kyegomez/swarms

[feat][hiearchical_swarm][heartbeat and worker timeout with reassignment]

Open

#1,554 opened on Apr 21, 2026

View on GitHub
 (2 comments) (0 reactions) (0 assignees)Python (948 forks)github user discovery
FEATenhancementgood first issue

Repository metrics

Stars
 (6,809 stars)
PR merge metrics
 (PR metrics pending)

Description

Problem

Workers in HierarchicalSwarm that call external tools (MCP, browsers, shell) can hang indefinitely. There is no heartbeat, no timeout, and no reassignment — one stuck worker blocks the entire plan.

Proposed feature

  • Per-worker heartbeat interval (default 30s).
  • Per-subtask timeout (configurable on the swarm and overridable per subtask).
  • On timeout: cancel the worker's task, log the failure, and reassign the subtask to another worker (or mark it FAILED after N retries).

Design sketch

  • HierarchicalSwarm.__init__ gains worker_timeout: Optional[int] = None and heartbeat_interval: int = 30.
  • Worker execution wrapped in a ThreadPoolExecutor future with .result(timeout=...).
  • On concurrent.futures.TimeoutError, the subtask goes back into the queue with an incremented retry count.
  • After max_retries (default 2), the subtask is marked FAILED and surfaced in the judge verdict.

Files

  • swarms/structs/hiearchical_swarm.py

Why

Production deployments routinely hit hung workers when tools misbehave. Without timeouts, one bad worker kills the entire swarm run.

Contributor guide

Research direction
Examine the existing worker execution flow in `swarms/structs/hiearchical swarm.py`, then implement per worker heartbeat via a background thread and enforce per subtask timeout using `concurrent.futures.ThreadPoolExecutor` with a configurable timeout. On timeout, cancel the future, log the failure, and reassign the subtask with retry count. Ensure the worker pool and queue logic are updated accordingly.
Tech stack
python
Domain
backend
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
Pythonconcurrency
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
50