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MarketExpansionWorkflow

What it is​

  • A non-functional template workflow for “market expansion and penetration strategy”.
  • Provides a placeholder execute() implementation that returns a structured “template_only” response and logs warnings.

Public API​

  • MarketExpansionWorkflowConfiguration(WorkflowConfiguration)

    • Configuration dataclass for the workflow (currently empty).

  • MarketExpansionWorkflow(Workflow)

    • __init__(config: Optional[MarketExpansionWorkflowConfiguration] = None)
      • Initializes the workflow with a default configuration if none is provided.
      • Emits a warning that the workflow is not functional yet.
    • async execute(inputs: Dict[str, Any]) -> Dict[str, Any]
      • Template execution method.
      • Returns:
        • status: "template_only"
        • message: indicates non-functional state
        • planned_steps: list of placeholder steps
        • inputs_received: list of input keys received
    • get_workflow_description() -> str
      • Returns a multi-line description string for the workflow.

Configuration/Dependencies​

  • Depends on:
    • naas_abi_core.logger for warnings
    • naas_abi_core.workflow.workflow.Workflow and WorkflowConfiguration
  • Configuration:
    • MarketExpansionWorkflowConfiguration currently defines no fields (inherits from WorkflowConfiguration).

Usage​

import asyncio
from naas_abi_marketplace.domains.business-development-representative.workflows.MarketExpansionWorkflow import (
    MarketExpansionWorkflow,
)

async def main():
    wf = MarketExpansionWorkflow()
    result = await wf.execute(
        {
            "domain_specific_input": {"target_market": "EU"},
            "context": {"goal": "expansion"},
            "parameters": {"depth": "high"},
        }
    )
    print(result)

asyncio.run(main())

Caveats​

  • The workflow is explicitly marked “NOT FUNCTIONAL YET - template only”.
  • execute() does not perform real processing; it only returns planned steps and the keys of received inputs.
  • Instantiation and execution will emit warning logs via logger.warning().