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DSPy Module for Fine-Tuning Script Generation

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Linked challenge: Orchestrate an AutoGen Agent Swarm for LLM Fine-Tuning & Deployment with Claude Opus 4.1 and MCP

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Linked challenge
Orchestrate an AutoGen Agent Swarm for LLM Fine-Tuning & Deployment with Claude Opus 4.1 and MCP

Prompt source

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Develop the DSPy modules for an 'FineTuningEngineerAgent' to generate optimized fine-tuning scripts based on input parameters (dataset_url, base_model, epochs, learning_rate). The DSPy program should ensure the generated script is robust, correct, and compatible with common LLM fine-tuning frameworks (e.g., Hugging Face Transformers).

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.