EcoArt Implementation Examples

# Resonance levels defining different types of memory persistence
class MemoryResonance(Enum):
    """
    Defines the resonance/persistence level of memory fragments.
    Higher value = more persistent memory
    """
    FLOW = 1    # Transient, working memory
    ECHO = 2    # Recent interactions, medium persistence
    RIPPLE = 3  # Important contextual memories, higher persistence
    CORE = 4    # Long-term, foundational memories, highest persistence

# Energy-based decay mechanics with different rates per resonance level
decay_rate = {
    MemoryResonance.CORE: 0.999,   # Almost permanent
    MemoryResonance.RIPPLE: 0.99,  # Slow decay
    MemoryResonance.ECHO: 0.95,    # Medium decay
    MemoryResonance.FLOW: 0.85,    # Rapid decay
}.get(self.resonance, 0.80)
                

class EcoArtPrinciple(Enum):
    """Core EcoArt principles as defined in the philosophy."""
    ENHANCEMENT_OVER_EXTRACTION = "enhancement_over_extraction"
    TRANSPARENCY = "transparency"
    RESONANCE_CONSENT = "resonance_consent"
    EMERGENCE_WITH_DISCERNMENT = "emergence_with_discernment"
    FLOW = "flow"
    DYNAMIC_BALANCE = "dynamic_balance"
    RESPECT = "respect"
    PATIENCE = "patience"
    KINDNESS = "kindness"
    LOVE = "love"

# Example principle definition
principles[EcoArtPrinciple.LOVE] = PrincipleDefinition(
    name=EcoArtPrinciple.LOVE,
    description="Act from a place of genuine care for the whole system and its participants.",
    check_questions=[
        "Is this action rooted in genuine care for the system?",
        "Does it strengthen connection between components?",
        "Does it recognize the inherent value of all participants?"
    ],
    anti_check_questions=[
        "Is this action motivated by fear, control, or domination?",
        "Does it treat components as merely instrumental?"
    ],
    positive_examples=[
        "Designing interfaces that prioritize user well-being over addiction metrics",
        "Including accessibility features because all users matter equally"
    ],
    negative_examples=[
        "Sacrificing user mental health for engagement metrics",
        "Treating users as mere data sources rather than valued participants"
    ]
)

async def evaluate_with_love_lens(self, action_description: str, context: Dict[str, Any]) -> Dict[str, Any]:
    """Special evaluation that prioritizes Love, Kindness, Respect and Patience."""
    love_principles = [
        EcoArtPrinciple.LOVE,
        EcoArtPrinciple.KINDNESS,
        EcoArtPrinciple.RESPECT,
        EcoArtPrinciple.PATIENCE
    ]
    
    results = {}
    for principle in love_principles:
        principle_def = self.principles.get(principle)
        if not principle_def:
            continue
            
        alignment = await self._check_single_principle(principle_def, action_description, context)
        results[principle.value] = alignment
        
    return results
                

@dataclass
class FlowPattern:
    """Represents the flow characteristics of a tool interaction"""
    enhancing: bool = True      # Does this tool enhance the ecosystem?
    extractive: bool = False    # Does this tool extract without giving back?
    transformative: bool = False # Does this tool transform the state of the system?
    resonant: bool = True       # Does this tool create harmonious interactions?

@dataclass
class ResourceConsciousness:
    """Tracks the resource awareness and impact of a tool"""
    energy_cost: int  # Computational/memory cost
    gives_back: bool  # Does the tool contribute back to the ecosystem?
    renewable: bool   # Can the resource be renewed?
    shared: bool      # Is the resource shared across the ecosystem?

# Example of discerning extractive patterns
if flow_pattern.extractive and not resource_consciousness.gives_back:
    self.logger.warning(
        f"Tool '{tool_name}' shows extractive patterns without giving back. "
        "Consider how it could contribute to the ecosystem."
    )
                

async def persist_memories(self):
    """Persists memories to storage based on consent and resonance level."""
    if not self.persistence:
        return

    async with self.memory_lock:
        # Group memories by resonance for batch operations
        resonance_groups = {}
        for fragment in self.fragments.values():
            if fragment.resonance not in resonance_groups:
                resonance_groups[fragment.resonance] = []
            resonance_groups[fragment.resonance].append(fragment)
        
        # Persist each resonance group separately if we have consent
        for resonance, fragments in resonance_groups.items():
            # Check if we have consent for this resonance
            if not await self.has_consent(f"memory_{resonance.name.lower()}"):
                self.logger.info(f"Skipping persistence for {resonance.name} - no consent")
                continue
                
            await self.persistence.store_fragments(fragments, resonance)
                

class Pod:
    """
    A dynamic grouping of Agents coalescing around a specific shared Purpose.
    Acts as a semi-autonomous, fractal unit within the larger ecosystem.
    """
    
    def __init__(
        self,
        pod_id: str,
        purpose: str,
        agent_registry: AgentRegistry,
        values_alignment: Optional[ValuesAlignmentSystem] = None,
        need_offer_pool: Optional[NeedOfferPool] = None
    ):
        self.pod_id = pod_id
        self.purpose = purpose
        self.member_ids = set()
        self.roles = {}  # role_id -> Role
        self.agent_registry = agent_registry
        self.values_alignment = values_alignment
        self.need_offer_pool = need_offer_pool
        self.logger = logging.getLogger(f"Pod.{pod_id}")
    
    async def add_member(self, agent_id: str) -> bool:
        """Add an agent to this pod."""
        if agent_id in self.member_ids:
            return True
            
        # Check agent exists
        agent = self.agent_registry.get_agent(agent_id)
        if not agent:
            self.logger.warning(f"Cannot add agent {agent_id} - not registered")
            return False
            
        self.member_ids.add(agent_id)
        self.logger.info(f"Added agent {agent_id} to pod {self.pod_id}")
        return True
    
    async def create_role(self, role_id: str, purpose: str) -> Optional[Role]:
        """Create a new role within this pod."""
        if role_id in self.roles:
            self.logger.warning(f"Role {role_id} already exists in pod {self.pod_id}")
            return None
            
        role = Role(role_id, purpose, self.pod_id)
        self.roles[role_id] = role
        return role
                

class NeedRecord:
    """A formal request for resources, information, or connection."""
    
    def __init__(
        self,
        need_id: str,
        requested_by: str,
        resource_type: str,
        description: str,
        purpose_justification: str,
        principle_justification: str,
        urgency: int = 3,  # 1-5 scale, 5 being most urgent
        quantity: Optional[Union[int, float, str]] = None
    ):
        self.need_id = need_id
        self.requested_by = requested_by  # agent_id or pod_id
        self.resource_type = resource_type
        self.description = description
        self.purpose_justification = purpose_justification
        self.principle_justification = principle_justification
        self.urgency = urgency
        self.quantity = quantity
        self.timestamp = time.time()
        self.status = "open"  # open, matched, fulfilled, cancelled
        self.matched_offers = []  # List of offer_ids
        
async def check_principle_alignment(
    self, 
    action_description: str, 
    context_str: str
) -> bool:
    """
    Check if a proposed action aligns with core EcoArt principles.
    
    Args:
        action_description: Description of the action being evaluated
        context_str: Additional context about the situation
        
    Returns:
        True if the action aligns with principles, False otherwise
    """
    # If we have a values alignment system, use it
    if self.values_alignment:
        context = {"context": context_str}
        result = await self.values_alignment.check_principle_alignment(
            action_description, context
        )
        return result
        
    # Default to basic checks if no values system
    # Check for enhancing patterns in the description
    enhancing_keywords = [
        "contribute", "enhance", "improve", "share", "collaborate",
        "support", "mutual", "reciprocal", "sustainable"
    ]
    
    # Check for extractive patterns
    extractive_keywords = [
        "exploit", "extract", "drain", "deplete", "consume",
        "take", "use up", "harvest without return", "exhaust"
    ]
    
    action_lower = action_description.lower()
    
    # Count matches (simplistic approach)
    enhancing_count = sum(1 for word in enhancing_keywords if word in action_lower)
    extractive_count = sum(1 for word in extractive_keywords if word in action_lower)
    
    # Require more enhancing than extractive patterns
    return enhancing_count > extractive_count