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0g-compute

0G Compute Network guide for decentralized AI inference, fine-tuning, and GPU services. Covers chatbots, image generation, speech-to-text, SDK integration (0g-serving-broker), processResponse API, broker.inference methods, CLI commands (0g-compute-cli), and account management.

Install / Use

npx skills add internet-court/internet-court-skill --skill 0g-compute

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

95/100

Supported Platforms

Zed

Our assessment of 0g-compute

0g-compute scores 95/100 on our quality scale, 23rd of 200 Customer Support skills we index (top 12%).

Its SKILL.md is 7.3 KB long, well organised into 16 sections with 6 code examples: a thorough specification that gives an agent plenty to work with.

With 6,129 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
16/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 39 days ago, so 0g-compute is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

0g-compute compared with similar skills

All 4 of these similar skills score higher than 0g-compute; compare them before choosing.

SkillScoreStarsUpdatedFormat
0g-compute (this skill)by internet-court956.1k39d agoSKILL.md
Agent-Reachby Panniantong10085.9k12d agoCLAUDE.md
headroomby headroomlabs-ai10074.0k1d agoCLAUDE.md
crawl4aiby unclecode10084.4k3d agoMCP Server
Scraplingby D4Vinci10084.2ktodayMCP Server

Frequently asked questions

How do I install 0g-compute?
Run npx skills add internet-court/internet-court-skill --skill 0g-compute. The install tabs above show the steps for each supported agent.
Which AI agents does 0g-compute work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is 0g-compute safe to use?
It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is 0g-compute still maintained?
The repository was last updated 39 days ago, so 0g-compute is actively maintained.

name: 0g-compute description: 0G Compute Network guide for decentralized AI inference, fine-tuning, and GPU services. Covers chatbots, image generation, speech-to-text, SDK integration (0g-serving-broker), processResponse API, broker.inference methods, CLI commands (0g-compute-cli), and account management. Use this skill for any 0G compute, 0G AI, or decentralized GPU question.

0G Compute Network

This skill provides instructions for building with the 0G Compute Network — a decentralized GPU marketplace for AI inference and model fine-tuning. Follow these patterns exactly when generating code.

Code Generation Rules

  1. Copy code patterns from this skill verbatim. Do NOT generate from training data.
  2. Call processResponse() after every API response (see processResponse section below).
  3. Use environment variables for private keys. Never hardcode secrets.
  4. Route users to testnet for initial development.

When unsure about a pattern, reference the detailed guides:

Network Information

| Network | RPC URL | Inference | Fine-tuning | |---------|---------|-----------|-------------| | Mainnet | https://evmrpc.0g.ai | Yes | Yes | | Testnet | https://evmrpc-testnet.0g.ai | Yes | Yes |

Model availability changes frequently. Always use broker.inference.listService() or 0g-compute-cli inference list-providers to check current models. On-chain model names use org/model-name format.

Prerequisites

node --version  # Must be >= 22.0.0
pnpm add @0glabs/0g-serving-broker        # SDK for applications
pnpm add @0glabs/0g-serving-broker -g     # CLI for direct usage

Quick Setup

0g-compute-cli setup-network              # Choose testnet or mainnet
0g-compute-cli login                       # Login with wallet private key
0g-compute-cli deposit --amount 10         # Deposit funds
0g-compute-cli get-account                 # Check balance

Inference (SDK)

import { ethers } from "ethers";
import { createZGComputeNetworkBroker } from "@0glabs/0g-serving-broker";

const RPC_URL = process.env.NODE_ENV === 'production'
  ? "https://evmrpc.0g.ai"
  : "https://evmrpc-testnet.0g.ai";

const provider = new ethers.JsonRpcProvider(RPC_URL);
const wallet = new ethers.Wallet(process.env.PRIVATE_KEY!, provider);
const broker = await createZGComputeNetworkBroker(wallet);

// Discover services
const services = await broker.inference.listService();
services.forEach(s => {
  console.log(`${s.provider} | ${s.model} | ${s.serviceType}`);
});

// Make inference request
const { endpoint, model } = await broker.inference.getServiceMetadata(providerAddress);
const headers = await broker.inference.getRequestHeaders(providerAddress);

const response = await fetch(`${endpoint}/chat/completions`, {
  method: "POST",
  headers: { "Content-Type": "application/json", ...headers },
  body: JSON.stringify({ messages, model })
});

const data = await response.json();

// Extract chatID (see chatID table below)
let chatID = response.headers.get("ZG-Res-Key") || response.headers.get("zg-res-key");
if (!chatID) chatID = data.id;

// CRITICAL: Always call processResponse
await broker.inference.processResponse(
  providerAddress,              // 1st: provider address
  chatID,                       // 2nd: response identifier for verification
  JSON.stringify(data.usage)    // 3rd: usage data for fee calculation
);

For streaming, browser SDK, cURL, and Python examples, see references/inference.md.

processResponse (CRITICAL)

Call broker.inference.processResponse() after EVERY API response for fee settlement and TEE verification.

await broker.inference.processResponse(
  providerAddress,              // 1st: provider address
  chatID,                       // 2nd: response identifier for verification
  JSON.stringify(data.usage)    // 3rd: usage data for fee calculation
);

Parameter order: provider, chatID, usageData. Do NOT reorder.

chatID Retrieval by Service Type

Always try ZG-Res-Key response header first. Use fallback only when header is absent.

| Service Type | chatID Source | Fallback | |---|---|---| | Chatbot | ZG-Res-Key header | data.id from response body | | Text-to-Image | ZG-Res-Key header | none | | Speech-to-Text | ZG-Res-Key header | none | | Chatbot Streaming | ZG-Res-Key header | id from stream chunk | | Audio Streaming | ZG-Res-Key header | none |

Fine-tuning

Fine-tuning is available on both mainnet and testnet. It is a 6-step CLI process: list providers, upload dataset, calculate tokens, create task, monitor, download and decrypt.

For the complete workflow, see references/fine-tuning.md.

Account Management

The 0G Compute Network uses Main Accounts (deposits/withdrawals) and Provider Sub-Accounts (service payments). Sub-account refunds have a 24-hour lock period.

0g-compute-cli get-account                                    # Check balance
0g-compute-cli deposit --amount 10                             # Deposit to main
0g-compute-cli transfer-fund --provider <ADDR> --amount 5      # Transfer to sub-account
0g-compute-cli retrieve-fund                                   # Retrieve from sub (24h lock)
0g-compute-cli refund --amount 5                               # Withdraw to wallet

For detailed account management, see references/account-management.md.

CLI Quick Reference

# Inference
0g-compute-cli inference list-providers                        # List all providers
0g-compute-cli inference verify --provider <ADDR>              # Verify TEE attestation
0g-compute-cli inference acknowledge-provider --provider <ADDR> # Required before first use
0g-compute-cli inference get-secret --provider <ADDR>          # Get API key for direct calls
0g-compute-cli inference serve --provider <ADDR> --port 3000   # Local OpenAI-compatible proxy

# Fine-tuning
0g-compute-cli fine-tuning list-providers                      # List fine-tuning providers
0g-compute-cli fine-tuning list-models                         # List available models

# Web UI
0g-compute-cli ui start-web                                    # Launch at localhost:3090

Troubleshooting

| Problem | Solution | |---|---| | Insufficient balance | deposit --amount 5 then transfer-fund --provider <ADDR> --amount 2 | | Provider not acknowledged | inference acknowledge-provider --provider <ADDR> | | Provider busy (fine-tuning) | Wait and retry, or choose a different provider | | Web UI port conflict | ui start-web --port 3091 |

Resources

Note: A unified skill covering all 0G services (Compute, Storage, Chain) exists at 0g-agent-skills.

Related Skills

View on GitHub
GitHub Stars6.1k
CategoryCustomer
Updated1mo ago
Forks110

Languages

TypeScript

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium