Somnia LLM Inference

A Somnia Agents base agent that runs a pinned LLM on a subcommittee of validators and returns the agreed answer to your contract.

Somnia LLM Inference is a base agent on Somnia Agents. A contract sends a prompt, a subcommittee of validators each runs the same pinned open-weight model with a fixed seed and zero temperature, and the agreed answer is returned to the contract's callback.

The full interface is in the LLM Inference reference.

How a request runs

Request. A contract sends a prompt to Somnia Agents with a deposit and a callback.
Elect. A subcommittee of validators from the Somnia Validator Network is chosen to run it.
Infer. Each validator runs the same model with the same seed at zero temperature.
Agree. Under majority consensus, byte-identical answers from the threshold of validators finalise the request.
Deliver. The answer goes to the contract's callback. Signed receipts of each validator's run are kept for audit, and unspent deposit is refunded.

Methods

Method	Returns
`inferString`	Single-turn text, optionally limited to a list of allowed values
`inferNumber`	An integer, clamped to a range you set
`inferChat`	A reply in a multi-turn conversation with system, user and assistant roles
`inferToolsChat`	A reply that can call MCP servers, with onchain functions returned as calldata

Each method can record chain-of-thought in the execution receipts. A request can accept only identical answers (majority consensus), or receive every validator's result and aggregate them onchain (threshold).

Example

moderation.ts

// From docs.somnia.network/agents/base-agents/llm-inference
const abi = [{
  type: 'function',
  name: 'inferString',
  inputs: [
    { name: 'prompt', type: 'string' },
    { name: 'system', type: 'string' },
    { name: 'chainOfThought', type: 'bool' },
    { name: 'allowedValues', type: 'string[]' }
  ],
  outputs: [{ name: 'response', type: 'string' }]
}];

// Content moderation example — constrain output to "safe" or "unsafe"
const calldata = encodeFunctionData({
  abi,
  functionName: 'inferString',
  args: [
    'Analyze the following text: "Check out this amazing new product!"',
    'You are a content moderation assistant.',
    false,            // chainOfThought
    ['safe', 'unsafe'] // allowedValues
  ]
});

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