jeff3071 commented on code in PR #71437:
URL: https://github.com/apache/airflow/pull/71437#discussion_r3766334676
##########
providers/common/ai/src/airflow/providers/common/ai/hooks/pydantic_ai.py:
##########
@@ -160,30 +181,57 @@ def get_conn(self) -> Model:
provider_kwargs = self._get_provider_kwargs(api_key, base_url, extra)
if provider_kwargs:
- _kwargs = provider_kwargs # capture for closure
self.log.info(
"Using explicit credentials for provider with model '%s': %s",
model_name,
list(provider_kwargs),
)
-
- def _provider_factory(pname: str) -> Any:
- try:
- return infer_provider_class(pname)(**_kwargs)
- except TypeError:
- self.log.warning(
- "Provider '%s' rejected kwargs %s; falling back to
env-var auth",
- pname,
- list(_kwargs),
- )
- return infer_provider(pname)
-
- self._model = infer_model(model_name,
provider_factory=_provider_factory)
+ self._model = infer_model(
+ model_name,
+
provider_factory=self._create_provider_factory(provider_kwargs),
+ )
return self._model
self._model = infer_model(model_name)
return self._model
+ def get_embedder(self) -> Embedder:
Review Comment:
I updated `test_connection()` to validate the LLM model when configured and
fall back to the embedding model when no LLM model is configured.
If both are configured, `test_connection()` currently check only LLM.
Should `test_connection()` check both model instead?
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