v0.130.0

The release adds new fields to several API objects including agent_type for Genie conversations, group_id for direct group members, effective_serverless_compute_id for job runs, and pipeline_channel for postgres pipelines. Four IAM v2 methods now include pagination (list_direct_group_members and list_workspace_assignment_details in both account and workspace APIs), which is a breaking change requiring code updates for existing callers.

The SDK expands IAM v2 capabilities with new methods for managing users, groups, service principals, and workspace assignments at both account and workspace levels. The new_cluster field in JobCluster is now optional (breaking change), and GenieSpace now includes creation and update timestamps.

Jobs API now supports trigger configuration through new fields for creating and tracking job triggers across multiple job objects. MLflow artifact location support for AI Runtime Tasks, enhanced pipeline connector options, and expanded GCP VPC Service Controls configuration were also added.

The SDK adds support for forwarding user access tokens in apps, custom docker images in job AI runtime tasks, and new gpu_xlarge_8 workload types for model serving. Breaking changes remove the include_browse parameter from catalog service APIs and make previously optional IAM identity fields like display_name, username, and account_sp_status required.

The Python SDK now supports enhanced billing configuration with principal overrides and resource filtering, adds NetSuite as a new catalog connection type, and enables input/output column mapping for pipeline transformers. Catalog policies also gained support for grant-based access control.

This release breaks compatibility by removing internal_id fields from IAM v2 objects and credential fields from model provider configurations, requiring updates to authentication and provider setup code. New ID fields replace the removed internal_id fields for groups, users, and service principals, and Kinesis stream support is added for ML pipelines.