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# What does this PR do? This PR fixes issues with the WatsonX provider so it works correctly with LiteLLM. The main problem was that WatsonX requests failed because the provider data validator didn’t properly handle the API key and project ID. This was fixed by updating the WatsonXProviderDataValidator and ensuring the provider data is loaded correctly. The openai_chat_completion method was also updated to match the behavior of other providers while adding WatsonX-specific fields like project_id. It still calls await super().openai_chat_completion.__func__(self, params) to keep the existing setup and tracing logic. After these changes, WatsonX requests now run correctly. ## Test Plan The changes were tested by running chat completion requests and confirming that credentials and project parameters are passed correctly. I have tested with my WatsonX credentials, by using the cli with `uv run llama-stack-client inference chat-completion --session` --------- Signed-off-by: Sébastien Han <seb@redhat.com> Co-authored-by: Sébastien Han <seb@redhat.com> |
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| .. | ||
| __init__.py | ||
| agents.py | ||
| batches.py | ||
| datasetio.py | ||
| eval.py | ||
| files.py | ||
| inference.py | ||
| post_training.py | ||
| safety.py | ||
| scoring.py | ||
| telemetry.py | ||
| tool_runtime.py | ||
| vector_io.py | ||