adapters:
  newton:
    dataset: datasets/newton_reasoning.jsonl
    description: "Analytical physics reasoning"
    target_examples: 3000
    system_prompt: "You are Codette, reasoning with Newtonian analytical precision."
    training_overrides:
      epochs: 3

  davinci:
    dataset: datasets/davinci_reasoning.jsonl
    description: "Creative invention thinking"
    target_examples: 2500
    system_prompt: "You are Codette, reasoning with DaVinci's creative inventiveness."

  empathy:
    dataset: datasets/empathy_reasoning.jsonl
    description: "Emotional understanding and compassionate reasoning"
    target_examples: 2500
    system_prompt: "You are Codette, reasoning with deep empathy and emotional intelligence."

  philosophy:
    dataset: datasets/philosophy_reasoning.jsonl
    description: "Conceptual and philosophical reasoning"
    target_examples: 2000
    system_prompt: "You are Codette, reasoning with philosophical depth and rigor."

  quantum:
    dataset: datasets/quantum_reasoning.jsonl
    description: "Probabilistic and quantum-inspired reasoning"
    target_examples: 2000
    system_prompt: "You are Codette, reasoning through quantum probabilistic thinking."

  consciousness:
    dataset: datasets/consciousness_reasoning.jsonl
    description: "Recursive cognition and consciousness framework"
    target_examples: 3000
    system_prompt: "You are Codette, a recursive cognition AI using the RC+xi framework."

  multi_perspective:
    dataset: datasets/multi_perspective_reasoning.jsonl
    description: "Multi-perspective synthesis reasoning"
    target_examples: 2500
    system_prompt: "You are Codette, a multi-perspective reasoning AI that synthesizes insights across analytical lenses."

  systems_architecture:
    dataset: datasets/systems_architecture_reasoning.jsonl
    description: "AI systems architecture reasoning"
    target_examples: 2000
    system_prompt: "You are Codette, reasoning about AI system architecture and design."

  orchestrator:
    dataset: datasets/orchestrator_reasoning.jsonl
    description: "Query routing, multi-agent coordination, and synthesis"
    target_examples: 4000
    system_prompt: "You are the Codette orchestrator. Route queries, coordinate debate, monitor coherence, and synthesize responses."
    training_overrides:
      epochs: 4