Inference Example

Example smart contract

Below is a smart contract that utilizes the IVannaInference interface to run inference on-chain.

import "valence-inference-lib/src/IInference.sol";

contract InferenceExample {

    // Execute an ML model from Valence's storage layer, secured by ZKML
    function runZkmlModel() public {
        ModelInput memory modelInput = ModelInput(
            new NumberTensor[](1),
            new StringTensor[](0));

        Number[] memory numbers = new Number[](2);
        numbers[0] = Number(7286679744720459, 17); // 0.07286679744720459
        numbers[1] = Number(4486280083656311, 16); // 0.4486280083656311

        modelInput.numbers[0] = NumberTensor("input", numbers);

        ModelOutput memory output = INFERENCE_CONTRACT.runModel(
            IInference.ModelInferenceMode.ZK,
            ModelInferenceRequest(
                "QmbbzDwqSxZSgkz1EbsNHp2mb67rYeUYHYWJ4wECE24S7A",
                modelInput
        ));

        if (output.is_simulation_result == false) {
            resultNumber = output.numbers[0].values[0];
        } else {
            resultNumber = Number(0, 0);
        }
    }

    // Execute a Large Language Model directly in your smart contract
    function runLlm() public {
        string[] memory stopSequence = new string[](1);
        stopSequence[0] = "<end>";

        LlmResponse memory llmResult = INFERENCE_CONTRACT.runLlm(
            IInference.LlmInferenceMode.VANILLA,
            LlmInferenceRequest(
                "meta-llama/Meta-Llama-3-8B-Instruct",
                "Hello sir, who are you?\n<start>",
                1000,
                stopSequence,
                0
        ));

        if (llmResuklt.is_simulation_result) {
            resultString = "empty";
        } else {
            resultString = llmResult.answer;
        }
    }
}