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132 lines
4.3 KiB
Markdown
132 lines
4.3 KiB
Markdown
---
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parent: Connecting to LLMs
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nav_order: 560
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---
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# Amazon Bedrock
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Aider can connect to models provided by Amazon Bedrock.
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To configure Aider to use the Amazon Bedrock API, you need to set up your AWS credentials.
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This can be done using the AWS CLI or by setting environment variables.
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## Select a Model from Amazon Bedrock
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Before you can use a model through Amazon Bedrock, you must "enable" the model under the **Model
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Access** screen in the AWS Management Console.
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To find the `Model ID`, open the **Model Catalog** area in the Bedrock console, select the model
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you want to use, and the find the `modelId` property under the "Usage" heading.
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### Bedrock Inference Profiles
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Amazon Bedrock has added support for a new feature called [cross-region "inference profiles."](https://aws.amazon.com/about-aws/whats-new/2024/09/amazon-bedrock-knowledge-bases-cross-region-inference/)
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Some models hosted in Bedrock _only_ support these inference profiles.
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If you're using one of these models, then you will need to use the `Inference Profile ID`
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instead of the `Model ID` from the **Model Catalog** screen, in the AWS Management Console.
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For example, the Claude Sonnet 3.7 model, release in February 2025, exclusively supports
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inference through inference profiles. To use this model, you would use the
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`us.anthropic.claude-3-7-sonnet-20250219-v1:0` Inference Profile ID.
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In the Amazon Bedrock console, go to Inference and Assessment ➡️ Cross-region Inference
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to find the `Inference Profile ID` value.
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If you attempt to use a `Model ID` for a model that exclusively supports the Inference Profile
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feature, you will receive an error message like the following:
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> litellm.BadRequestError: BedrockException - b'{"message":"Invocation of model ID
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anthropic.claude-3-7-sonnet-20250219-v1:0 with on-demand throughput isn\xe2\x80\x99t supported. Retry your
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request with the ID or ARN of an inference profile that contains this model."}'
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## Installation and Configuration
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First, install aider:
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{% include install.md %}
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Next, configure your AWS credentials. This can be done using the AWS CLI or by setting environment variables.
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## AWS CLI Configuration
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If you haven't already, install the [AWS CLI](https://aws.amazon.com/cli/) and configure it with your credentials:
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```bash
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aws configure
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```
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This will prompt you to enter your AWS Access Key ID, Secret Access Key, and default region.
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## Environment Variables
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You can set the following environment variables:
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```bash
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export AWS_REGION=your_preferred_region
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# For user authentication
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export AWS_ACCESS_KEY_ID=your_access_key
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export AWS_SECRET_ACCESS_KEY=your_secret_key
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# For profile authentication
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export AWS_PROFILE=your-profile
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```
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You can add these to your
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[.env file](/docs/config/dotenv.html).
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### Set Environment Variables with PowerShell
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If you're using PowerShell on MacOS, Linux, or Windows, you can set the same AWS configuration environment variables with these commands.
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```pwsh
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$env:AWS_ACCESS_KEY_ID = 'your_access_key'
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$env:AWS_SECRET_ACCESS_KEY = 'your_secret_key'
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$env:AWS_REGION = 'us-west-2' # Put whichever AWS region that you'd like, that the Bedrock service supports.
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```
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## Get Started
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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:
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```bash
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# Change directory into your codebase
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cd /to/your/project
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aider --model bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0
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```
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Sometimes it seems to help if you prefix the model name with "us.":
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```bash
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aider --model bedrock/us.anthropic.claude-3-5-sonnet-20240620-v1:0
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```
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## Available Models
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To see some models available via Bedrock, run:
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```bash
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aider --list-models bedrock/
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```
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Make sure you have access to these models in your AWS account before attempting to use them with Aider.
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## Install boto3
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You may need to install the `boto3` package.
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```bash
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# If you installed with aider-install or `uv tool`
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uv tool run --from aider-chat pip install boto3
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# Or with pipx...
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pipx inject aider-chat boto3
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# Or with pip
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pip install -U boto3
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```
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# More info
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For more information on Amazon Bedrock and its models, refer to the [official AWS documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
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Also, see the
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[litellm docs on Bedrock](https://litellm.vercel.app/docs/providers/bedrock).
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