cerebro 1.1.10

An AI memory layer and multi-agent swarm engine in async Rust: specialized agents share working, episodic and semantic memory.
Documentation 
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//! # Swarm Sandbox (Sleep Cycles) — experimental, not implemented
//!
//! Planned: an isolated sandbox environment where agents can safely hallucinate
//! scenarios, test tools, and perform self-play reinforcement learning without
//! mutating the core production state.
//!
//! Only the API surface exists today. [`SandboxOrchestrator::simulate_scenario`]
//! does not run a simulation yet.

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

/// The sandbox orchestrator for isolated agent self-play (not implemented yet).
pub struct SandboxOrchestrator {
    /// When false, `simulate_scenario` returns immediately and prints nothing.
    pub enabled: bool,
}

impl SandboxOrchestrator {
    /// Create a sandbox orchestrator. Simulation is not implemented either way.
    pub fn new(enabled: bool) -> Self {
        Self { enabled }
    }

    /// Placeholder for running a sandbox simulation for a specific agent.
    ///
    /// Not implemented yet. If `enabled` is false, returns `Ok(())` at once.
    /// Otherwise prints a one-line notice to stderr and returns `Ok(())`.
    /// No memory is read or changed.
    pub async fn simulate_scenario(
        &self,
        agent: &AgentConfig,
        _scenario_prompt: &str,
    ) -> Result<()> {
        if !self.enabled {
            return Ok(());
        }

        // A full implementation 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.

        eprintln!(
            "[Sandbox] Scenario simulation is not implemented yet; nothing was run for agent [{}].",
            agent.name
        );

        Ok(())
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::swarm::agent::LlmProvider;
    use std::time::Duration;

    #[tokio::test]
    async fn test_simulate_scenario_is_noop() {
        let agent = AgentConfig {
            id: "dreamer".into(),
            name: "Dreamer".into(),
            system_prompt: "You test scenarios.".into(),
            model: LlmProvider::Ollama {
                model: "llama3".into(),
                base_url: "http://localhost:11434".into(),
            },
            tools: vec![],
            handoff_targets: vec![],
            max_steps: 1,
        };

        for enabled in [false, true] {
            let sandbox = SandboxOrchestrator::new(enabled);
            let result = tokio::time::timeout(
                Duration::from_millis(50),
                sandbox.simulate_scenario(&agent, "what if?"),
            )
            .await;
            assert!(matches!(result, Ok(Ok(()))));
        }
    }
}