📖Agent Development Framework

DeepAI Agent building framework is divided into three levels: Agent World, Agent OS and Agent Protocol. This layered architecture ensures seamless connection from user interaction to underlying network.

Technology Stack Architecture

• Service Module
• Kernel system: provides basic computing capability and resource scheduling
• Data center: supports efficient data processing and storage
• Multi-agent collaboration: enables distributed processing of complex tasks
• External interface: connects with external systems

• Agent Module
• Inference engine: supports intelligent decision-making and logical analysis
• Learning system: provides continuous evolution capability
• Inference computation: executes real-time model inference
• Oracle: obtains trusted external data
• Identity management: ensures secure and controllable interaction

• Model Repository: Integrates mainstream AI models, providing rich capability support for agents.

• Consensus Mechanism: Ensures network consistency and reliability

• Token Incentives: Drives healthy ecosystem development

• Behavior Recording: Guarantees system transparency

• DAO Governance: Achieves decentralized democratic decision-making

• Secure Computing: Protects data and computation process

• Decentralization: Build distributed autonomous network

• Agent-Driven: Agent as core operational unit

• Modular Design: Ensure system extensibility

• AI Empowerment: Deep integration of artificial intelligence capabilities

• Security and Trust: Build zero-trust security system

• Value-Driven: Drive innovation through token economics

Infrastructure Core

1. Model Integration DeepAI platform supports integration of diverse AI models, covering influential large commercial models in industry, such as natural language processing and image recognition systems, while also including models driven by open source community. This design not only meets broad industry needs but can also be fine-tuned for specific market segments to meet unique requirements of different industries, thus providing more precise services.

2. Plugin Architecture The platform adopts innovative plugin architecture, allowing third-party developers to add customized functions to agents in modular way. This flexible design enables developers to quickly integrate new AI services without modifying core code, promoting diversity and prosperity of technical ecosystem, encouraging more developers to participate in ecosystem building.

3. Knowledge Base DeepAI’s knowledge base aims to provide users with centralized data storage and retrieval solutions. By utilizing this knowledge base, agents can improve response quality in generative way, more accurately meeting user needs. The knowledge base is not just information repository but helps models better understand and adapt to user behavior through continuous learning and analysis of specific use cases.

4. Optimization Engine Personality-based optimization engine is core component of this infrastructure. The engine uses advanced algorithms to analyze user interaction patterns, automatically adjusting agent response methods to better simulate real human emotions and personalities. This deep personalization experience not only enhances user immersion but also strengthens interaction effect between users and agents.

5. Community Integration Community integration module gives agents powerful cross-platform capabilities, seamlessly integrating them into mainstream social channels like Telegram, Discord. This design allows agents to provide services directly in environments familiar to users, without requiring users to adapt to new usage scenarios, thus improving user convenience and satisfaction.

6. Smart Contract Interface The infrastructure’s smart contract interface allows interaction with blockchain smart contracts, achieving efficient collaboration between AI infrastructure and public chains. This design ensures seamless connection between on-chain and off-chain services, promoting decentralized development of entire ecosystem.