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TensorRT-LLM Deployment Strategy

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Linked challenge: DeepCode Architect: Multi-Model Code Generation & Optimization

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Linked challenge
DeepCode Architect: Multi-Model Code Generation & Optimization

Prompt source

Original prompt text with formatting preserved for inspection.

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Outline a deployment strategy for running your selected code generation LLMs (e.g., a Hugging Face model and OpenAI o3 via proxy) using TensorRT-LLM. Describe the steps for quantization, model compilation, and setting up an inference server that can be accessed by your DSPy program.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Preserve the source structure until you know which part of the prompt is actually driving the result quality.

Tune next

Change domain facts, examples, and tool context first before you rewrite the instruction scaffold.

Verify after

Validate one failure mode at a time so prompt changes stay attributable instead of getting noisy.