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Develop Adaptive Thinking Budget Logic
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Linked challenge: Build Low-Latency Agentic Reasoning Workloads with OpenAI o3 and Langroid MCP
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Linked challenge
Build Low-Latency Agentic Reasoning Workloads with OpenAI o3 and Langroid MCP
Prompt source
Original prompt text with formatting preserved for inspection.
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Develop the logic within a Langroid agent that allows it to dynamically adjust its 'thinking budget' (e.g., number of reasoning steps, depth of chain-of-thought) based on an incoming task's `deadline_ms` and `priority` attributes. Demonstrate how OpenAI o3's prompt structure can be varied to achieve this adaptive behavior.
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.