cetingokhan commented on code in PR #62816:
URL: https://github.com/apache/airflow/pull/62816#discussion_r2901759000
##########
providers/common/ai/src/airflow/providers/common/ai/hooks/pydantic_ai.py:
##########
@@ -157,13 +187,229 @@ def test_connection(self) -> tuple[bool, str]:
"""
Test connection by resolving the model.
- Validates that the model string is valid, the provider package is
- installed, and the provider class can be instantiated. Does NOT make an
- LLM API call — that would be expensive, flaky, and fail for reasons
- unrelated to connectivity (quotas, billing, rate limits).
+ Validates that the model string is valid and the provider class can be
+ instantiated with the supplied credentials. Does NOT make an LLM API
+ call — that would be expensive and fail for reasons unrelated to
+ connectivity (quotas, billing, rate limits).
"""
try:
self.get_conn()
return True, "Model resolved successfully."
except Exception as e:
return False, str(e)
+
+
+class PydanticAIAzureHook(PydanticAIHook):
+ """
+ Hook for Azure OpenAI via pydantic-ai.
+
+ Connection fields:
+ - **password**: Azure API key
+ - **host**: Azure endpoint (e.g.
``https://<resource>.openai.azure.com``)
+ - **extra** JSON::
+
+ {"model": "azure:gpt-4o", "api_version": "2024-07-01-preview"}
+
+ :param llm_conn_id: Airflow connection ID.
+ :param model_id: Model identifier, e.g. ``"azure:gpt-4o"``.
+ """
+
+ conn_type = "pydanticaiazure"
+ default_conn_name = "pydanticai_azure_default"
+ hook_name = "Pydantic AI (Azure OpenAI)"
+
+ @staticmethod
+ def get_ui_field_behaviour() -> dict[str, Any]:
+ """Return custom field behaviour for the Airflow connection form."""
+ return {
+ "hidden_fields": ["schema", "port", "login"],
+ "relabeling": {"password": "API Key", "host": "Azure Endpoint"},
+ "placeholders": {
+ "host": "https://<resource>.openai.azure.com",
+ "extra": '{"model": "azure:gpt-4o", "api_version":
"2024-07-01-preview"}',
+ },
+ }
+
+ def _get_provider_kwargs(
+ self,
+ api_key: str | None,
+ base_url: str | None,
+ extra: dict[str, Any],
+ ) -> dict[str, Any]:
+ kwargs: dict[str, Any] = {}
+ if api_key:
+ kwargs["api_key"] = api_key
+ if base_url:
+ kwargs["azure_endpoint"] = base_url
+ if extra.get("api_version"):
+ kwargs["api_version"] = extra["api_version"]
+ return kwargs
+
+
+class PydanticAIBedrockHook(PydanticAIHook):
+ """
+ Hook for AWS Bedrock via pydantic-ai.
+
+ Credentials are resolved in order:
+
+ 1. IAM keys from ``extra`` (``aws_access_key_id`` +
``aws_secret_access_key``,
+ optionally ``aws_session_token``).
+ 2. Bearer token in ``extra`` (``api_key``, maps to env
``AWS_BEARER_TOKEN_BEDROCK``).
+ 3. Environment-variable / instance-role chain (``AWS_PROFILE``, IAM role,
…)
+ when no explicit keys are provided.
+
+ Connection fields:
+ - **extra** JSON::
+
+ {
+ "model": "bedrock:us.anthropic.claude-opus-4-5",
+ "region_name": "us-east-1",
+ "aws_access_key_id": "AKIA...",
+ "aws_secret_access_key": "...",
+ "aws_session_token": "...",
+ "profile_name": "my-aws-profile",
+ "api_key": "bearer-token",
+ "base_url": "https://custom-bedrock-endpoint";,
+ "aws_read_timeout": 60.0,
+ "aws_connect_timeout": 10.0
+ }
+
+ Leave ``aws_access_key_id`` / ``aws_secret_access_key`` and
``api_key``
+ empty to use the default AWS credential chain.
+
+ :param llm_conn_id: Airflow connection ID.
+ :param model_id: Model identifier, e.g.
``"bedrock:us.anthropic.claude-opus-4-5"``.
+ """
+
+ conn_type = "pydanticaibedrock"
+ default_conn_name = "pydanticai_bedrock_default"
+ hook_name = "Pydantic AI (AWS Bedrock)"
+
+ @staticmethod
+ def get_ui_field_behaviour() -> dict[str, Any]:
+ """Return custom field behaviour for the Airflow connection form."""
+ return {
+ "hidden_fields": ["schema", "port", "login", "host", "password"],
+ "relabeling": {},
+ "placeholders": {
+ "extra": (
+ '{"model": "bedrock:us.anthropic.claude-opus-4-5", '
+ '"region_name": "us-east-1"}'
+ " — leave aws_access_key_id empty for IAM role / env-var
auth"
+ ),
+ },
+ }
Review Comment:
I added a note because I thought changing the parameter names that Bedrock
users are used to might cause confusion.
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