Struct FederatedCoordinator 

pub struct FederatedCoordinator { /* private fields */ }

Federated learning coordinator

Aggregates learning from multiple ephemeral agents.

Implementations

impl FederatedCoordinator

pub fn new(coordinator_id: impl Into<String>, config: SonaConfig) -> Self

Create a new federated coordinator

pub fn default_coordinator( coordinator_id: impl Into<String>, hidden_dim: usize, ) -> Self

Create with default config for coordination

pub fn coordinator_id(&self) -> &str

Get coordinator ID

pub fn set_quality_threshold(&mut self, threshold: f32)

Set quality threshold for accepting trajectories

pub fn set_consolidation_interval(&mut self, interval: usize)

Set consolidation interval

pub fn master_engine(&self) -> &SonaEngine

Get master engine reference

pub fn aggregate(&mut self, export: AgentExport) -> AggregationResult

Aggregate agent export into coordinator

pub fn force_consolidate(&self) -> String

Force consolidation

pub fn get_initial_patterns(&self, k: usize) -> Vec<LearnedPattern>

Get initial state for new agents

Returns learned patterns that new agents can use for warm start.

pub fn get_all_patterns(&self) -> Vec<LearnedPattern>

Get all learned patterns

pub fn stats(&self) -> CoordinatorStats

Get coordinator statistics

pub fn contributions(&self) -> &HashMap<String, AgentContribution>

Get contribution history

pub fn metrics(&self) -> &TrainingMetrics

Get metrics

pub fn agent_count(&self) -> usize

Get total number of contributing agents

pub fn total_trajectories(&self) -> usize

Get total trajectories aggregated

pub fn find_patterns(&self, query: &[f32], k: usize) -> Vec<LearnedPattern>

Find similar patterns

pub fn apply_lora(&self, input: &[f32]) -> Vec<f32>

Apply coordinator’s LoRA to input

pub fn consolidate(&self) -> String

Consolidate learning (alias for force_consolidate)

pub fn clear(&mut self)

Clear all contributions