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Implement LangGraph Control Flow and Evaluation Integration
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Multi-Model Creative Brief Generation with LangChain and GPT-5 Pro
Format
Text-first
Lines
1
Sections
1
Linked challenge
Multi-Model Creative Brief Generation with LangChain and GPT-5 Pro
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Complete your LangGraph workflow by adding conditional edges and decision logic for agent handoffs and tool calls. Define how the Creative Director decides which section needs elaboration by the Creative Specialist or when a LocalAI tool should be invoked. Integrate a simple evaluation logging mechanism at the end of the workflow to capture the generated brief and model usage for Relicx (or a similar eval platform).
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.