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Try the dApp and playground at http://46.17.103.110:3000/ ! You can use a private seed such as kexrupgtmbmwwzlcpqccemtgvolpzqezybmgaedaganynsnjijfyvcn.

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QuLang brings together AI builders across the Qubic blockchain. Its goal is to enable decentralized inference of Large Language Models (LLMs) and AI Agents. Here's how it works:

• Users can top up their QuLang accounts through the smart contract (procedure TopUp, 1) and withdraw their balance using the same mechanism (procedure Withdraw, 2).

• Providers can register endpoints for LLM inference following the Vercel AI SDK UI standard (an example is available in the example-openai-provider repository). The endpoints are stored in a centralized PostgreSQL database, while pricing (input token price, output token price) and burn rate parameters are managed by the smart contract (procedure updateProvider, 3).

• Inference transactions are validated through a main endpoint. Users with sufficient QuLang balances are debited an amount calculated by:

$$ D = n_{\text{input token}} \times p_{\text{input token}} + n_{\text{output token}} \times p_{\text{output token}} $$

The AI provider receives a credit of $D \times (1 - r_{\text{burn}})$, and the remaining amount $r_{\text{burn}} \times D$ is either burned or credited to the contract’s shares.

Important note: Some features, particularly security measures and exception handling, are not yet fully developed.

Projects

1. core (Node and Smart Contract)

A fork of the Qubic node with our smart contract implementation.

• Code: https://github.com/Qubic-Qulang/core/blob/madrid-2025/src/contracts/HM25.h
• Node endpoint: http://46.17.103.110:31841/
• RPC endpoint: http://46.17.103.110/v1/tick-info

2. qulang-app (Main dApp)

• URL: http://46.17.103.110:3000/
• Repository: https://github.com/Qubic-Qulang/qulang-app

3. example-openai-provider

• Endpoint instance: http://46.17.103.110:3001/
• Repository: https://github.com/Qubic-Qulang/example-openai-provider

This Next.js application demonstrates how AI providers can register with the QuLang marketplace. The API exposes model details (provider name, image, and description) via environment variables. It also includes a playground chatbot interface for easy testing and debugging of AI inference.