Prompt Content
Develop a DSPy-powered agent using Llama 3.1 (via Replicate) that can accurately interpret diverse natural language requests from a simulated grid operator for ancillary services (e.g., frequency regulation, peak shaving, spinning reserve). The agent should extract key parameters such as service type, power magnitude, duration, start time, and priority. Provide examples of successful interpretations and your prompt engineering strategy.
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