forked from phoenix-oss/llama-stack-mirror
# What does this PR do? IBM watsonx ai added as the inference [#1741 ](https://github.com/meta-llama/llama-stack/issues/1741) [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) --------- Co-authored-by: Sajikumar JS <sajikumar.js@ibm.com>
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watsonx Distribution
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self
The llamastack/distribution-watsonx 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::watsonx |
| safety | inline::llama-guard |
| 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 |
Environment Variables
The following environment variables can be configured:
LLAMASTACK_PORT: Port for the Llama Stack distribution server (default:5001)WATSONX_API_KEY: watsonx API Key (default: ``)WATSONX_PROJECT_ID: watsonx Project ID (default: ``)
Models
The following models are available by default:
meta-llama/llama-3-3-70b-instruct (aliases: meta-llama/Llama-3.3-70B-Instruct)meta-llama/llama-2-13b-chat (aliases: meta-llama/Llama-2-13b)meta-llama/llama-3-1-70b-instruct (aliases: meta-llama/Llama-3.1-70B-Instruct)meta-llama/llama-3-1-8b-instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)meta-llama/llama-3-2-11b-vision-instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)meta-llama/llama-3-2-1b-instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)meta-llama/llama-3-2-3b-instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)meta-llama/llama-3-2-90b-vision-instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)meta-llama/llama-guard-3-11b-vision (aliases: meta-llama/Llama-Guard-3-11B-Vision)
Prerequisite: API Keys
Make sure you have access to a watsonx API Key. You can get one by referring watsonx.ai.
Running Llama Stack with watsonx
You can do this via Conda (build code), venv 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=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ./run.yaml:/root/my-run.yaml \
llamastack/distribution-watsonx \
--yaml-config /root/my-run.yaml \
--port $LLAMA_STACK_PORT \
--env WATSONX_API_KEY=$WATSONX_API_KEY \
--env WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID \
--env WATSONX_BASE_URL=$WATSONX_BASE_URL
Via Conda
llama stack build --template watsonx --image-type conda
llama stack run ./run.yaml \
--port $LLAMA_STACK_PORT \
--env WATSONX_API_KEY=$WATSONX_API_KEY \
--env WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID