LP-106: LLM Gateway Integration with Hanzo AI

Abstract

This proposal establishes integration standards between Lux Network and Hanzo's LLM Gateway (HIP-4), enabling Lux validators and applications to access 100+ LLM providers through a unified interface. This integration provides AI capabilities to smart contracts, enables on-chain inference verification, and supports AI-powered blockchain analytics.

Motivation

Lux Network requires AI capabilities for:

1. Smart Contract Intelligence: AI-powered contract analysis and optimization
2. Validator Assistance: Automated threat detection and network optimization
3. Cross-Chain Analytics: AI-driven insights across Lux's multi-chain architecture
4. Developer Tools: AI code generation and auditing for Lux dApps
5. User Experience: Natural language interfaces for blockchain interactions

Hanzo's LLM Gateway provides these capabilities through a battle-tested, provider-agnostic interface.

Specification

Integration Architecture

Lux Network Layer
├── Smart Contracts
│   └── AI Oracle Contracts → Hanzo LLM Gateway
├── Validator Nodes
│   └── AI Monitoring Module → Hanzo LLM Gateway
├── Developer Tools
│   └── AI Assistant SDK → Hanzo LLM Gateway
└── Applications
    └── AI Service Layer → Hanzo LLM Gateway

Hanzo LLM Gateway (HIP-4)
├── Provider Router (100+ providers)
├── Model Selection Engine
├── Caching Layer
└── Cost Optimization

Smart Contract AI Oracle

interface ILuxAIOracle {
    struct AIRequest {
        string prompt;
        string model;
        uint256 maxTokens;
        uint256 temperature;
        address callback;
        bytes32 requestId;
    }
    
    struct AIResponse {
        bytes32 requestId;
        string response;
        uint256 tokensUsed;
        uint256 cost;
        bytes signature;  // Proof of inference
    }
    
    // Request AI inference
    function requestInference(
        AIRequest calldata request
    ) external payable returns (bytes32 requestId);
    
    // Callback for AI response
    function fulfillInference(
        AIResponse calldata response
    ) external;
    
    // Verify inference proof
    function verifyInference(
        bytes32 requestId,
        bytes calldata proof
    ) external view returns (bool);
}

Validator AI Integration

package validator

import (
    "github.com/luxfi/lux-node/snow/engine"
    "github.com/hanzoai/llm-gateway/client"
)

type AIValidator struct {
    engine    engine.Engine
    llmClient *client.LLMGateway
}

// Analyze transaction patterns
func (v *AIValidator) AnalyzeTransaction(tx *Tx) (*AIAnalysis, error) {
    prompt := fmt.Sprintf(`
        Analyze this transaction for anomalies:
        From: %s
        To: %s
        Value: %s
        Data: %s
        
        Check for:
        1. Known attack patterns
        2. Unusual gas usage
        3. Suspicious contract calls
        4. Money laundering indicators
    `, tx.From, tx.To, tx.Value, tx.Data)
    
    response, err := v.llmClient.Complete(&CompletionRequest{
        Model:  "claude-3-opus",
        Prompt: prompt,
        MaxTokens: 500,
    })
    
    return parseAIAnalysis(response), err
}

// Optimize validator performance
func (v *AIValidator) OptimizePerformance() error {
    metrics := v.engine.GetMetrics()
    
    prompt := fmt.Sprintf(`
        Analyze validator metrics and suggest optimizations:
        - Block production rate: %f
        - Network latency: %dms
        - Memory usage: %dMB
        - Peer count: %d
    `, metrics.BlockRate, metrics.Latency, metrics.Memory, metrics.Peers)
    
    response, err := v.llmClient.Complete(&CompletionRequest{
        Model:  "gpt-4-turbo",
        Prompt: prompt,
    })
    
    return v.applyOptimizations(response)
}

Developer SDK Integration

import { LuxSDK } from '@luxfi/sdk';
import { HanzoLLMGateway } from '@hanzoai/llm-gateway';

class LuxAISDK extends LuxSDK {
  private llm: HanzoLLMGateway;
  
  constructor(config: LuxConfig) {
    super(config);
    this.llm = new HanzoLLMGateway({
      apiKey: config.hanzoApiKey,
      endpoint: config.llmGatewayUrl || 'https://api.hanzo.ai/v1'
    });
  }
  
  // Generate smart contract code
  async generateContract(spec: ContractSpec): Promise<string> {
    const response = await this.llm.complete({
      model: 'claude-3-opus',
      messages: [{
        role: 'system',
        content: 'You are a Solidity expert. Generate secure, gas-optimized contracts.'
      }, {
        role: 'user',
        content: `Generate a smart contract with:
          Name: ${spec.name}
          Type: ${spec.type}
          Features: ${spec.features.join(', ')}
          Security: ${spec.securityLevel}
        `
      }],
      maxTokens: 2000
    });
    
    // Validate generated code
    await this.auditContract(response.content);
    
    return response.content;
  }
  
  // AI-powered contract audit
  async auditContract(code: string): Promise<AuditReport> {
    const response = await this.llm.complete({
      model: 'gpt-4-turbo',
      messages: [{
        role: 'system',
        content: 'You are a smart contract security auditor.'
      }, {
        role: 'user',
        content: `Audit this contract for vulnerabilities:\n\n${code}`
      }],
      maxTokens: 1500
    });
    
    return parseAuditReport(response.content);
  }
  
  // Natural language to transaction
  async nlToTransaction(request: string): Promise<Transaction> {
    const response = await this.llm.complete({
      model: 'claude-3-haiku',
      messages: [{
        role: 'user',
        content: `Convert to transaction: "${request}"`
      }],
      responseFormat: {
        type: 'json_object',
        schema: TransactionSchema
      }
    });
    
    return JSON.parse(response.content);
  }
}

Cross-Chain AI Analytics

interface CrossChainAnalytics {
  // Analyze bridge transactions
  analyzeBridgeFlow(params: {
    sourceChain: string;
    targetChain: string;
    timeRange: TimeRange;
  }): Promise<BridgeAnalysis>;
  
  // Detect cross-chain arbitrage
  detectArbitrage(params: {
    tokens: string[];
    chains: string[];
    minProfit: BigNumber;
  }): Promise<ArbitrageOpportunity[]>;
  
  // Risk assessment for cross-chain operations
  assessCrossChainRisk(params: {
    operation: CrossChainOp;
    value: BigNumber;
  }): Promise<RiskScore>;
}

class LuxCrossChainAI implements CrossChainAnalytics {
  async analyzeBridgeFlow(params): Promise<BridgeAnalysis> {
    const data = await this.collectBridgeData(params);
    
    const analysis = await this.llm.complete({
      model: 'claude-3-opus',
      messages: [{
        role: 'system',
        content: 'Analyze cross-chain bridge patterns for insights.'
      }, {
        role: 'user',
        content: `Analyze bridge flow:\n${JSON.stringify(data, null, 2)}`
      }]
    });
    
    return {
      volume: analysis.volume,
      trends: analysis.trends,
      anomalies: analysis.anomalies,
      recommendations: analysis.recommendations
    };
  }
}

Configuration Management

# lux-node-config.yaml
ai:
  enabled: true
  provider: hanzo
  gateway:
    url: https://api.hanzo.ai/v1
    api_key: ${HANZO_API_KEY}
    timeout: 30s
    retry_attempts: 3
  
  models:
    default: claude-3-haiku
    analysis: claude-3-opus
    code_generation: gpt-4-turbo
    audit: claude-3-opus
  
  features:
    transaction_analysis: true
    performance_optimization: true
    contract_generation: true
    natural_language: true
    cross_chain_analytics: true
  
  limits:
    max_requests_per_minute: 100
    max_tokens_per_request: 4000
    monthly_budget: 1000  # USD

Performance Optimization

// Caching layer for AI responses
type AICache struct {
    redis *redis.Client
    ttl   time.Duration
}

func (c *AICache) Get(prompt string) (*AIResponse, bool) {
    key := hashPrompt(prompt)
    data, err := c.redis.Get(context.Background(), key).Bytes()
    if err != nil {
        return nil, false
    }
    
    var response AIResponse
    json.Unmarshal(data, &response)
    return &response, true
}

func (c *AICache) Set(prompt string, response *AIResponse) {
    key := hashPrompt(prompt)
    data, _ := json.Marshal(response)
    c.redis.Set(context.Background(), key, data, c.ttl)
}

// Batch processing for efficiency
type AIBatcher struct {
    gateway  *LLMGateway
    requests chan *AIRequest
    batch    []*AIRequest
    ticker   *time.Ticker
}

func (b *AIBatcher) ProcessBatch() {
    responses, err := b.gateway.CompleteBatch(b.batch)
    if err == nil {
        for i, resp := range responses {
            b.batch[i].callback(resp)
        }
    }
    b.batch = nil
}

Security Considerations

contract SecureAIOracle {
    // Proof of inference verification
    mapping(bytes32 => InferenceProof) public proofs;
    
    struct InferenceProof {
        bytes32 modelHash;
        bytes32 inputHash;
        bytes32 outputHash;
        uint256 timestamp;
        bytes signature;
    }
    
    function verifyInferenceProof(
        bytes32 requestId,
        bytes calldata proof
    ) public view returns (bool) {
        InferenceProof memory p = proofs[requestId];
        
        // Verify signature from trusted AI provider
        address signer = recoverSigner(p, proof);
        require(trustedProviders[signer], "Untrusted provider");
        
        // Verify proof freshness
        require(block.timestamp - p.timestamp < 3600, "Stale proof");
        
        // Verify proof integrity
        bytes32 proofHash = keccak256(abi.encode(
            p.modelHash,
            p.inputHash,
            p.outputHash,
            p.timestamp
        ));
        
        return verifySignature(proofHash, proof);
    }
}

Rationale

Why Hanzo LLM Gateway?

• Provider Agnostic: Access to 100+ LLM providers
• Cost Optimization: Automatic routing to cheapest provider
• High Availability: Fallback across multiple providers
• Unified Interface: Single API for all models
• Battle Tested: Already serving millions of requests

Why On-Chain AI Integration?

• Smart Contract Intelligence: Enable AI-powered DeFi strategies
• Automated Security: Real-time threat detection
• User Accessibility: Natural language blockchain interaction
• Developer Productivity: AI-assisted development

Implementation Timeline

Phase 1: Core Integration (Q1 2025)

• Basic LLM Gateway connection
• Simple AI oracle contract
• Developer SDK integration

Phase 2: Validator AI (Q2 2025)

• Transaction analysis
• Performance optimization
• Network monitoring

Phase 3: Advanced Features (Q3 2025)

• Cross-chain analytics
• Contract generation
• Natural language interfaces

Phase 4: Full Production (Q4 2025)

• Mainnet deployment
• Performance optimization
• Enterprise features

Backwards Compatibility

This LP is additive and opt‑in. Nodes, contracts, and apps continue to function without the AI components enabled. Configuration gates all new behavior (ai.enabled); APIs are introduced alongside existing ones, avoiding breaking changes.

Testing

Integration Tests

# Test Hanzo gateway connection
go test ./ai/gateway -v

# Test AI oracle contract
forge test --match-contract AIOracle

# Test SDK integration
npm run test:ai-sdk

Performance Benchmarks

• Latency: < 500ms for simple queries
• Throughput: > 1000 requests/minute
• Cache hit rate: > 80%
• Cost optimization: 30% savings vs direct provider

Security Audit

• AI response verification mechanisms
• Rate limiting and DDoS protection
• API key management
• Proof of inference validation

Security Considerations

• Verify provenance: accept responses only from trusted providers with signed proofs; enforce freshness windows.
• Rate limit and cache to mitigate abuse; isolate AI subsystems from consensus‑critical paths.
• Treat AI output as untrusted input; validate before on‑chain effects.
• Secure API keys and transport (TLS); rotate keys and monitor usage.

References

1. HIP-4: LLM Gateway Standard
2. LP-10: P-Chain Platform Chain Specification
3. LP-103: MPC-LSS Multi-Party Computation
4. Hanzo LLM Gateway Docs

Test Cases

Unit Tests

1. Attestation Validation

   • Test attestation format
   • Verify signature chains
   • Test timestamp validation

2. AI Model Integration

   • Test model loading
   • Verify inference accuracy
   • Test resource limits

3. Privacy Preservation

   • Test data isolation
   • Verify access controls
   • Test audit logging

Integration Tests

1. Attestation Flow

   • Test end-to-end attestation
   • Verify chain of custody
   • Test revocation handling

2. Compute Verification

   • Test proof generation
   • Verify computation integrity
   • Test dispute resolution

Copyright

Copyright and related rights waived via CC0.