forked from phoenix-oss/llama-stack-mirror
2.4 KiB
2.4 KiB
Bedrock Distribution
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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::code-interpreter, 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.
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.
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
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