cerebro 1.1.7

A blazing-fast AI memory layer that enables teams of specialized agents to collaborate through a shared cognitive architecture.
Documentation 
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//! # Swarm Sandbox (Sleep Cycles)
//!
//! Isolated sandbox environment where agents can safely hallucinate scenarios,
//! test tools, and perform self-play reinforcement learning without mutating
//! the core production state.

use super::agent::AgentConfig;
use crate::traits::Result;

/// The sandbox orchestrator manages isolated self-play for agents.
pub struct SandboxOrchestrator {
    pub enabled: bool,
}

impl SandboxOrchestrator {
    pub fn new(enabled: bool) -> Self {
        Self { enabled }
    }

    /// Run a sandbox simulation for a specific agent.
    pub async fn simulate_scenario(
        &self,
        agent: &AgentConfig,
        _scenario_prompt: &str,
    ) -> Result<()> {
        if !self.enabled {
            return Ok(());
        }

        println!(
            "🌙 [Sandbox] Agent [{}] entering sleep cycle...",
            agent.name
        );

        // In a full implementation, the sandbox would:
        // 1. Instantiate a temporary MemoryKVStore and CerebroMemoryBus.
        // 2. Feed the agent the scenario prompt.
        // 3. Let it execute using its tools (which would be mocked or safe-mode).
        // 4. Evaluate the success.
        // 5. If successful, extract the strategy and save to Semantic Memory.

        tokio::time::sleep(std::time::Duration::from_millis(500)).await;

        println!(
            "✨ [Sandbox] Agent [{}] derived new instinct from simulation.",
            agent.name
        );

        Ok(())
    }
}