<!-- This file was auto-generated by distro_codegen.py, please edit source -->
# Bedrock Distribution

```{toctree}
:maxdepth: 2
:hidden:

self
```

The `llamastack/distribution-bedrock` distribution consists of the following provider configurations:

| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::bedrock` |
| safety | `remote::bedrock` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::rag-runtime`, `remote::model-context-protocol` |
| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |



### Environment Variables

The following environment variables can be configured:

- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `8321`)

### Models

The following models are available by default:

- `meta.llama3-1-8b-instruct-v1:0 (aliases: meta-llama/Llama-3.1-8B-Instruct)`
- `meta.llama3-1-70b-instruct-v1:0 (aliases: meta-llama/Llama-3.1-70B-Instruct)`
- `meta.llama3-1-405b-instruct-v1:0 (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)`


### Prerequisite: API Keys

Make sure you have access to a AWS Bedrock API Key. You can get one by visiting [AWS Bedrock](https://aws.amazon.com/bedrock/).


## Running Llama Stack with AWS Bedrock

You can do this via Conda (build code) or Docker which has a pre-built image.

### Via Docker

This method allows you to get started quickly without having to build the distribution code.

```bash
LLAMA_STACK_PORT=8321
docker run \
  -it \
  --pull always \
  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
  llamastack/distribution-bedrock \
  --port $LLAMA_STACK_PORT \
  --env AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
  --env AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
  --env AWS_SESSION_TOKEN=$AWS_SESSION_TOKEN \
  --env AWS_DEFAULT_REGION=$AWS_DEFAULT_REGION
```

### Via Conda

```bash
llama stack build --template bedrock --image-type conda
llama stack run ./run.yaml \
  --port $LLAMA_STACK_PORT \
  --env AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
  --env AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
  --env AWS_SESSION_TOKEN=$AWS_SESSION_TOKEN \
  --env AWS_DEFAULT_REGION=$AWS_DEFAULT_REGION
```
