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Lepton AI

A Python library and `lep` command-line interface for operating the NVIDIA DGX Cloud Lepton platform.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Lepton AI — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when AI workload deployment or operations need to be handled through Python or a command-line workflow connected to NVIDIA DGX Cloud Lepton.

Who it is for

  • Developers building AI services
  • Platform and ML engineers managing cloud workloads
  • Teams automating endpoint, job, cluster, storage, and secret operations

Documented uses

  • Create and inspect AI inference endpoints
  • Submit and monitor batch jobs
  • Launch GPU-backed development pods
  • Manage Ray clusters and fine-tuning jobs
  • Call deployed endpoints from Python
Before you choose

Requirements & limits

The repository is public and open source under the Apache-2.0 license. The documented setup installs with pip and uses `lep login` for workspace authentication. No pricing details are provided.

  • It targets NVIDIA DGX Cloud Lepton rather than functioning as a general, provider-neutral deployment library.
  • Endpoint authentication is represented separately from public IP reachability.
  • Teleport SSH workflows require tsh v18 or newer and additional workspace, cluster, or workload configuration.
  • The primary implementation language is Python, with CLI access through lep.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install Lepton AI and create an endpoint

Set up the library and CLI, authenticate to a workspace, and create an endpoint from a container image.

Before you start

  • Python package installation with pip
  • A Lepton workspace
  • A container image reference

Steps

  1. Install the library with the command below.

    Documented command
    pip install -U leptonai

  2. Run lep login to authenticate.

  3. Run lep endpoint create -n my-endpoint --container-image my-registry/my-app:latest.

  4. Run lep endpoint list and lep endpoint status -n my-endpoint to inspect the endpoint.

Expected outcome

An endpoint is created and its status can be inspected from the CLI.

Guide limitations

  • In workspaces with secure endpoint defaults, the endpoint may require an API token.
  • The generated token is printed by the create command and must be saved for authenticated clients.
  • The --public option controls IP reachability only; it does not disable API-token authentication.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
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Sources checked
30 September 2026
Original website title
leptonai/leptonai · Official homepage title · retained in its source language
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