# Example

## Example: Commit-Reveal Scoring (Inference Subnet)

The **inference-subnet** built on the Hypertensor template demonstrates a powerful example of decentralized coordination using a **commit-reveal** model. This model ensures fairness, verifiability, and resistance to manipulation during scoring phases for both **hosters** and **validators**.

### Commit-Reveal Workflow Example

This subnet divides each epoch into **phases**, where nodes submit **commits** (cryptographic hashes of data) followed by **reveals** (the actual data), enabling transparent scoring without early data leaks.

### **Step-by-Step Process:**

1. **Validator Prompt Commit (0-15%)**
   * At the start of the epoch, the **elected validator** publishes a **randomized prompt tensor** to the DHT.
   * This prompt is validated using a **Pydantic schema** to ensure proper format and tensor structure.
   * If the validator doesn't submit one by the 10% mark of the epoch, anyone can take over this task.
2. **Randomized Seed  (0-15%)** ⸺ Score multiplier
   * At the start of the epoch, the **elected validator** publishes a **randomized float** to the DHT.
   * This prompt is validated using a **Pydantic schema** to ensure it's a float and is verified to be between the minimum and maximum values.
   * If the validator doesn't submit one by the 10% mark of the epoch, anyone can take over this task.
3. **Hoster Inference & Commit Phase (15-50%)**
   * Each **hoster** runs inference on the validator’s prompt.
   * Instead of revealing the output immediately, each hoster commits a **hash** of the result (e.g., `SHA256(salt + tensor)`).
   * This hash is stored in the DHT to prevent tampering or early reveals.
4. **Reveal Phase (50-60%)**
   * After the commit phase ends (based on epoch progress), each **hoster reveals** their output and salt.
   * The **validator** also reveals its own **score commit** from the previous epoch (i.e., the scores it assigned to each hoster).
   * These reveals are matched against the original commits to verify integrity later when scored.
5. **Scoring (60-100%)**
   * **Hosters** are scored based on the **distance of their output** from the **mean tensor** across all valid hoster reveals.
   * **Validators** are scored based on:
     * The **accuracy** of their revealed scores
     * How closely their scores align with the previous validator's on-chain scores in relation to the attestation ratio.
6. **Validator Commit Scores (60-100%)**
   * Validators commit a hash of their scores to the DHT that is revealed on the following epoch.

***

#### [Predicate Validator](/subnet-template/dht-records/record-validator/predicate-validator.md) Integration

All commit and reveal actions are **validated by a `PredicateValidator`**, which:

* Enforces **phase correctness** (e.g., commits and reveals in specific periods of an epoch)
* Ensures each record (commit or reveal) is **schema-compliant** and **authenticated**
* Prevents out-of-order or invalid submissions

***

#### Authentication Requirement

Every reveal must be cryptographically linked to its original commit using the same keypair. This ensures:

* No node can **forge or steal** another node’s output
* Scores are only assigned to **authenticated participants**

***

#### Why This Matters

This design enables decentralized, trustless coordination and evaluation of AI work — all without central servers or privileged roles.

> 🔐 The commit-reveal model ensures fairness, resists manipulation, and enables transparent peer scoring at scale.

## Overview

<figure><img src="/files/hQ9ONKIor1nJ4036xwvR" alt=""><figcaption></figcaption></figure>


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