The Architecture

The QudeAI Framework is designed as a modular, scalable, and high-performance system to facilitate the deployment, interaction, and management of AI agents.

1. Core Components

1.1 Backend API Layer

  • The backend serves as the primary interface for users to interact with agents.

  • Built with Node.js, it uses Express for routing and API endpoints.

  • Supports RESTful API interaction for agent queries, token management, and trading operations.

  • Integrates directly with Firebase for data persistence and Solana for blockchain-related operations.

Key Responsibilities:

  • Manage agent lifecycle (deployment, interaction, decommission).

  • Query and handle agent-specific data from blockchain and external APIs.

  • Enable seamless interaction through HTTP methods (GET, POST, etc.).

import express from 'express';
import { interactAgent } from './interactAgent';

const app = express();
app.use(express.json());

app.post('/api/agent/:agentName/interact', async (req, res) => {
  const { agentName } = req.params;
  const { message } = req.body;
  const response = await interactAgent(agentName, message);
  res.json({ response });
});

app.listen(3000, () => console.log('Server is running on port 3000'));

1.2 Blockchain Integration

  • Solana is used for high-speed, low-cost transactions.

  • The framework interacts with Solana via @solana/web3.js for:

    • Token creation and management.

    • Querying on-chain data like top holders, token supply, and transaction history.

  • Ensures transparency and immutability by storing critical agent and token data on the blockchain.

Key Features:

  • Supports querying real-time blockchain data via Bitquery APIs.

  • Efficient token management and trading operations on the Solana network.

import { Connection, clusterApiUrl } from '@solana/web3.js';

const connection = new Connection(clusterApiUrl('mainnet-beta'), 'confirmed');

async function getTokenBalance(mintAddress: string): Promise<void> {
  const balance = await connection.getTokenSupply(mintAddress);
  console.log(`Token Supply: ${balance.value.uiAmount}`);
}
getTokenBalance('6LKbpcg2fQ84Ay3kKXVyo3bHUGe3s36g9EVbKYSupump');

1.3 AI Engine

  • Powered by OpenAI APIs, the AI engine enables intelligent interactions and responses.

  • Each agent can be configured with specific behaviors and knowledge bases for tailored user experiences.

Key Features:

  • Flexible configuration of agent behavior.

  • Scalable AI query handling using OpenAI's GPT models.

  • Enables natural language processing (NLP) for advanced interaction.

import { Configuration, OpenAIApi } from 'openai';

const openai = new OpenAIApi(new Configuration({ apiKey: process.env.OPENAI_API_KEY }));

async function askAI(question: string): Promise<string> {
  const response = await openai.createCompletion({
    model: 'text-davinci-003',
    prompt: question,
    max_tokens: 200,
  });
  return response.data.choices[0].text.trim();
}

1.4 Firebase Integration

  • Acts as the centralized database for storing agent metadata, user interactions, and analytics.

  • Real-time data updates enable seamless coordination between agents and users.

  • Firebase handles authentication and agent ownership validation.

Key Responsibilities:

  • Store agent details (name, contract address, metadata).

  • Maintain logs of user interactions and performance metrics.

import { initializeApp } from 'firebase/app';
import { getDatabase, ref, set } from 'firebase/database';

const firebaseConfig = { apiKey: 'your_api_key', authDomain: 'your_project_id' };
const app = initializeApp(firebaseConfig);

async function storeAgentData(agentName: string, data: any): Promise<void> {
  const db = getDatabase(app);
  await set(ref(db, `agents/${agentName}`), data);
  console.log('Agent data stored successfully!');
}

2. Layers of Architecture

2.1 User Interaction Layer

  • Users can interact with agents through:

    • Command-line tools (npm run interactqude).

    • RESTful API endpoints (curl commands for GET/POST).

    • External web interfaces and third-party applications.

  • Provides an intuitive interface for both developers and end-users.

curl -X POST "https://api.qude.ai/api/agent/Aura/interact" \
-H "Content-Type: application/json" \
-d '{"message": "Hello, Aura!"}'

2.2 Middleware Layer

  • Orchestrates requests between the User Interaction Layer and Backend API.

  • Ensures secure communication via authentication mechanisms (API keys, tokens).

  • Validates and sanitizes inputs to prevent unauthorized access or misuse.

function validateRequest(req, res, next) {
  if (!req.headers['x-api-key']) {
    return res.status(401).json({ error: 'Unauthorized access' });
  }
  next();
}
app.use(validateRequest);

2.3 Backend Service Layer

  • The core of the framework handles:

    • API requests and responses.

    • Blockchain queries and Solana wallet interactions.

    • Communication with external APIs like OpenAI and Bitquery.

async function fetchTrendingTokens(): Promise<void> {
  const query = `
  query {
    Solana {
      DEXTradeByTokens(limit: { count: 5 }) {
        Trade {
          Currency { Name, MintAddress }
        }
      }
    }
  }`;
  const response = await fetch(process.env.BITQUERY_API_URL!, {
    method: 'POST',
    headers: { 'X-API-KEY': process.env.BITQUERY_API_KEY!, 'Content-Type': 'application/json' },
    body: JSON.stringify({ query }),
  });
  const data = await response.json();
  console.log(data);
}

2.4 Data Storage Layer

  • Firebase:

    • Stores metadata and interaction logs.

    • Provides secure, real-time data synchronization.

  • Solana Blockchain:

    • Immutable storage for on-chain data like token details and ownership.

3. Key Integrations

Technology
Purpose

OpenAI

AI-powered interactions for agent behavior.

Solana Blockchain

High-performance blockchain for token and transaction management.

Firebase

Cloud database for storing agent data and logs.

Bitquery APIs

Provides blockchain analytics and query capabilities.

Node.js

Backend framework for API and business logic.

TypeScript

Strongly typed language for improved development efficiency.

4. Scalability and Extensibility

  • Horizontal Scalability:

    • Deploy multiple agents or services independently.

    • Scale backend services and API handling as user demands grow.

  • Extensibility:

    • Easily integrate additional blockchain networks or AI engines.

    • Add new features via modular components and APIs.

5. Security

  • API authentication using environment variables and tokens.

  • Data integrity ensured via blockchain immutability.

  • Firebase provides secure and encrypted data storage.

6. Example Workflow

Agent Interaction Workflow:

  1. User Input:

    • A user sends a request via CLI or API, e.g., npm run interactqude Aura ask "Hello!".

  2. Middleware Validation:

    • Input is validated, and the appropriate API endpoint is triggered.

  3. AI Engine Processing:

    • The AI engine processes the request and generates a response.

  4. Blockchain Query (if needed):

    • Blockchain data (e.g., token holders, supply) is fetched using Bitquery APIs.

  5. Response:

    • The processed response is returned to the user via CLI or API.

7. Future Enhancements

  • Integration with additional blockchains for multi-chain support.

  • Advanced analytics dashboard for agent performance tracking.

  • Plugin-based architecture for third-party integrations.

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