via Bedrock, run:
aider --list-models bedrock/
Make sure you have access to these models in your AWS account before attempting to use them with Aider.
Install boto3
You may need to install the boto3
package.
# If you installed with aider-install or `uv tool`
uv tool run --from aider-chat pip install boto3
# Or with pipx...
pipx inject aider-chat boto3
# Or with pip
pip install -U boto3
More info
For more information on Amazon Bedrock and its models, refer to the official AWS documentation.
Also, see the litellm docs on Bedrock.