jeff3071 commented on code in PR #72002:
URL: https://github.com/apache/airflow/pull/72002#discussion_r4013739930
##########
providers/common/ai/src/airflow/providers/common/ai/hooks/llamaindex.py:
##########
@@ -172,14 +181,42 @@ def get_embedding_model(self) -> BaseEmbedding:
except ImportError as e:
raise AirflowOptionalProviderFeatureException(e)
+ reserved_keys = sorted(self.embedding_kwargs.keys() & {"model",
"model_name"})
+ if reserved_keys:
+ raise ValueError(
+ f"embedding_kwargs must not contain reserved keys
{reserved_keys}; use embed_model instead"
+ )
+ additional_kwargs = self.embedding_kwargs.get("additional_kwargs")
+ if isinstance(additional_kwargs, dict):
+ reserved_request_keys = sorted(additional_kwargs.keys() &
{"input", "model", "model_name"})
+ if reserved_request_keys:
+ raise ValueError(
+ "embedding_kwargs['additional_kwargs'] must not contain
reserved keys "
+ f"{reserved_request_keys}; model identity and input are
managed by the hook"
+ )
+
conn = self.get_connection(self.embed_conn_id)
model_id = self._resolve_model(
conn.extra_dejson,
constructor_value=self.embed_model,
extra_key="embed_model",
kind="embedding",
)
- return OpenAIEmbedding(model=model_id, **self._connection_kwargs(conn))
+ connection_kwargs = self._connection_kwargs(conn)
+ overridden_keys = sorted(self.embedding_kwargs.keys() &
connection_kwargs.keys())
Review Comment:
Agree, there is no reliable way to guard every override path because the
supported parameters and nesting vary by integration.
I removed the denylist and document `embedding_kwargs` would forward without
filtering and may override hook-provided values.
The remaining warnings cover:
- LangChain: `api_key`, `base_url`, `provider`.
- LlamaIndex: `api_key`, `api_base`.
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