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# What does this PR do? It avoids model_limit KeyError while trying to get embedding models for Watsonx <!-- If resolving an issue, uncomment and update the line below --> Closes https://github.com/llamastack/llama-stack/issues/4059 ## Test Plan <!-- Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.* --> Start server with watsonx distro: ```bash llama stack list-deps watsonx | xargs -L1 uv pip install uv run llama stack run watsonx ``` Run ```python client = LlamaStackClient(base_url=base_url) client.models.list() ``` Check if there is any embedding model available (currently there is not a single one) |
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| .. | ||
| agents | ||
| datasetio | ||
| eval | ||
| files | ||
| inference | ||
| post_training | ||
| safety | ||
| tool_runtime | ||
| vector_io | ||
| __init__.py | ||