Back to Prompt Library
implementation
Orchestrating Workflow with Ludwig and Human-in-the-Loop
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: AI-Powered Enterprise Content Review Agent
Format
Text-first
Lines
1
Sections
1
Linked challenge
AI-Powered Enterprise Content Review Agent
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Extend the agent's capabilities to orchestrate a content approval workflow using Ludwig. When a content piece fails initial review, the agent should be able to trigger a Ludwig workflow that involves a human expert for manual review and approval. Create a tool `trigger_ludwig_workflow(content_id: str, issues: list[str]) -> str`. Describe how this tool would interface with a Ludwig endpoint and how the agent would decide to use it. Provide the Python code for this new tool.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Hold the task contract and output shape stable so generated implementations remain comparable.
Tune next
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Verify after
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.