Testing & Debugging Skills

Use when you need to customize how DSPy formats prompts for a specific provider — switching from chat to completion format, forcing JSON output, or debugging prompt rendering issues. Common scenarios - debugging why your prompt looks wrong when sent to the model, switching from OpenAI to Anthropic and the formatting breaks, forcing the model to return valid JSON instead of markdown, working with completion-style models that do not support chat format, customizing system messages, or handling models that choke on structured output instructions. Related - ai-switching-models, ai-following-rules, ai-parsing-data. Also used for prompt template rendering, how DSPy builds the prompt, custom system message in DSPy, JSON mode not working, model ignores format instructions, switch from chat to completion API, dspy.ChatAdapter, dspy.JSONAdapter, prompt formatting issues, debug what DSPy sends to the model, dspy.XMLAdapter, XML output format.

Use when you need maximum quality from a smaller/cheaper model — generates training data from a teacher model and fine-tunes a student model weights. Common scenarios - distilling GPT-4 quality into a cheaper model, generating training data from a strong teacher to fine-tune a weak student, reducing inference costs by replacing an expensive model with a fine-tuned small one, or building a production model that is fast and cheap. Related - ai-fine-tuning, ai-cutting-costs, dspy-better-together. Also used for dspy.BootstrapFinetune, model distillation with DSPy, teacher-student training, fine-tune small model from GPT-4 outputs, reduce API costs with fine-tuning, generate training data then fine-tune, cheap model same quality, distill large model into small model, fine-tune Llama from GPT-4, production model training, move from API to self-hosted model.

Use Langtrace for DSPy observability and tracing. Use when you want to set up Langtrace, langtrace-python-sdk, auto-instrument DSPy, trace DSPy calls, LLM observability, app.langtrace.ai, or self-hosted tracing. Also used for langtrace setup, langtrace API key, pip install langtrace-python-sdk, DSPy tracing, auto-instrument DSPy, langtrace self-hosted, langtrace docker, trace LM calls, langtrace vs phoenix, langtrace cloud.