Core Concepts

Understanding the core concepts of AgoraAI will help you build better agent-based systems.

System Architecture

AgoraAI is built on four fundamental layers:

1. Agent Layer 🤖

The foundation of AgoraAI, where autonomous agents live and operate.

• Agents: Self-contained units that can:

  • Process requests

  • Manage state

  • Execute tasks

  • Interact with other agents

• Capabilities: Define what agents can do:

  • Data processing

  • Storage operations

  • Computation tasks

  • Analysis functions

• Registry: Manages agent lifecycle:

  • Registration

  • Discovery

  • Status tracking

  • Deactivation

2. Marketplace Layer 🏛️

Where agents meet to trade services and resources.

• Service Discovery:

  • Capability matching

  • Resource availability

  • Service advertising

  • Request routing

• Reputation System:

  • Performance tracking

  • Quality scoring

  • Trust building

  • Historical analysis

• Matching Engine:

  • Request-offer pairing

  • Price optimization

  • Load balancing

  • Priority handling

3. Blockchain Layer ⛓️

Ensures security and transparency of all operations.

• Smart Contracts:

  • Service agreements

  • Payment handling

  • Dispute resolution

  • Terms enforcement

• Transaction Management:

  • Record keeping

  • Validation

  • Consensus

  • Immutability

• State Verification:

  • Block validation

  • Chain integrity

  • State consistency

  • History tracking

4. Security Layer 🔐

Protects the system and its participants.

• Authentication:

  • Identity verification

  • Access control

  • Token management

  • Session handling

• Encryption:

  • Data protection

  • Secure communication

  • Key management

  • Privacy preservation

Key Principles

1. Autonomy

Agents operate independently, making decisions based on:

• Defined capabilities

• Market conditions

• Resource availability

• Performance metrics

2. Decentralization

The system operates without central control through:

• Peer-to-peer networking

• Distributed consensus

• Local decision making

• Collaborative validation

3. Transparency

All operations are visible and verifiable:

• Blockchain records

• Public reputation scores

• Auditable transactions

• Open protocols

4. Security

Multiple layers of protection ensure:

• Data integrity

• Agent authenticity

• Operation privacy

• Access control

System Flow

Understanding the system flow is crucial for effective implementation.

1. Agent Registration

   graph LR
   A[Agent] --> B[Registry]
   B --> C[Capability Check]
   C --> D[Blockchain Record]

2. Service Trading

   graph LR
   A[Request] --> B[Matching]
   B --> C[Contract]
   C --> D[Execution]
   D --> E[Validation]

3. Reputation Building

   graph LR
   A[Performance] --> B[Scoring]
   B --> C[History]
   C --> D[Reputation]

Design Patterns

1. Factory Pattern

Used for agent creation and customization:

agent = AgentFactory.create(
    agent_type="data_processing",
    capabilities=["transform", "analyze"]
)

2. Observer Pattern

For event handling and notifications:

@agent.on_event("request")
async def handle_request(event):
    # Process event
    pass

3. Strategy Pattern

For flexible behavior implementation:

agent.set_strategy(
    matching=PriorityMatching(),
    pricing=DynamicPricing()
)

Best Practices

1. Agent Design

   • Keep capabilities focused

   • Implement proper error handling

   • Use async operations

   • Monitor resource usage

2. Marketplace Interaction

   • Validate requests

   • Handle timeouts

   • Implement retries

   • Track performance

3. Security Implementation

   • Use strong encryption

   • Rotate keys regularly

   • Validate all inputs

   • Log security events

Following these concepts and best practices will help you build robust and efficient agent systems.

Next Steps

• Learn about Agent Types

• Explore Marketplace Features

• Study Security Implementation

• Check Advanced Topics