Getting Started

What Is HiveMind Plugin Manager?

HiveMind Plugin Manager (HPM) is the extension layer that lets the HiveMind ecosystem swap its storage backend, agent integration, network transport, and binary data handling without changing core code. Every implementation - whether a JSON file database, a WebSocket server, or an audio handler - is a separate installable Python package that registers itself under a standardised setuptools entry-point group. HPM discovers those entry points at runtime and exposes factory classes so callers never need to hard-code import paths.

There are exactly five plugin types:

Type	Entry-point group	What it does
DATABASE	hivemind.database	Stores and retrieves Client credentials
AGENT_PROTOCOL	hivemind.agent.protocol	Bridges HiveMind messages to an AI backend
NETWORK_PROTOCOL	hivemind.network.protocol	Transports HiveMessage objects over a wire
BINARY_PROTOCOL	hivemind.binary.protocol	Handles raw binary payloads (audio, images, files)
POLICY	hivemind.policy	Admission-control: allow, deny, or mutate messages before they reach the bus

Source: hivemind_plugin_manager/__init__.py:10

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Install

pip install hivemind-plugin-manager

Runtime dependencies pulled in automatically: json_database, ovos-bus-client, ovos-utils, and hivemind-bus-client (via protocols).

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Verify Installation

from hivemind_plugin_manager import find_plugins, HiveMindPluginTypes

# Returns a dict of {plugin_name: class} for every installed DB plugin
print(find_plugins(HiveMindPluginTypes.DATABASE))

If you have hivemind-json-db-plugin installed you will see something like:

{'hivemind-json-db-plugin': <class 'json_database.hpm.JsonDB'>}

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Hello-World Plugin (Database)

The fastest way to understand HPM is to write a trivial database plugin and register it.

1. Implement the abstract class

# my_hpm_plugin/db.py
from typing import List, Iterable, Union
from hivemind_plugin_manager.database import AbstractDB, Client


class InMemoryDB(AbstractDB):
    def __init__(self, **kwargs):
        super().__init__(**kwargs)
        self._store: List[Client] = []

    def add_item(self, client: Client) -> bool:
        for i, c in enumerate(self._store):
            if c.client_id == client.client_id:
                self._store[i] = client
                return True
        self._store.append(client)
        return True

    def search_by_value(self, key: str,
                        val: Union[str, bool, int, float]) -> List[Client]:
        return [c for c in self._store if getattr(c, key, None) == val]

    def __len__(self) -> int:
        return len(self._store)

    def __iter__(self) -> Iterable[Client]:
        return iter(self._store)

2. Register the entry point

In setup.py (or pyproject.toml):

# setup.py
setup(
    name="my-hpm-plugin",
    ...
    entry_points={
        "hivemind.database": [
            "my-inmemory-db-plugin = my_hpm_plugin.db:InMemoryDB"
        ]
    }
)

3. Install and verify

pip install -e .
python -c "from hivemind_plugin_manager import find_plugins, HiveMindPluginTypes; print(find_plugins(HiveMindPluginTypes.DATABASE))"
# {'my-inmemory-db-plugin': <class 'my_hpm_plugin.db.InMemoryDB'>}

4. Instantiate via factory

from hivemind_plugin_manager import DatabaseFactory

db = DatabaseFactory.create("my-inmemory-db-plugin", name="clients", subfolder="hivemind-core")

DatabaseFactory.create - hivemind_plugin_manager/__init__.py:26

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CLI Tool: hpm

After installation a hpm command is available (entry point registered in setup.py:54):

hpm list database          # list installed database plugins
hpm get database           # show currently configured database plugin
hpm set database hivemind-json-db-plugin   # activate a plugin
hpm show-config            # dump full server.json

Config is stored in ~/.config/hivemind-core/server.json (XDG). See hivemind_plugin_manager/tui.py for full CLI implementation.

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