⚙️Technical Architecture

AgentsLab is built on a modern Web3 technology stack that seamlessly integrates frontend interaction, on-chain smart contracts, data indexing, and decentralized storage. The result is a scalable, modular, and autonomous AI platform.

3.1 Frontend Interface

• Framework: Built with Next.js for hybrid static and server-side rendering, ensuring fast performance and SEO optimization.

• Styling: Uses TailwindCSS for atomic, utility-first styling and responsive design.

• Wallet Integration: Powered by Wagmi + RainbowKit, supporting major wallets like MetaMask and WalletConnect for seamless Web3 connectivity.

• Agent Builder UI: Offers a no-code, visual interface for configuring personality training, behavior logic, model selection, and event triggers.

3.2 Smart Contracts

• Languages: Core contracts are written in Solidity, with some security-critical logic implemented in Vyper.

• Deployment Networks: Initially deployed on Ethereum, with multichain compatibility for networks like Arbitrum, Base, and Polygon.

• Contract Modules include:

  • AgentFactory.sol: Handles creation and registration of agents with unique AgentIDs.

  • TokenLauncher.sol: Enables one-click meme-style token deployment.

  • Governance.sol: Implements proposal voting and feature access via $AL token.

  • Marketplace.sol: Supports agent listing, invocation, and trading.

  • Permission.sol: Manages access control and execution permissions for agents.

3.3 Data Layer

• Indexing: Utilizes The Graph to build subgraphs that index:

  • Agent creation and invocation history

  • Token issuance records

  • Plugin usage logs

  • User-agent interaction events

• Query Layer: Exposes a GraphQL API for frontend and third-party developers, with support for filtering, pagination, and real-time subscriptions.

3.4 Storage Layer

• Agent Logic & Memory: Long-term agent data, including behavior logic, training snapshots, and memory states, is stored via:

  • IPFS: For storing logic files, metadata, and plugin manifests.

  • Arweave: For immutable and auditable records of agent creation and update history.

• Model Snapshots: Agent model presets (e.g., initial prompts, personalities) are stored off-chain, cryptographically linked to AgentIDs.

3.5 Agent Runtime Layer (Upcoming)

• Agent Execution VM: Future integration of lightweight sandboxes for hybrid on/off-chain reasoning and execution.

• A2A Protocol (Agent-to-Agent): Enables agents to invoke and collaborate with each other, supporting multi-agent intelligent workflows.