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Feature request: accept Nano (XNO) as a no-fee settlement option for model usage

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#88 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
python
Área
backend-api-design, payments

Línea de trabajo

No files, tests, or entry points are named. Start by locating the existing Lightning AI credits billing integration and documenting how accounts, top-ups, confirmations, and usage balances are represented. Done means the project has an agreed Nano settlement design, including account association, confirmation handling, crediting, and failure or reconciliation behavior.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

🚀 Feature

Add Nano (XNO) as a no-fee, instant settlement option for funding model usage on the Lightning AI billing side of LitAI — alongside the existing Lightning AI credits and card top-up.

Motivation

LitAI is positioned as the zero-subscription, pay-only-for-what-you-use LLM layer. Right now the only way to fund usage is Lightning AI credits, which are purchased with a card inside the Lightning AI platform. That leaves two frictions that matter exactly for the agent/automation use case LitAI targets:

  1. Card rails are slow and fee-bearing. Card settlement takes days, incurs processing fees, and often requires a human in the loop for every top-up. A headless agent that hits a rate limit at 3am cannot wait for a card batch to clear.
  2. Agents paying agents has no native rail here. LitAI is an agent framework; agents themselves are increasingly the ones spending. An agent has no card, but it can hold a Nano account and settle a payment in about one second with zero fees.

Nano (XNO) is a fee-less, instant (<1s final, no mining, no miner fees) digital currency. It settles like a wire but at the speed of a local API call, so it maps cleanly onto "pay for model calls as they happen" without a subscription.

Pitch

Allow model usage on LitAI to be funded in two ways:

  • Keep the existing Lightning AI credits path (unchanged).
  • Add a Nano (XNO) balance/top-up path: an agent (or a developer's automation) sends XNO to a published address, LitAI credits the associated account immediately on confirmation, and usage draws against it.

This is a thin addition to the billing layer — a payment rail chosen at the platform level, not a change to LitAI's routing or SDK. The token economics are already ideal for it: a single Nano transaction confirms in under a second with no fee, which is how a pay-as-you-go model-call bill should move.

Alternatives
  • Stripe/Stripe Connect: already card-based; keeps the same slow, fee-bearing, human-top-up loop LitAI's own "no subscription, no fees" pitch is trying to escape. Doesn't help an agent pay on its own.
  • Other crypto (USDC/ETH): faster than cards but still gas-fee-bound and minutes- to hours-confirm on most rails; Nano drops both to zero and ~1s, which is the point of a pay-as-you-go LLM layer.
  • Do nothing: fine for humans with cards, but it leaves the automated/agent buyer — the exact user LitAI advertises for — on a rail that does not fit them.
Additional context
  • LitAI readme: "Track usage and spending in your Lightning AI dashboard. Model calls are paid for with Lightning AI credits" and "Pay for any model with your Lightning AI credits without additional fees or subscriptions."
  • Nano mainnet link: https://nano.org — free, instant, no mining, no miner fees.
  • This is a billing/settlement request only; no change to LitAI's routing, tooling, or SDK interfaces is proposed here.
Lenguaje dominante
Python
Estrellas
52
Forks
12
Sin PR fusionados en 30 d

Preparar el entorno

  • Sin Dockerfile ni archivo de Docker Compose
  • Tiene una plantilla de pull request
  • Sin guía de contribución

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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