Update Workflow
Update an existing workflow’s configuration, nodes, or settings
Path Parameters
Query Parameters
Request Body
All fields are optional. Only provided fields will be updated.Response
Returns the updatedWorkflowResponse object.
Example Request
Notes
- Use
deploy=trueto immediately apply changes - Without
deploy=true, changes are staged and require a separate Deploy Workflow call
Query Parameters
Body
Request model for updating an existing workflow.
All fields are optional — only provide the fields you want to change. At least one field must be provided. The workflow type remains 'orchestration' and cannot be changed.
Response
Successful Response
Response model for workflow endpoints.
Inherits from AIAgent but excludes agent-specific fields that are not relevant to workflows (orchestrations). This provides a clean API surface for workflow consumers without exposing confusing agent-only concepts.
The workflow's execution logic is defined in orchestration_nodes — a DAG
of typed nodes. Agent-specific fields like graph, attached_tools,
delegation_* and framework are hidden.
Enumeration of the agent types.
Attributes: Manager: marks the agent as a Managing agent. Regular: marks the agent as a regular agent. A2A: marks the agent as an external agent used via A2A protocol. Curl: marks the agent as an external agent used via a CURL. Orchestration: marks the agent as an Orchestration object.
manager, regular, a2a, curl, orchestration Configuration for event-based notifications.
Attributes: on_success: Notifications to send when an operation succeeds. Maps notification types to a list of notification configurations. on_error: Notifications to send when an operation fails. Maps notification types to a list of notification configurations. on_budget: Notifications to send on budget threshold crossings. A dedicated category — budget alerts are not errors.
Configuration object for task-level execution strategies.
This model groups optional strategy configurations that control how a task is executed and managed over time, including retries, iterative execution, stopping conditions, and daily run limits.
Attributes: retry_strategy: Optional retry policy configuration that defines how the task should behave when execution fails (e.g., max attempts, backoff rules).

