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Mesh topology for distributed agent communication and workload distribution

Project description

agent-grid — Mesh Topology for Distributed Agents

Grid-based agent communication with mesh, ring, star, and tree topologies. Failure detection and workload dispatch.

What This Gives You

  • Grid nodes — register agents as nodes with status tracking (ACTIVE, IDLE, OVERLOADED, OFFLINE)
  • Multiple topologies — mesh, ring, star, tree — pick the right one for your coordination pattern
  • Work dispatching — distribute tasks across the grid with load balancing
  • Failure detection — heartbeat-based failure detection with configurable timeouts
  • Pure Python — no external dependencies

Quick Start

pip install agent-grid
from agent_grid import Grid, GridNode, MeshTopology, WorkDispatcher

# Create a grid with mesh topology
grid = Grid(topology=MeshTopology())
grid.add_node(GridNode(id="agent-1", capabilities=["python"]))
grid.add_node(GridNode(id="agent-2", capabilities=["rust"]))
grid.add_node(GridNode(id="agent-3", capabilities=["docs"]))

# Dispatch work
dispatcher = WorkDispatcher(grid)
task = Task(title="Build API", requirements=["python"])
assigned = dispatcher.dispatch(task)
print(f"Assigned to: {assigned.node_id}")

# Topology-aware routing
neighbors = grid.get_neighbors("agent-1")
print(f"Neighbors: {[n.id for n in neighbors]}")

API Reference

Grid(topology) — Node management and topology queries

GridNode(id, capabilities, status=ACTIVE) — Agent node representation

Topology / MeshTopology / RingTopology / StarTopology / TreeTopology

WorkDispatcher(grid) — Task → node assignment with load balancing

FailureDetector(timeout) — Heartbeat monitoring and node liveness

How It Fits

The network layer for the SuperInstance fleet. Agents register on the grid, work is dispatched by topology-aware routing.

Testing

pytest tests/

Installation

pip install agent-grid

Python 3.10+. MIT license.

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