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0g Compute

OrganizationPopular
internet-court
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. Use this skill for any 0G compute, 0G AI, or decentralized GPU question.

Overview

Publisherinternet-court
Repositoryinternet-court-skill
Skill name0g-compute
Stars
5.8K
Forks
106
Bundled files
6
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by internet-court on GitHub. Read the source before you install it.

Installation

Install the 0g Compute AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/internet-court/internet-court-skill.git /tmp/internet-court-skill
mkdir -p .claude/skills
cp -r /tmp/internet-court-skill/vendored/0g/0g-compute .claude/skills/0g-compute
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 0g Compute in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 0g Compute on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 0g Compute is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

NetworkRPC URLInferenceFine-tuning
Mainnethttps://evmrpc.0g.aiYesYes
Testnethttps://evmrpc-testnet.0g.aiYesYes

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

bash
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

bash
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)

typescript
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.

typescript
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 TypechatID SourceFallback
ChatbotZG-Res-Key headerdata.id from response body
Text-to-ImageZG-Res-Key headernone
Speech-to-TextZG-Res-Key headernone
Chatbot StreamingZG-Res-Key headerid from stream chunk
Audio StreamingZG-Res-Key headernone

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.

bash
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

bash
# 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

ProblemSolution
Insufficient balancedeposit --amount 5 then transfer-fund --provider <ADDR> --amount 2
Provider not acknowledgedinference acknowledge-provider --provider <ADDR>
Provider busy (fine-tuning)Wait and retry, or choose a different provider
Web UI port conflictui start-web --port 3091

Resources

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 0g Compute AI skill do?

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.

Why use 0g Compute on TypingMind?

Because you install it once and use it with any model. 0g Compute is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 0g Compute in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/internet-court/internet-court-skill/tree/main/vendored/0g/0g-compute. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 0g Compute?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 0g Compute?

As many as you like. As long as a model supports skills, you can use 0g Compute with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 0g Compute AI skill free?

It is published on GitHub by internet-court. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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