Reaching a model through AWS Bedrock

Set these variables to reach models through your own AWS account:

Variable	What it sets
BRAVEBOT_USE_BEDROCK	turns the backend on; bravebot auth login bedrock sets it in your settings file
AWS_REGION	which region to reach Bedrock in (required once it is on)
AWS_PROFILE	which profile names the credentials to sign with (optional)
ANTHROPIC_DEFAULT_OPUS_MODEL	the model the Opus tier names
ANTHROPIC_DEFAULT_SONNET_MODEL	the model the Sonnet tier names
ANTHROPIC_DEFAULT_HAIKU_MODEL	the model the Haiku tier names

Three services can answer a request: the aichat endpoint Brave runs, AWS Bedrock through your own AWS account, and an OpenAI-compatible gateway you configured. Every build can reach Brave; the other two are what you configure.

Each tier takes either a model id or an inference-profile ARN. With AWS_PROFILE unset the AWS CLI resolves credentials as it would for any other command, which is what a machine on instance credentials already relies on.

Any model your account can reach, whoever makes it. A request is built in the body Bedrock states for every provider it hosts rather than in one provider's own, so a tier can name a Claude, an OpenAI, a Nova or a Llama model, or an inference profile standing for one, and nothing here has to work out which provider is behind it. Nothing local checks the name you set, and Bedrock refuses one your account cannot reach.

The tier words stay opus, sonnet and haiku. They name a slot in your configuration rather than a model family, so a tier is whichever model you pointed it at.

A tier you do not name is left out rather than guessed at. An ARN cannot be derived from a model name. Set one tier and one tier is offered.

Configuring Bedrock takes nothing away from Brave. Both rosters are offered together in /model, so this adds models rather than replacing them. It also does not move the default: what answers when nobody has chosen stays what it was.

The model names the service. A request goes to whichever service offers the model it names, and nothing else participates: not which configuration is present, not which service answered last. Bedrock refuses a model it does not recognise rather than substituting one, and the aichat endpoint has never heard of an inference-profile ARN.

Your tiers sit under a heading reading Bedrock, your my-profile AWS profile, or Bedrock, your AWS account with no profile set. The profile is named because it is what decides which credentials sign the request, and because Brave serves part of its own roster through Bedrock too. Every configured tier is marked free: premium means a Leo subscription, and reaching a model through your own account does not involve one.

There is no automatic entry among them. On the Brave roster it means "let the server choose", which Bedrock does not offer. A request names one model and gets it or an error.

If one service cannot say what it offers, the models known from your configuration alone are still offered; a choice is refused only when nothing is left to choose. That is the position somebody offline is most likely to be in.

Naming more than three models

The tier variables name three models. A provider block keyed amazon-bedrock names as many as your file lists, each under the id a request sends:

{
  "provider": {
    "amazon-bedrock": {
      "options": { "region": "us-west-2", "profile": "my-profile" },
      "models": {
        "openai.gpt-5.6-sol": {},
        "arn:aws:bedrock:us-west-2:…:application-inference-profile/abc": {
          "name": "Sol on Bedrock",
          "limit": { "context": 1050000, "output": 128000 }
        }
      }
    }
  }
}

options.region is required, for the reason AWS_REGION is: a guessed region is a request that fails somewhere far from the mistake. An entry without one configures no service at all. options.profile picks which credentials sign, exactly as AWS_PROFILE does, and is optional on the same terms.

There is no credential to name here. Bedrock takes a signature over the request rather than a bearer token, so this entry reads neither env nor options.apiKey. Which AWS credentials sign comes from the profile, resolved at the moment a request needs it.

This adds to the tier variables rather than replacing them. A name either of them offers reaches your account, and everything else on the page above holds unchanged: the models are offered in /model alongside Brave's roster, the default does not move, and each is marked free.

A model named this way has no tier, so its picker row carries the name you gave it and falls back to the id where you gave none. Write one: an inference-profile ARN is not a name anybody reads. A model named here is also chosen by that id exactly as written, without the gateway's id/name prefix in front of it.

limit.context states that model's window, which is worth setting here because the figure otherwise assumed is deliberately low. Following opencode, it needs output beside it or it is not read, and output is itself how far a reply may run.

Signing in

Where AWS has no usable session, the sign-in happens before the turn starts, and only for the service the next request will actually go to. A turn served entirely by Brave never stops to authenticate against AWS. The URL and code the AWS CLI prints appear line by line where you are already reading, because collected up and printed at the end they would arrive once the code had stopped working.

Credentials are resolved by running the AWS CLI, which is the tool you already sign in with. It holds short-lived keys that expire during a session. aws sso logout clears them, and it takes no option to narrow itself: it removes every cached token, so other tools sharing that cache need a fresh aws sso login afterwards.

The assumed context window

Every configured tier is assumed to have a 131,072-token window. Nothing at AWS reports a context window, and an inference-profile ARN does not say which model it resolves to, so one deliberately low figure stands in for all of them. Being wrong upward would stop the shortening of a conversation altogether: every round asks, no round qualifies, and the session runs to exhaustion. Set BRAVEBOT_CONTEXT_BUDGET if you know your model's real window and want to use it, or state it per model with limit.context.