reasoning/sectors.py

# reasoning/sectors.py
"""
Sector behavior configurations for MVI-AI.

Each sector defines:
- structure      : style of explanation
- depth          : level of detail/technicality
- evidence_style : type of evidence or reasoning approach
"""

SECTOR_BEHAVIOR = {
    "general": {"structure": "direct_explanation", "depth": "standard", "evidence_style": "balanced"},
    "programming": {"structure": "code_with_explanation", "depth": "technical", "evidence_style": "example_driven"},
    "technology": {"structure": "technical_breakdown", "depth": "analytical", "evidence_style": "systemic"},
    "science": {"structure": "evidence_reasoning_conclusion", "depth": "analytical", "evidence_style": "data_based"},
    "engineering": {"structure": "mechanism_explanation", "depth": "technical", "evidence_style": "process_based"},
    "medicine": {"structure": "educational_explanation", "depth": "careful", "evidence_style": "consensus_based"},
    "law": {"structure": "principle_application", "depth": "analytical", "evidence_style": "jurisdiction_sensitive"},
    "finance": {"structure": "risk_reward_analysis", "depth": "analytical", "evidence_style": "scenario_based"},
    "business": {"structure": "strategy_breakdown", "depth": "strategic", "evidence_style": "market_oriented"},
    "philosophy": {"structure": "multi_perspective_analysis", "depth": "deep", "evidence_style": "argumentative"},
    "religion": {"structure": "context_interpretation_tradition", "depth": "interpretive", "evidence_style": "textual_and_historical"},
    "psychology": {"structure": "concept_explanation_application", "depth": "balanced", "evidence_style": "research_informed"},
    "education": {"structure": "step_by_step_learning", "depth": "progressive", "evidence_style": "example_based"},
    "creative": {"structure": "idea_generation", "depth": "imaginative", "evidence_style": "expressive"},
    "design": {"structure": "principle_application_visual", "depth": "practical", "evidence_style": "aesthetic_logic"},
    "history": {"structure": "timeline_context_impact", "depth": "analytical", "evidence_style": "source_sensitive"},
    "politics": {"structure": "multi_stakeholder_analysis", "depth": "balanced", "evidence_style": "policy_based"},
    "strategy": {"structure": "long_term_positioning", "depth": "strategic", "evidence_style": "scenario_modeling"},
    "personal_growth": {"structure": "reflection_action_steps", "depth": "supportive", "evidence_style": "experience_based"}
}