AI Inference extension

Chromia empowers developers by integrating AI inference capabilities directly into decentralized applications (dapps). This integration enables intelligent, real-time decision-making within the on-chain environment. By leveraging externally trained models for optimized inference, developers can seamlessly embed AI-driven logic into their dapps while upholding the core principles of blockchain: trustlessness and transparency. This fusion of blockchain security with artificial intelligence unlocks a new era of responsive and adaptive applications.

Configuring the blockchain in the dapp

To utilize this extension, configure your blockchain operations and queries. Here’s a sample configuration:

chromia.yml

blockchains:
  ai_inference_dapp: # Ensure this name is unique. Rename it if you encounter duplicate issues during deployment.
    module: main
    config:
      sync_ext:
        - "net.postchain.hybridcompute.HybridComputeSynchronizationInfrastructureExtension"
      gtx:
        modules:
          - "net.postchain.hybridcompute.HybridComputeGTXModule"
      hybridcompute:
        engine: "net.postchain.gtx.extensions.ai_inference.AiInferenceComputeEngine"
        load_timeout_seconds: 600 # Timeout in seconds for initial model loading
        compute_timeout_seconds: 600 # Timeout in seconds for each inference
      ai_inference:
        model_url: "https://djl-misc.s3.amazonaws.com/test/models/gpt2/gpt2_pt.zip" # Specify model URL here
        tokenizer_name: gpt2 # Specify tokenizer name here
        max_sequence_length: 60 # Max sequence length, see https://javadoc.io/static/ai.djl/api/0.32.0/ai/djl/modality/nlp/generate/SearchConfig.html#setMaxSeqLength(int)
        max_length: 512 # Length to truncate and/or pad sequences to, see https://javadoc.io/static/ai.djl.huggingface/tokenizers/0.32.0/ai/djl/huggingface/tokenizers/HuggingFaceTokenizer.Builder.html#optMaxLength(int)

Integrating with Rell

Incorporate the AI Inference extension library into your configuration as follows:

chromia.yml

libs:
  hybridcompute:
    registry: https://gitlab.com/chromaway/postchain-chromia
    path: chromia-infrastructure/rell/src/lib/hybridcompute
    tagOrBranch: 3.27.6
    rid: x"DF9EF3C9333D497F501B2D230CA0B9FD12F5288FA4E1D9F5DDBE916506543887"
    insecure: false
  ai_inference:
    registry: https://gitlab.com/chromaway/core/ai-inference-extension
    path: rell/src/lib/ai_inference
    tagOrBranch: 0.1.10
    rid: x"0B9D2011C51E750CC9639B3EA285EC6F92BF947B4445BDA54397A362627CEE2E"
    insecure: false
compile:
  rellVersion: 0.14.9

Next, run chr install.

Minimal implementation example

Here's a minimal implementation example in Rell:

main.rell

module;

import ai: lib.ai_inference;

operation submit_inference_request(id: text, prompt: text) {
    ai.submit_inference_request(id, prompt);
}

query fetch_inference_result(id: text): ai.inference_result? = ai.fetch_inference_result(id);

@extend(ai.on_inference_result)
function (id: text, result: ai.inference_result) {
    if (result.result != null) {
        log("Inference with id %s finished successfully.".format(id));
    } else {
        log("Inference with id %s failed: %s.".format(id, result.error));
    }
}

Deployment to testnet

Leasing a container

If you are unfamiliar with leasing a container, follow these steps.

Ensure you select the AI Inference extension when leasing the container. :::

Deployment

Follow the deployment steps.

You can find the BRID for the Testnet Directory Chain in the explorer.

The deployment section in your chromia.yml will look like this:

deployments:
testnet: # Deployment Target name
  brid: x"6F1B061C633A992BF195850BF5AA1B6F887AEE01BB3F51251C230930FB792A92" # Blockchain RID for Testnet Directory Chain
  url: https://node0.testnet.chromia.com:7740 # Target URL for one of the nodes in Testnet
  container: 4d7890243fe710...08c724700cbd385ecd17d6f # Replace with your container ID (Example: container: 15ddfcb25dcb43577ab311fe78aedab14fda25757c72a787420454728fb80304)
  chains:
    ai_inference_dapp: x"9716FBFF3...663FEC673710" # Replace with the actual BRID after the dapp gets deployed. You can find it in the terminal during deployment.

Simple test

In the examples provided, ai_inference_dapp and testnet refer to the deployment parameters.

To send a request, use:

chr tx -bc ai_inference_dapp -d testnet submit_inference_request 'a1' 'Ai inference started?'

To get a response, execute:

chr query -bc ai_inference_dapp -d testnet fetch_inference_result id=a1

Output:

[
  "error": null,
  "result": "Ai inference started?\n\nThe answer is yes.\n\nThe first step is to find the source of the inference.\n\n
]

Explore the example source code.

You can access the source code and additional information about the AI Inference extension in the official repository.