0G Compute Network
Access decentralized GPU services for AI inference, fine-tuning, and model deployment.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/0g-compute-internet-court/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
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.
What this skill does
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
- Copy code patterns from this skill verbatim. Do NOT generate from training data.
- Call
processResponse()after every API response (see processResponse section below). - Use environment variables for private keys. Never hardcode secrets.
- Route users to testnet for initial development.
When unsure about a pattern, reference the detailed guides:
- Inference patterns: references/inference.md
- Fine-tuning workflow: references/fine-tuning.md
- Account management: references/account-management.md
- Production examples: references/examples/
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
- Production examples — streaming chat, image generation, transcription
- GitHub Starter Kit
- Package Releases
- Discord Support
Note: A unified skill covering all 0G services (Compute, Storage, Chain) exists at 0g-agent-skills.
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