SCORIA AI - Decentralized AI Agent Framework on Solana

Enterprise-grade decentralized AI infrastructure enabling privacy-preserving model execution with blockchain-verified integrity.

🚀 Core Features

AI/ML Infrastructure

• Local Model Serving: ONNX/TensorRT runtime with GPU acceleration
• Federated Learning: Secure model aggregation (Paillier HE + ZKP)
• Model Marketplace: NFT-based model distribution
• Privacy Swaps: P2P data exchange with zk-SNARKs

Blockchain Integration

• Solana Program: On-chain model registry & inference verification
• Chainlink Adapter: Trustless oracle for real-world data
• DAO Governance: Reputation-weighted voting system
• Proof of Compute: GPU-based consensus mechanism

Enterprise Security

• Confidential Execution: SGX/TEE support
• Compliance Ready: GDPR/SOC2 audit trails
• Zero-Knowledge ML: zkCNN/zkRNN proof systems
• Runtime Integrity: BLAKE3 + Ed25519 signatures

🌐 Architecture

graph TD
    %% User Layer
    A[User Client] -->|Submit Task| B{SCORIA Program}
    A -->|Query Models| D[[Model Registry]]
    A -->|Verify Proofs| J[Proof Explorer]
    
    %% Blockchain Layer
    subgraph Solana MainNet
        B -->|Record State| C[(State Accounts)]
        C -->|Model Metadata| D
        B -->|Verify Proof| E[ZK Verifier]
        E --> F[Proof Ledger]
    end
    
    %% AI Execution Layer
    subgraph Local Engine
        D --> G[Model Loader]
        G --> H[Secure Enclave]
        H -->|GPU Acceleration| I[TensorRT/ONNX Runtime]
        I -->|Generate Proofs| E
    end
    
    %% Privacy Layer
    subgraph Privacy Network
        K[Federated Nodes] -->|Secure Aggregation| L[[Global Model]]
        L -->|Encrypted Updates| M[HE Vault]
        M -->|Threshold Decrypt| G
    end
    
    %% Infrastructure Layer
    subgraph Backend Services
        N[(PostgreSQL)] --> O[Analytics API]
        P[(Redis Cache)] --> Q[Session Manager]
        R[Kafka Streams] --> S[Event Processor]
    end
    
    %% Monitoring
    subgraph Observability
        T[Prometheus] --> U[Grafana Dashboard]
        V[ELK Stack] --> W[Audit Trail]
        X[Health Check] --> Y[Auto-Scaling]
    end
    
    %% Tooling
    subgraph Dev Tools
        Z[Anchor CLI] --> B
        AA[ONNX Toolkit] --> G
        AB[Circuit Compiler] --> E
    end
    
    %% External Adapters
    CC[[Chainlink Oracle]] --> B
    DD[[IPFS Storage]] --> D
    EE[[Wormhole Bridge]] --> K
    
    style A fill:#4b9be1,color:white
    style B fill:#666699,color:white
    style D fill:#ff9966
    style E fill:#99cc00
    style H fill:#c71585
    style L fill:#20b2aa
    style CC fill:#375bd2
    style EE fill:#8a2be2
          

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🧩 Tech Stack

Layer	Components
Blockchain	Solana CLI 1.14, Anchor Framework, Wormhole Bridge
AI Runtime	ONNX Runtime 1.15, TensorRT 8.6, CUDA 12.2
Privacy	Circom 2.1.5, Halo2, SEAL (Microsoft HE)
Infrastructure	Redis 7.0, PostgreSQL 15, Kafka 3.4
Monitoring	Prometheus 2.45, Grafana 10.1, ELK Stack 8.9

🛠️ Installation

Prerequisites

• Rust 1.72+ (nightly)
• Solana CLI 1.14.7
• Node.js 18.16+
• CUDA Toolkit 12.2
• PostgreSQL 15

# 1. Clone repository
git clone --recurse-submodules https://github.com/yourorg/scoria-ai.git

# 2. Install core dependencies
./scripts/install_deps.sh --with-gpu --with-chainlink

# 3. Configure environment
cp .env.example .env
# Edit .env with your Solana RPC endpoints and DB credentials

# 4. Build all components
make all

# 5. Run verification tests
make test-e2e

🧠 Usage Examples

Start Local Inference Node

# With GPU acceleration
scoria-node start \
  --model-repo ./models \
  --gpu 0 \
  --privacy-level enterprise

Submit Inference Task

import { ScoriaClient } from '@scoria/client';

const client = new ScoriaClient({
  cluster: 'mainnet-beta',
  wallet: new AnchorWallet(signer)
});

const result = await client.submitInferenceTask({
  model: 'resnet50-v2.1',
  inputs: tensorData,
  zkParams: {
    proofSystem: 'halo2',
    visibility: 'private'
  }
});

Participate in Federated Learning

// Submit local model update
let update = ModelUpdate::new(
    local_model,
    ZkProof::generate(
        training_data_stats,
        ComplianceProof::gdpr_compliant()
    )
);

let tx = client.build_fl_update_transaction(update);
tx.sign(&wallet).await?;

🔒 Security & Compliance

Audited Components

• Cryptography: FIPS 140-3 Level 2 certified modules
• Smart Contracts: Certora formal verification
• Data Pipeline: GDPR Article 32 encryption

Compliance Standards

• SOC2 Type II (AI Inference Pipeline)
• ISO 27001 (Model Serving Infrastructure)
• HIPAA (Medical Use Cases)

📈 Performance

Metric	Value (A100 80GB)
Inference Throughput	12,500 TPS
Proof Generation Time	850 ms
Model Load Latency	120 ms
Privacy Swap Bandwidth	9.2 Gbps

🤝 Contributing

• Fork the repository
• Create feature branch (git checkout -b feature/amazing)
• Commit changes (git commit -m 'Add amazing feature')
• Push to branch (git push origin feature/amazing)
• Open Pull Request

Development Guidelines:

• 100% test coverage for core components
• Zero unsafe code outside crypto modules
• Strict Clippy linter rules

📜 License

AGPL-3.0 License - See LICENSE for details.