Infernet Monorepo

This monorepo includes all of the libraries & frameworks used for building & running containers in Infernet Nodes.

Overview

Currently, the structure is as follows:

├── Makefile
├── README.md
├── scripts
├── tools
├── infernet_services # contains out-of-the-box usable infernet services
├── projects
│ ├── infernet_ml # code for infernet-ml library
│ ├── infernet_client # code for infernet-client library & CLI tool
│ └── ritual_arweave # code for ritual-arweave library & CLI tool
│ └── infernet_pyarweave # code for ritual-pyarweave library
├── pyproject.toml
├── requirements-dev.lock
└── requirements.lock

• libraries/: This directory contains all of the python projects.
  • infernet_ml/: Contains the code for the infernet-ml library.
  • infernet_client/: Contains the code for the infernet-client library & CLI tool.
  • ritual_arweave/: Contains the code for the ritual-arweave library & CLI tool.
  • infernet_pyarweave/: Contains the code for the infernet-pyarweave library.
• scripts/: Contains various makefile scripts used for
  • gcp.mk: To use gcloud artifact repository for pypi packages.
  • docs.mk: To generate documentation for the python projects.
  • pypi.mk: To build & publish python packages.
• tools/: Contains miscellaneous scripts used across the monorepo. Currently it contains a generate_docs.py script that generates files from the python projects.
• infernet_services/: Contains the code for various useful-reusable Infernet services as well as end-to-end tests for them. It also contains test_services that are used to test the infernet-node in isolation.
• pyproject.toml: This is the top-level pyproject.toml that is primarily used by rye to handle various tasks regarding monorepo management. This is akin to the top-level package.json file in JS monorepos.

Python Libraries

The libraries/ portion of this repository was scaffolded using rye. Rye comes with built-in support for packaging & installing python packages. It also has support for workspaces, which allows us to follow a monorepo structure where we have multiple python libraries in the same repository.

Usage: For documentation on the libraries as well as how to install them, please refer to the following links:

1. infernet-ml
2. `ritual-arweave
3. `infernet-client

The following sections detail how to work with the python libraries in this repository. That is how to build, test, and develop on them.

Pre-requisites

• Python 3.11
• Install uv.

Overview of the commands

All of the commands follow the format

make <command> library=<library-name>

Where <command> is the name the command & <library-name> is the name of the directory of the library.

For example, to run all the tests for the infernet-ml library, you would run:

make test-library library=infernet_ml

since the infernet-ml library is located in the libraries/infernet_ml directory.

Set up development environment

If developing on a library or running tests, you can set up the development environment by running:

make setup-library-env library=<library-name>

This will create a new uv environment under the .venv directory. Activate it by running:

source .venv/bin/activate

Running Tests for a Library

You can run tests for a library by running:

make test-library library=<library-name>

Building a Library

Following in the same theme, you can build a library by running:

make build-library library=<library-name>

This will create a dist folder and a .tar.gz file for the library.

Build System: Rye by default uses hatchling for packaging & creation of the libraries.

Publishing a Library

To publish a library, you can run:

make publish-library library=<library-name>

Note that you would need a pypi account and the necessary permissions to be able to publish a library.

Services

All of the services are located in the infernet_services directory. These services are out-of-the-box reusable services that cover many of the common use-cases for ML workflows.

For documentation on the services & how to use them, please refer to the Infernet Services Documentation.

For doing development on the services, you can follow the following sections.

Pre-requisites

1. Docker

Overview of the commands

All of the commands follow the format

make <command> service=<service-name>

Where <command> is the name the command & <service-name> is the name of the directory of the library.

For example, to run all the tests for the css_inference_service service, you would run:

make test-service service=css_inference_service

Testing Services

You can run tests for a service by running:

make test-service service=<service-name>

Building a Service

To build a service, you can run:

make build-service service=<service-name>

Running Services

To run a service you would have to configure it & deploy it via an Infernet node. To do so:

1. Create a config.json file under the infernet_services/deploy directory. To learn about the possible config params, refer to the configuration documentation.
2. Run the following command:

make deploy-node service=<service-name>

This will deploy the service along with the Infernet node..