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Implement Ray Tune and All Hands AI Interface
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Google ADK Agent for Sustainable Data Center Energy Monitoring
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Linked challenge
Google ADK Agent for Sustainable Data Center Energy Monitoring
Prompt source
Original prompt text with formatting preserved for inspection.
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Describe how you would use Ray Tune to optimize the parameters (e.g., anomaly detection thresholds, reporting frequency) of your ADK agent's energy analysis logic. Furthermore, explain how you would expose the agent's capabilities through an All Hands AI chat assistant, allowing users to query energy data and receive reports. Provide example snippets for agent configuration and chat interaction.
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.