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Bittensor Subnet Template

Discord Chat License: MIT

The Incentivized Internet

Discord • Network • Research

Quickstarter template

This template contains all the required installation instructions, scripts, and files and functions for:

  • Building Bittensor subnets.
  • Creating custom incentive mechanisms and running these mechanisms on the subnets.

In order to simplify the building of subnets, this template abstracts away the complexity of the underlying blockchain and other boilerplate code. While the default behavior of the template is sufficient for a simple subnet, you should customize the template in order to meet your specific requirements.

Introduction

IMPORTANT: If you are new to Bittensor subnets, read this section before proceeding to Installation section.

The Bittensor blockchain hosts multiple self-contained incentive mechanisms called subnets. Subnets are playing fields in which:

  • Subnet miners who produce value, and
  • Subnet validators who produce consensus

determine together the proper distribution of TAO for the purpose of incentivizing the creation of value, i.e., generating digital commodities, such as intelligence or data.

Each subnet consists of:

  • Subnet miners and subnet validators.
  • A protocol using which the subnet miners and subnet validators interact with one another. This protocol is part of the incentive mechanism.
  • The Bittensor API using which the subnet miners and subnet validators interact with Bittensor's onchain consensus engine Yuma Consensus. The Yuma Consensus is designed to drive these actors: subnet validators and subnet miners, into agreement on who is creating value and what that value is worth.

This starter template is split into three primary files. To write your own incentive mechanism, you should edit these files. These files are:

  1. template/protocol.py: Contains the definition of the protocol used by subnet miners and subnet validators.
  2. neurons/miner.py: Script that defines the subnet miner's behavior, i.e., how the subnet miner responds to requests from subnet validators.
  3. neurons/validator.py: This script defines the subnet validator's behavior, i.e., how the subnet validator requests information from the subnet miners and determines the scores.

Example

The Bittensor Subnet 1 for Text Prompting is built using this template. See Bittensor Text-Prompting for how to configure the files and how to add monitoring and telemetry and support multiple miner types. Also see this Subnet 1 in action on Taostats explorer.

Installation

Before you proceed

Before you proceed with the installation of the subnet, note the following:

  • Use these instructions to run your subnet locally for your development and testing, or on Bittensor testnet or on Bittensor mainnet.
  • IMPORTANT: We strongly recommend that you first run your subnet locally and complete your development and testing before running the subnet on Bittensor testnet. Furthermore, make sure that you next run your subnet on Bittensor testnet before running it on the Bittensor mainnet.
  • You can run your subnet either as a subnet owner, or as a subnet validator or as a subnet miner.
  • IMPORTANT: Make sure you are aware of the minimum compute requirements for your subnet. See the Minimum compute YAML configuration.
  • Note that installation instructions differ based on your situation: For example, installing for local development and testing will require a few additional steps compared to installing for testnet. Similarly, installation instructions differ for a subnet owner vs a validator or a miner.

Install

Writing your own incentive mechanism

As described in Quickstarter template section above, when you are ready to write your own incentive mechanism, update this template repository by editing the following files. The code in these files contains detailed documentation on how to update the template. Read the documentation in each of the files to understand how to update the template. There are multiple TODOs in each of the files identifying sections you should update. These files are:

  • template/protocol.py: Contains the definition of the wire-protocol used by miners and validators.
  • neurons/miner.py: Script that defines the miner's behavior, i.e., how the miner responds to requests from validators.
  • neurons/validator.py: This script defines the validator's behavior, i.e., how the validator requests information from the miners and determines the scores.
  • template/forward.py: Contains the definition of the validator's forward pass.
  • template/reward.py: Contains the definition of how validators reward miner responses.

In addition to the above files, you should also update the following files:

  • README.md: This file contains the documentation for your project. Update this file to reflect your project's documentation.
  • CONTRIBUTING.md: This file contains the instructions for contributing to your project. Update this file to reflect your project's contribution guidelines.
  • template/__init__.py: This file contains the version of your project.
  • setup.py: This file contains the metadata about your project. Update this file to reflect your project's metadata.
  • docs/: This directory contains the documentation for your project. Update this directory to reflect your project's documentation.

Note The template directory should also be renamed to your project name.

Subnet Links

In order to see real-world examples of subnets in-action, see the subnet_links.json document or access them from inside the template package by:

import template
template.SUBNET_LINKS
[{'name': 'sn0', 'url': ''},
 {'name': 'sn1', 'url': 'https://github.com/opentensor/text-prompting/'},
 {'name': 'sn2', 'url': 'https://github.com/bittranslateio/bittranslate/'},
 {'name': 'sn3', 'url': 'https://github.com/gitphantomman/scraping_subnet/'},
 {'name': 'sn4', 'url': 'https://github.com/manifold-inc/targon/'},
...
]

License

This repository is licensed under the MIT License.

# The MIT License (MIT)
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# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
# the Software.

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