Hivemind Manager

Hivemind Manager (hm) is a developer-focused process manager built on top of Hivemind.

It provides service discovery, dependency management, supervision, automatic restarts, log management, and project-aware workflows for local development environments.

Instead of manually managing multiple Hivemind processes, hm treats your workspace as a collection of services and provides a unified CLI for operating them.

Features

• Automatic discovery of *.hm service definitions
• Project-aware workspace detection
• Dependency resolution via # depends_on:
• Supervisor process with automatic restart backoff
• PID tracking and process lifecycle management
• Orphaned process cleanup
• Multi-service log management
• Execution-based log rotation
• Project-local configuration via pyproject.toml
• Works from any subdirectory inside a project
• Lightweight and Hivemind-compatible

Installation

From PyPI

pip install hivemind-manager==0.1.0

From Source

git clone git@github.com:dhruv13x/hivemind-manager.git
cd hivemind-manager
pip install -e .

Requirements

• Python 3.8+
• Hivemind installed and available on PATH

Verify installation:

hivemind --version

Quick Start

Inside your project:

hm init

This creates a project configuration:

[tool.hm]
home_dir = "hm"
preserve_logs = true
max_log_history = 5
max_log_size_mb = 0

Then start services:

hm up

Check status:

hm ps

Stop everything:

hm down

Service Definitions

Services are defined using standard Hivemind files.

Example: infra.hm

api: uvicorn app.main:app --host 0.0.0.0 --port 8000
worker: python -m app.worker

Example: transfer.hm

# depends_on: infra
transfer_bot: python -m services.transfer_bot.main

Dependency Management

Dependencies are declared using comments:

# depends_on: infra

When starting:

hm start transfer

hm automatically starts:

infra
└── transfer

if the dependency is not already running.

Project Discovery

hm automatically discovers project roots using:

1. HM_PROJECT_ROOT
2. pyproject.toml containing [tool.hm]
3. .hm service definitions
4. Current working directory

Commands work from anywhere inside the project:

cd scripts/dev
hm ps
hm start infra
hm logs transfer

Commands

Initialize Project

hm init

Create project configuration and HM workspace.

List Services

hm list

Example:

Detected services:

✓ infra
✓ transfer
✓ bypass
✓ uab

Show Status

hm ps

Example:

SERVICE         STATUS
----------------------
infra           running
transfer        running
uab             stopped

Start Service

hm start infra

Without log following:

hm start infra --no-follow

Stop Service

hm stop infra

Restart Service

hm restart infra

Without log following:

hm restart infra --no-follow

View Logs

hm logs infra

hm uses Inode-aware tailing, meaning the log stream persists across service restarts and rotations. You don't need to re-run the command when a service cycles.

Start All Services

hm up

Start all and follow combined logs:

hm up --follow

Stop All Services

hm down

Diagnostics

hm doctor

Example:

Project Root : /workspace/bot_platform
HM Home      : /workspace/bot_platform/hm
Config File  : /workspace/bot_platform/pyproject.toml
Hivemind Bin : /usr/local/bin/hivemind

Log Management

Each service receives:

hm/
├── infra.log
├── infra.log.1
├── infra.log.2
├── infra.pid

Execution-based rotation preserves previous runs:

• infra.log — current execution
• infra.log.1 — previous execution
• infra.log.2 — older execution

This makes debugging service restarts straightforward.

Configuration

Project configuration lives in pyproject.toml:

[tool.hm]
home_dir = "hm"
preserve_logs = true
max_log_history = 5
max_log_size_mb = 0

Environment Variables

Override configuration via environment:

Why Hivemind Manager?

Hivemind excels at running processes.

Hivemind Manager adds:

• Service-level supervision
• Dependency resolution
• Project discovery
• Log history
• Process cleanup
• Workspace-aware workflows

without replacing Hivemind itself.

License

MIT License
Copyright (c) dhruv13x