Ruflo Swarm Distributed Agent Mesh

@ruvnet/ruflo · v3.1.0

A high-performance multi-agent swarm orchestration framework for DeepSeek Harness. Features dynamic DAG task distribution, shared episodic memory pools, and deterministic consensus protocols.

Multi-AgentSwarmDAGConcurrency
GitHub Stars
73 K+
+12.4% this month
Monthly Downloads
329 K+
Monthly registry pulls
Reach Score
99.4/ 100
Top Tier Ecosystem
Runtime
Cordis v3+
Node 18+ / Bun / Deno

Installation & Integration

CLI one-click launch, package managers, and Cordis integration

bash
manager:
$ pnpm add @ruvnet/ruflo

Architecture

Ruflo Swarm shatters the scalability limits of monolithic agents. When tackling complex refactors or multi-service architectures, a single LLM context quickly runs out of headroom and risks reasoning drift. This plugin implements a decentralized swarm communication mesh atop the Cordis bus. Tasks decompose into dynamic Directed Acyclic Graphs (DAGs) executed concurrently by specialized roles—Architect, Developer, QA Auditor, and Security Gatekeeper. Agent interactions adhere to strict RPC protocols with automatic backpressure control.

Architectural Principles & Constraints

01
Strict Type Isolation

Guaranteed by TypeScript compile-time contracts, inter-plugin event bus calls enjoy zero-drift safety.

02
Sub-Millisecond Hot Reload

Supports dynamic runtime mounting and graceful unloading without restarting the primary host process.

03
Deterministic State Machine

Embeds multi-phase execution lifecycle guards, preventing context loss during long-horizon reasoning.

04
Zero Native Build Dependencies

Designed for lightweight cross-platform environments, booting instantly across Node.js, Bun, and Deno.

Core Features

01
DAG Critical-Path Scheduler: Maximizes parallel throughput across non-blocking task trees
02
Isolated Worker Domains: Ensures sandboxed state isolation per subagent preventing collisions
03
CRDT-Powered State Sync: Enables conflict-free concurrent editing across multi-agent sessions
04
Automated Circuit Breaker: Suspends repeated worker failures and invokes replanning routines

Core Workflow

01

DAG Task Decomposition

Coordinator breaks target goals into modular DAG nodes with explicit dependency gates.

02

Role-Based Dispatch

Assigns specialist agents equipped with domain-specific tools and system prompts.

03

Concurrent Mesh Interop

Agents execute code and tests in parallel sandboxes, streaming artifacts over the bus.

04

Consensus Arbitration & Merge

Auditor verifies diff correctness, runs regression suites, and commits final solutions.

Configuration Parameters Reference (YAML / JSON)

ParameterTypeDefaultDescription
maxConcurrencynumber8Maximum number of concurrent subagents in swarm
timeoutPerTasknumber300Execution timeout limit per subtask in seconds
enableCRDTbooleantrueEnable CRDT-based conflict-free shared workspace

Use Cases

Enterprise Production Agent

Relies on microkernel lifecycle guards and fault-tolerant state machines for continuous reliability.

SWE-bench Benchmark Evaluation

Native integration with SWE-bench workflows, automatically capturing diffs and verification metrics.

Autonomous Code Refactoring

Separates reasoning from tool actions to independently locate and refactor multi-file codebases.

Cross-Tool Workflow Automation

Safely orchestrates events across sandboxes to seamlessly link enterprise developer tooling.

Best Practices

01
Sandbox Permission Guard

Strictly isolate sub-process calls and network scope; deploy within Docker containers in production.

02
Exponential Backoff Retries

Configure adaptive exponential retries with strict timeouts to mitigate upstream model rate limits.

03
Session State Checkpointing

Persist state machine snapshots to survive hardware interruptions and resume instantly without loss.

04
Full Trajectory Audit Logs

Enable full trace logging, aggregating reasoning thought streams and tool I/O into your observability hub.

FAQ

Q1:How to handle timeouts in long-running autonomous tasks?

Increase the timeout parameter inside your YAML configuration and dispatch periodic heartbeat signals across the Cordis event bus. For long-running tool execution and model reasoning, configure persistent session snapshotting so suspended tasks can safely resume their exact context after interruptions, preventing the kernel from recycling active agent sessions prematurely.

Q2:How to capture and stream the model reasoning thought process?

The harness runtime natively provides end-to-end streaming hooks while its state machine automatically intercepts and strips <think> reasoning tags from model responses. Subscribe directly to the onThink event listener to consume live reasoning token streams in real-time, delivering typewriter animation to the user interface while persisting full trajectories for audit compliance.

Q3:How to resolve dependency conflicts across multiple plugins?

Cordis microkernel uses directed acyclic graph topological sorting to dynamically resolve plugin dependencies. When shared services or runtime versions conflict, assign distinct isolated namespaces at the application entrypoint. Leveraging context injection alongside lazy activation ensures dependencies load strictly on-demand when tools are triggered, maintaining system stability and preventing memory bloat.

Q4:How to enforce permissions and sandbox isolation in production?

Combine isolated container sandboxing with fine-grained capability checks to prevent plugins from accessing sensitive files or unauthorized external networks. Enforce explicit runtime system call whitelisting through the microkernel, executing all third-party tool scripts inside isolated ephemeral containers to block arbitrary code execution and eliminate security privilege escalation risks entirely.

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