hugie 0.3.1

CLI for managing Hugging Face Inference Endpoints

Hugie 🐻

📖 Official documentation

Hugie is a Command Line Interface (CLI) for working with the Huggingface Inference Endpoints API (API docs)

Getting started

The package is pip installable and can be installed from PyPI

pipx install hugie

⚠️ To get started, you must set your individual or organisation Huggingface token into an env var called HUGGINGFACE_READ_TOKEN.

Usage 📺

tldr; watch the video:

Commands ⌨️

hugie
>>>
Usage: hugie [OPTIONS] COMMAND [ARGS]...

Options:
  --help                          Show this message and exit.

Commands:
  config
  endpoint
  version   Show version.

Endpoint

hugie endpoint --help
>>>
Usage: hugie endpoint[OPTIONS] COMMAND[ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  create  Create an endpoint
  delete  Delete an endpoint
  info    Get info about an endpoint
  list    List all the deployed endpoints
  logs    Get logs about an endpoint
  test    Test and endpoint
  update  Update an endpoint

Create

To create an endpoint:

hugie endpoint create examples/development.json

List

To list all your endpoints:

hugie endpoint list

# Use --json option to view all content

hugie endpoint list --json

Update

To update an endpoint, edit examples/development.json

hugie endpoint update development examples/development.json

Logs

To see the logs:

hugie endpoint logs development

Delete

To delete the endpoint

hugie endpoint delete development

this will ask you if you are sure you want to delete before moving forward. If you want to force the deletion you can use --force

JSON format

The endpoint create and endpoint update commands both require JSONs of the fomat:

{
  "accountId": null,
  "compute":
    "accelerator": "cpu",
    "instanceSize": "small",
    "instanceType": "c6i",
    "scaling": {
      "maxReplica": 1,
      "minReplica": 1
    }
  },
  "model": {
    "framework": "custom",
    "image": {
      "huggingface": {}
    },
    "repository": "t5-small",
    "revision": "main",
    "task": "text-classification"
  },
  "name": "aws-dev",
  "provider": {
    "region": "us-east-1",
    "vendor": "aws"
  },
  "type": "protected"
}

See examples/development.json for an example.

For development

Read our CONTRIBUTING.md then

Create a virtual environment and install the package

poetry install

Run tests

pytest

To upload to PyPi run

`` poetry publish

you need the mantisnlp password to proceed. Ask Nick or Matt.