RagMetricsResponse

pydantic model openapi_client.models.rag_metrics_response.RagMetricsResponse

Success body for GET /clusters/rag/metrics. Unlike the dwh and os metrics responses, which nest their payload under a Clusters key, this body is returned flat at the top level. Clients written against the os metrics shape will not work here unchanged. Which properties appear depends on the configured RAG vector store. An Aurora-backed store returns ClusterIdentifier and Engine; an OpenSearch Serverless store returns CollectionId, CollectionName and CollectionEndpoint. ClusterType, Status and Metrics are common to both. A failed metrics collection returns the Error property with an empty Metrics object. See the operation description for the status code this is returned with.

Fields:

• cluster_identifier (str | None)

• cluster_type (str | None)

• collection_endpoint (str | None)

• collection_id (str | None)

• collection_name (str | None)

• engine (str | None)

• error (str | None)

• metrics (openapi_client.models.rag_metrics_response_metrics.RagMetricsResponseMetrics | None)

• status (str | None)

field cluster_type: Optional[StrictStr] = None (alias 'ClusterType')

Label identifying the RAG vector store backing this response. Observed values are “RAG Aurora” and “RAG OpenSearch Serverless” on success, and “RDS Aurora” or “RAG OpenSearch Serverless” when metrics collection failed.

field cluster_identifier: Optional[StrictStr] = None (alias 'ClusterIdentifier')

Aurora DB cluster identifier. Returned for Aurora-backed stores only.

field engine: Optional[StrictStr] = None (alias 'Engine')

Aurora database engine. Returned for Aurora-backed stores only.

field collection_id: Optional[StrictStr] = None (alias 'CollectionId')

OpenSearch Serverless collection id. Returned for OpenSearch Serverless stores only.

field collection_name: Optional[StrictStr] = None (alias 'CollectionName')

OpenSearch Serverless collection name. Returned for OpenSearch Serverless stores only.

field collection_endpoint: Optional[StrictStr] = None (alias 'CollectionEndpoint')

OpenSearch Serverless collection endpoint. Returned for OpenSearch Serverless stores only.

field status: Optional[StrictStr] = None (alias 'Status')

Current state of the RAG vector store.

field metrics: Optional[RagMetricsResponseMetrics] = None (alias 'Metrics')

field error: Optional[StrictStr] = None (alias 'Error')

Present only when metrics collection failed, in which case Metrics is an empty object. Absent on success.

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of RagMetricsResponse from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of RagMetricsResponse from a dict

Return type:

Optional[Self]