This template contains all the required installation instructions, scripts, and files and functions for:
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:
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:
This starter template is split into three primary files. To write your own incentive mechanism, you should edit these files. These files are:
template/protocol.py: Contains the definition of the protocol used by subnet miners and subnet validators.neurons/miner.py: Script that defines the subnet miner's behavior, i.e., how the subnet miner responds to requests from subnet validators.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.The Bittensor Subnet 1 for Text Prompting is built using this template. See 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.
Before you proceed with the installation of the subnet, note the following:
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.template directory should also be renamed to your project name.To leverage the abstract SubnetsAPI in Bittensor, you can implement a standardized interface. This interface is used to interact with the Bittensor network and can be used by a client to interact with the subnet through its exposed axons.
What does Bittensor communication entail? Typically two processes, (1) preparing data for transit (creating and filling synapses) and (2), processing the responses received from the axon(s).
This protocol uses a handler registry system to associate bespoke interfaces for subnets by implementing two simple abstract functions:
prepare_synapseprocess_responsesThese can be implemented as extensions of the generic SubnetsAPI interface. E.g.:
This is abstract, generic, and takes(*args, **kwargs) for flexibility. See the extremely simple base class:
class SubnetsAPI(ABC):
def __init__(self, wallet: "bt.wallet"):
self.wallet = wallet
self.dendrite = bt.dendrite(wallet=wallet)
async def __call__(self, *args, **kwargs):
return await self.query_api(*args, **kwargs)
@abstractmethod
def prepare_synapse(self, *args, **kwargs) -> Any:
"""
Prepare the synapse-specific payload.
"""
...
@abstractmethod
def process_responses(self, responses: List[Union["bt.Synapse", Any]]) -> Any:
"""
Process the responses from the network.
"""
...
Here is a toy example:
from bittensor.subnets import SubnetsAPI
from MySubnet import MySynapse
class MySynapseAPI(SubnetsAPI):
def __init__(self, wallet: "bt.wallet"):
super().__init__(wallet)
self.netuid = 99
def prepare_synapse(self, prompt: str) -> MySynapse:
# Do any preparatory work to fill the synapse
data = do_prompt_injection(prompt)
# Fill the synapse for transit
synapse = StoreUser(
messages=[data],
)
# Send it along
return synapse
def process_responses(self, responses: List[Union["bt.Synapse", Any]]) -> str:
# Look through the responses for information required by your application
for response in responses:
if response.dendrite.status_code != 200:
continue
# potentially apply post processing
result_data = postprocess_data_from_response(response)
# return data to the client
return result_dataYou can use a subnet API to the registry by doing the following:
In order to see real-world examples of subnets in-action, see the subnet_links.py 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/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/'},
...
]This repository is licensed under the MIT License.
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