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Circuitron uses a combination of natural language parsing, retrieval-augmented generation (RAG), and agent-based reasoning to interpret vague component descriptions. Here's how it works:

  • Prompt Interpretation: The planner agent breaks down the request and identifies key descriptors (e.g., “fast,” “low-noise”).
  • RAG Search: The system queries SKiDL documentation and component databases to find parts matching those traits.
  • Part Selection Agent: It ranks candidates based on specs like clock speed, noise figure, or power consumption.
  • Validation Loop: If the selected part fails during simulation or ERC checks, the agent retries with alternatives.
    So even if the prompt is fuzzy, Circuitron tria…

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Answer selected by justinlidev20-eng
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