forked from phoenix-oss/llama-stack-mirror

feat: Add watsonx inference adapter (#1895 )

# 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>

2025-04-25 11:29:21 -07:00

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watsonx Distribution

:maxdepth: 2
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self

The llamastack/distribution-{{ name }} distribution consists of the following provider configurations.

{% if run_config_env_vars %}

Environment Variables

The following environment variables can be configured:

{% for var, (default_value, description) in run_config_env_vars.items() %}

{{ var }}: {{ description }} (default: {{ default_value }}) {% endfor %} {% endif %}

{% if default_models %}

Models

The following models are available by default:

{% for model in default_models %}

{{ model.model_id }} {{ model.doc_string }} {% endfor %} {% endif %}

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-{{ name }} \
  --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

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