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Posted to commits@airflow.apache.org by "vincbeck (via GitHub)" <gi...@apache.org> on 2026/09/04 15:16:41 UTC
[PR] Skip legacy models when selecting a Bedrock inference profile [airflow]
vincbeck opened a new pull request, #72521:
URL: https://github.com/apache/airflow/pull/72521
`get_text_inference_profile_arn()` returns the first "sonnet" inference profile in `list_inference_profiles` order. That order is not stable, and when it changed the helper started returning a profile backed by a model its provider had marked as legacy. Bedrock then rejects the request:
ValidationException: This Model is marked by provider as Legacy and you
have not been actively using the model in the last 30 days. Please upgrade
to an active model on Amazon Bedrock.
The inference profile summaries do not expose a lifecycle status, so look the legacy models up with `list_foundation_models` and skip any profile that resolves to one of them. Foundation model IDs are compared rather than ARNs because a global profile resolves to the same model in several regions.
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Re: [PR] Skip legacy models when selecting a Bedrock inference profile [airflow]
Posted by "vincbeck (via GitHub)" <gi...@apache.org>.
vincbeck commented on code in PR #72521:
URL: https://github.com/apache/airflow/pull/72521#discussion_r3968790019
##########
providers/amazon/tests/system/amazon/aws/utils/bedrock.py:
##########
@@ -37,11 +42,27 @@ def get_text_inference_profile_arn() -> str:
from airflow.providers.amazon.aws.hooks.bedrock import BedrockHook
client = BedrockHook().conn
+
+ # Bedrock rejects a model its provider marked as legacy, so a legacy model can not be relied on here.
+ # The inference profile summaries do not carry the lifecycle status, only the foundation models a
+ # profile resolves to do.
+ legacy_model_ids = {
+ model["modelId"]
+ for model in client.list_foundation_models()["modelSummaries"]
+ if model.get("modelLifecycle", {}).get("status") == "LEGACY"
+ }
+ log.info("Legacy model IDs: %s", sorted(legacy_model_ids))
+
profiles = client.list_inference_profiles(typeEquals="SYSTEM_DEFINED")["inferenceProfileSummaries"]
arns = [
Review Comment:
Sure
##########
providers/amazon/tests/system/amazon/aws/utils/bedrock.py:
##########
@@ -37,11 +42,27 @@ def get_text_inference_profile_arn() -> str:
from airflow.providers.amazon.aws.hooks.bedrock import BedrockHook
client = BedrockHook().conn
+
+ # Bedrock rejects a model its provider marked as legacy, so a legacy model can not be relied on here.
+ # The inference profile summaries do not carry the lifecycle status, only the foundation models a
+ # profile resolves to do.
+ legacy_model_ids = {
+ model["modelId"]
+ for model in client.list_foundation_models()["modelSummaries"]
+ if model.get("modelLifecycle", {}).get("status") == "LEGACY"
Review Comment:
Makes sense
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Re: [PR] Skip legacy models when selecting a Bedrock inference profile [airflow]
Posted by "ramitkataria (via GitHub)" <gi...@apache.org>.
ramitkataria commented on code in PR #72521:
URL: https://github.com/apache/airflow/pull/72521#discussion_r3937494291
##########
providers/amazon/tests/system/amazon/aws/utils/bedrock.py:
##########
@@ -37,11 +42,27 @@ def get_text_inference_profile_arn() -> str:
from airflow.providers.amazon.aws.hooks.bedrock import BedrockHook
client = BedrockHook().conn
+
+ # Bedrock rejects a model its provider marked as legacy, so a legacy model can not be relied on here.
+ # The inference profile summaries do not carry the lifecycle status, only the foundation models a
+ # profile resolves to do.
+ legacy_model_ids = {
+ model["modelId"]
+ for model in client.list_foundation_models()["modelSummaries"]
+ if model.get("modelLifecycle", {}).get("status") == "LEGACY"
+ }
+ log.info("Legacy model IDs: %s", sorted(legacy_model_ids))
+
profiles = client.list_inference_profiles(typeEquals="SYSTEM_DEFINED")["inferenceProfileSummaries"]
arns = [
Review Comment:
Since the pick among non-legacy candidates still follows list_inference_profiles order, the model under test can change between runs. Would it make sense to add a deterministic tiebreak, e.g. sort the candidates and pick the oldest non-legacy Sonnet, so runs are reproducible and we don't land on a brand-new release before batch inference or RAG support it?
##########
providers/amazon/tests/system/amazon/aws/utils/bedrock.py:
##########
@@ -37,11 +42,27 @@ def get_text_inference_profile_arn() -> str:
from airflow.providers.amazon.aws.hooks.bedrock import BedrockHook
client = BedrockHook().conn
+
+ # Bedrock rejects a model its provider marked as legacy, so a legacy model can not be relied on here.
+ # The inference profile summaries do not carry the lifecycle status, only the foundation models a
+ # profile resolves to do.
+ legacy_model_ids = {
+ model["modelId"]
+ for model in client.list_foundation_models()["modelSummaries"]
+ if model.get("modelLifecycle", {}).get("status") == "LEGACY"
Review Comment:
Should we filter for just `ACTIVE` so that if there's a new state like `DEPRECATED` or something else, this would still keep working?
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Re: [PR] Skip legacy models when selecting a Bedrock inference profile [airflow]
Posted by "vincbeck (via GitHub)" <gi...@apache.org>.
vincbeck merged PR #72521:
URL: https://github.com/apache/airflow/pull/72521
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