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summary, read_when, title
| summary | read_when | title | ||
|---|---|---|---|---|
| Use Amazon Bedrock (Converse API) models with OpenClaw |
|
Amazon Bedrock |
Amazon Bedrock
OpenClaw can use Amazon Bedrock models via pi-ai's Bedrock Converse streaming provider. Bedrock auth uses the AWS SDK default credential chain, not an API key.
| Property | Value |
|---|---|
| Provider | amazon-bedrock |
| API | bedrock-converse-stream |
| Auth | AWS credentials (env vars, shared config, or instance role) |
| Region | AWS_REGION or AWS_DEFAULT_REGION (default: us-east-1) |
Getting started
Choose your preferred auth method and follow the setup steps.
**Best for:** developer machines, CI, or hosts where you manage AWS credentials directly.<Steps>
<Step title="Set AWS credentials on the gateway host">
```bash
export AWS_ACCESS_KEY_ID="AKIA..."
export AWS_SECRET_ACCESS_KEY="..."
export AWS_REGION="us-east-1"
# Optional:
export AWS_SESSION_TOKEN="..."
export AWS_PROFILE="your-profile"
# Optional (Bedrock API key/bearer token):
export AWS_BEARER_TOKEN_BEDROCK="..."
```
</Step>
<Step title="Add a Bedrock provider and model to your config">
No `apiKey` is required. Configure the provider with `auth: "aws-sdk"`:
```json5
{
models: {
providers: {
"amazon-bedrock": {
baseUrl: "https://bedrock-runtime.us-east-1.amazonaws.com",
api: "bedrock-converse-stream",
auth: "aws-sdk",
models: [
{
id: "us.anthropic.claude-opus-4-6-v1:0",
name: "Claude Opus 4.6 (Bedrock)",
reasoning: true,
input: ["text", "image"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 200000,
maxTokens: 8192,
},
],
},
},
},
agents: {
defaults: {
model: { primary: "amazon-bedrock/us.anthropic.claude-opus-4-6-v1:0" },
},
},
}
```
</Step>
<Step title="Verify models are available">
```bash
openclaw models list
```
</Step>
</Steps>
<Tip>
With env-marker auth (`AWS_ACCESS_KEY_ID`, `AWS_PROFILE`, or `AWS_BEARER_TOKEN_BEDROCK`), OpenClaw auto-enables the implicit Bedrock provider for model discovery without extra config.
</Tip>
**Best for:** EC2 instances with an IAM role attached, using the instance metadata service for authentication.
<Steps>
<Step title="Enable discovery explicitly">
When using IMDS, OpenClaw cannot detect AWS auth from env markers alone, so you must opt in:
```bash
openclaw config set plugins.entries.amazon-bedrock.config.discovery.enabled true
openclaw config set plugins.entries.amazon-bedrock.config.discovery.region us-east-1
```
</Step>
<Step title="Optionally add an env marker for auto mode">
If you also want the env-marker auto-detection path to work (for example, for `openclaw status` surfaces):
```bash
export AWS_PROFILE=default
export AWS_REGION=us-east-1
```
You do **not** need a fake API key.
</Step>
<Step title="Verify models are discovered">
```bash
openclaw models list
```
</Step>
</Steps>
<Warning>
The IAM role attached to your EC2 instance must have the following permissions:
- `bedrock:InvokeModel`
- `bedrock:InvokeModelWithResponseStream`
- `bedrock:ListFoundationModels` (for automatic discovery)
- `bedrock:ListInferenceProfiles` (for inference profile discovery)
Or attach the managed policy `AmazonBedrockFullAccess`.
</Warning>
<Note>
You only need `AWS_PROFILE=default` if you specifically want an env marker for auto mode or status surfaces. The actual Bedrock runtime auth path uses the AWS SDK default chain, so IMDS instance-role auth works even without env markers.
</Note>
Automatic model discovery
OpenClaw can automatically discover Bedrock models that support streaming
and text output. Discovery uses bedrock:ListFoundationModels and
bedrock:ListInferenceProfiles, and results are cached (default: 1 hour).
How the implicit provider is enabled:
- If
plugins.entries.amazon-bedrock.config.discovery.enabledistrue, OpenClaw will try discovery even when no AWS env marker is present. - If
plugins.entries.amazon-bedrock.config.discovery.enabledis unset, OpenClaw only auto-adds the implicit Bedrock provider when it sees one of these AWS auth markers:AWS_BEARER_TOKEN_BEDROCK,AWS_ACCESS_KEY_ID+AWS_SECRET_ACCESS_KEY, orAWS_PROFILE. - The actual Bedrock runtime auth path still uses the AWS SDK default chain, so
shared config, SSO, and IMDS instance-role auth can work even when discovery
needed
enabled: trueto opt in.
```json5
{
plugins: {
entries: {
"amazon-bedrock": {
config: {
discovery: {
enabled: true,
region: "us-east-1",
providerFilter: ["anthropic", "amazon"],
refreshInterval: 3600,
defaultContextWindow: 32000,
defaultMaxTokens: 4096,
},
},
},
},
},
}
```
| Option | Default | Description |
| ------ | ------- | ----------- |
| `enabled` | auto | In auto mode, OpenClaw only enables the implicit Bedrock provider when it sees a supported AWS env marker. Set `true` to force discovery. |
| `region` | `AWS_REGION` / `AWS_DEFAULT_REGION` / `us-east-1` | AWS region used for discovery API calls. |
| `providerFilter` | (all) | Matches Bedrock provider names (for example `anthropic`, `amazon`). |
| `refreshInterval` | `3600` | Cache duration in seconds. Set to `0` to disable caching. |
| `defaultContextWindow` | `32000` | Context window used for discovered models (override if you know your model limits). |
| `defaultMaxTokens` | `4096` | Max output tokens used for discovered models (override if you know your model limits). |
Quick setup (AWS path)
This walkthrough creates an IAM role, attaches Bedrock permissions, associates the instance profile, and enables OpenClaw discovery on the EC2 host.
# 1. Create IAM role and instance profile
aws iam create-role --role-name EC2-Bedrock-Access \
--assume-role-policy-document '{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": {"Service": "ec2.amazonaws.com"},
"Action": "sts:AssumeRole"
}]
}'
aws iam attach-role-policy --role-name EC2-Bedrock-Access \
--policy-arn arn:aws:iam::aws:policy/AmazonBedrockFullAccess
aws iam create-instance-profile --instance-profile-name EC2-Bedrock-Access
aws iam add-role-to-instance-profile \
--instance-profile-name EC2-Bedrock-Access \
--role-name EC2-Bedrock-Access
# 2. Attach to your EC2 instance
aws ec2 associate-iam-instance-profile \
--instance-id i-xxxxx \
--iam-instance-profile Name=EC2-Bedrock-Access
# 3. On the EC2 instance, enable discovery explicitly
openclaw config set plugins.entries.amazon-bedrock.config.discovery.enabled true
openclaw config set plugins.entries.amazon-bedrock.config.discovery.region us-east-1
# 4. Optional: add an env marker if you want auto mode without explicit enable
echo 'export AWS_PROFILE=default' >> ~/.bashrc
echo 'export AWS_REGION=us-east-1' >> ~/.bashrc
source ~/.bashrc
# 5. Verify models are discovered
openclaw models list
Advanced configuration
OpenClaw discovers **regional and global inference profiles** alongside foundation models. When a profile maps to a known foundation model, the profile inherits that model's capabilities (context window, max tokens, reasoning, vision) and the correct Bedrock request region is injected automatically. This means cross-region Claude profiles work without manual provider overrides.Inference profile IDs look like `us.anthropic.claude-opus-4-6-v1:0` (regional)
or `anthropic.claude-opus-4-6-v1:0` (global). If the backing model is already
in the discovery results, the profile inherits its full capability set;
otherwise safe defaults apply.
No extra configuration is needed. As long as discovery is enabled and the IAM
principal has `bedrock:ListInferenceProfiles`, profiles appear alongside
foundation models in `openclaw models list`.
You can apply [Amazon Bedrock Guardrails](https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails.html)
to all Bedrock model invocations by adding a `guardrail` object to the
`amazon-bedrock` plugin config. Guardrails let you enforce content filtering,
topic denial, word filters, sensitive information filters, and contextual
grounding checks.
```json5
{
plugins: {
entries: {
"amazon-bedrock": {
config: {
guardrail: {
guardrailIdentifier: "abc123", // guardrail ID or full ARN
guardrailVersion: "1", // version number or "DRAFT"
streamProcessingMode: "sync", // optional: "sync" or "async"
trace: "enabled", // optional: "enabled", "disabled", or "enabled_full"
},
},
},
},
},
}
```
| Option | Required | Description |
| ------ | -------- | ----------- |
| `guardrailIdentifier` | Yes | Guardrail ID (e.g. `abc123`) or full ARN (e.g. `arn:aws:bedrock:us-east-1:123456789012:guardrail/abc123`). |
| `guardrailVersion` | Yes | Published version number, or `"DRAFT"` for the working draft. |
| `streamProcessingMode` | No | `"sync"` or `"async"` for guardrail evaluation during streaming. If omitted, Bedrock uses its default. |
| `trace` | No | `"enabled"` or `"enabled_full"` for debugging; omit or set `"disabled"` for production. |
<Warning>
The IAM principal used by the gateway must have the `bedrock:ApplyGuardrail` permission in addition to the standard invoke permissions.
</Warning>
Bedrock can also serve as the embedding provider for
[memory search](/concepts/memory-search). This is configured separately from the
inference provider -- set `agents.defaults.memorySearch.provider` to `"bedrock"`:
```json5
{
agents: {
defaults: {
memorySearch: {
provider: "bedrock",
model: "amazon.titan-embed-text-v2:0", // default
},
},
},
}
```
Bedrock embeddings use the same AWS SDK credential chain as inference (instance
roles, SSO, access keys, shared config, and web identity). No API key is
needed. When `provider` is `"auto"`, Bedrock is auto-detected if that
credential chain resolves successfully.
Supported embedding models include Amazon Titan Embed (v1, v2), Amazon Nova
Embed, Cohere Embed (v3, v4), and TwelveLabs Marengo. See
[Memory configuration reference -- Bedrock](/reference/memory-config#bedrock-embedding-config)
for the full model list and dimension options.
- Bedrock requires **model access** enabled in your AWS account/region.
- Automatic discovery needs the `bedrock:ListFoundationModels` and
`bedrock:ListInferenceProfiles` permissions.
- If you rely on auto mode, set one of the supported AWS auth env markers on the
gateway host. If you prefer IMDS/shared-config auth without env markers, set
`plugins.entries.amazon-bedrock.config.discovery.enabled: true`.
- OpenClaw surfaces the credential source in this order: `AWS_BEARER_TOKEN_BEDROCK`,
then `AWS_ACCESS_KEY_ID` + `AWS_SECRET_ACCESS_KEY`, then `AWS_PROFILE`, then the
default AWS SDK chain.
- Reasoning support depends on the model; check the Bedrock model card for
current capabilities.
- If you prefer a managed key flow, you can also place an OpenAI-compatible
proxy in front of Bedrock and configure it as an OpenAI provider instead.