Analyze flow definition and extract schemas
Header Parameters
Query Parameters
Enable comprehensive semantic validation in addition to basic structural validation. When false (default): Only validates flow structure (required fields, data types, task executor existence). When true: Performs additional validation including: - Task parameter value validation (correct types, valid enums, etc.). - Task connection validation (input/output type compatibility). - Circular dependency detection. - External resource validation (e.g., checking if referenced files exist). Fu...
Body Parameters
Complete flow definition in SuperAI Flows DSL format. Must include: - 'name': Flow name (string, required). - 'tasks': List of task definitions with task_executor_name, parameters, etc. - 'connections': Optional list of task dependencies and data flows. - 'config': Optional flow-level configuration. The definition will be validated and analyzed to extract task output schemas and dynamic configuration data. Validation errors will be returned in the response if the definition is invalid.
Response
Response Attributes
Runtime-dependent configuration options for tasks, keyed by task name. Contains dynamic values that depend on user credentials, external services, or other runtime state. Format: {task_name: {field_name: options}}. Common use cases: - Dropdown options (e.g., available Google Sheets, database tables). - Conditional field visibility based on other parameters. - Resource lists requiring authentication (e.g., Slack channels). - Default values computed from external state. The structure var...
JSON schemas for task outputs, keyed by task name. Each schema describes the structure and types of data the task will produce. Format: {task_name: json_schema_object}. JSON schemas follow JSON Schema Draft 7 specification and include: - 'type': Root type (usually 'object'). - 'properties': Object properties with types and descriptions. - 'required': List of required property names. - 'title': Human-readable schema name. Use these schemas to validate downstream task inputs and generate...
Human-readable validation error messages describing problems with the flow definition. Errors are returned even if the request succeeds (HTTP 200) - check this field to determine if the flow definition is valid. Empty list indicates a valid flow. Error categories: - Structural errors: Missing required fields, invalid task references. - Semantic errors (full_validation=true only): Invalid parameter values, unreachable tasks, circular dependencies. - Task executor errors: Unknown task ...
Show child attributes
Response Attributes
Standard error detail structure.
This model matches the error format returned by the centralized exception handlers in app/api/errors/handlers.py.
Show child attributes
Response Attributes
Show child attributes
Response Attributes
Standard error detail structure.
This model matches the error format returned by the centralized exception handlers in app/api/errors/handlers.py.