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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>
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docs/source/distributions/remote_hosted_distro/watsonx.md
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docs/source/distributions/remote_hosted_distro/watsonx.md
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---
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orphan: true
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---
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<!-- This file was auto-generated by distro_codegen.py, please edit source -->
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# watsonx Distribution
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```{toctree}
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:maxdepth: 2
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:hidden:
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self
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```
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The `llamastack/distribution-watsonx` distribution consists of the following provider configurations.
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| API | Provider(s) |
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|-----|-------------|
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| agents | `inline::meta-reference` |
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| datasetio | `remote::huggingface`, `inline::localfs` |
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| eval | `inline::meta-reference` |
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| inference | `remote::watsonx` |
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| safety | `inline::llama-guard` |
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| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
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| telemetry | `inline::meta-reference` |
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| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
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| vector_io | `inline::faiss` |
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### Environment Variables
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The following environment variables can be configured:
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- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
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- `WATSONX_API_KEY`: watsonx API Key (default: ``)
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- `WATSONX_PROJECT_ID`: watsonx Project ID (default: ``)
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### Models
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The following models are available by default:
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- `meta-llama/llama-3-3-70b-instruct (aliases: meta-llama/Llama-3.3-70B-Instruct)`
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- `meta-llama/llama-2-13b-chat (aliases: meta-llama/Llama-2-13b)`
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- `meta-llama/llama-3-1-70b-instruct (aliases: meta-llama/Llama-3.1-70B-Instruct)`
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- `meta-llama/llama-3-1-8b-instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)`
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- `meta-llama/llama-3-2-11b-vision-instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)`
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- `meta-llama/llama-3-2-1b-instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)`
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- `meta-llama/llama-3-2-3b-instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)`
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- `meta-llama/llama-3-2-90b-vision-instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)`
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- `meta-llama/llama-guard-3-11b-vision (aliases: meta-llama/Llama-Guard-3-11B-Vision)`
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### Prerequisite: API Keys
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Make sure you have access to a watsonx API Key. You can get one by referring [watsonx.ai](https://www.ibm.com/docs/en/masv-and-l/maximo-manage/continuous-delivery?topic=setup-create-watsonx-api-key).
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## Running Llama Stack with watsonx
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You can do this via Conda (build code), venv or Docker which has a pre-built image.
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### Via Docker
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This method allows you to get started quickly without having to build the distribution code.
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```bash
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LLAMA_STACK_PORT=5001
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docker run \
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-it \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ./run.yaml:/root/my-run.yaml \
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llamastack/distribution-watsonx \
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--yaml-config /root/my-run.yaml \
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--port $LLAMA_STACK_PORT \
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--env WATSONX_API_KEY=$WATSONX_API_KEY \
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--env WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID \
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--env WATSONX_BASE_URL=$WATSONX_BASE_URL
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```
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### Via Conda
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```bash
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llama stack build --template watsonx --image-type conda
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llama stack run ./run.yaml \
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--port $LLAMA_STACK_PORT \
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--env WATSONX_API_KEY=$WATSONX_API_KEY \
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--env WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID
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```
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