⏳
DIN: AI Agent Blockchain
English
English
  • ABOUT DIN
    • ⏳ Overview
    • 🛣️ Our Journey
  • The Concept
    • 💡 Market and Trend Analysis
      • Overview of the current data trend and market
      • Overview of the current AI trend and market
      • Existing gaps and opportunities in the market
    • 🏠 DIN Architecture
      • 🟡Data Layer: All for the Data
        • Data Flow of AI
        • Data Collection
        • Data Validation
        • Data Vectorization
        • The Reward Mechnism
      • 🟩Service Layer: Toolkit for AI-Agent
        • LLMOps
        • RAG (Retrieval Augmented Generation)
          • Hybrid Search
          • Rerank
          • Retrieval
        • Annotation Reply
      • 💙Application Layer: The Ecosystem and Product
        • Analytix
        • xData
        • Reiki
  • How DIN works
    • ⛓️DIN Blockchain
      • 🌏Mainnet
      • 🧪Testnet
    • 🏤DIN Foundation
      • Team&Advisor wallet
      • MM & Liquidity wallet
      • Community wallet
      • Investors wallet
      • Ecosystem wallet
    • 💰 Tokenomics and Utilities
      • Token Allocations
      • Airdrop
      • Contract Details
      • Use cases for the token within the ecosystem
  • HOW TO JOIN
    • 🧲xData Explained
    • ⚙️Chipper Node Explained
      • How to run Chipper Node
      • Farm xDIN
      • Delegation
        • Revoke delegation
        • As an Operator
      • Node Stats
      • Smart Contract Addresses
    • 🤑Earn $DIN
    • 💹Staking
    • 🌉Buy $DIN
  • ROADMAP
    • 🎆 2025 Forward
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  1. The Concept
  2. 🏠 DIN Architecture

Service Layer: Toolkit for AI-Agent

In the service layer, a development platform is provided, which combines the concepts of Backend-as-a-Service and LLMOps to enable dAI-Apps developers to build production-grade generative applications quickly. Even non-technical personnel can participate in AI application definition and data operations.

By integrating the critical technology stacks required for building LLM applications, including support for hundreds of models, an intuitive Prompt orchestration interface, high-quality RAG engines, and a flexible Agent framework, while providing a set of easy-to-use interfaces and APIs, the platform saves developers a lot of time reinventing the wheel, allowing them to focus on innovation and business needs.

This layer focuses on defining and continuously improving the dAI-Apps applications development, the advantages are:

  • Integrate LLMs into existing businesses—Enhance the capabilities of current apps by introducing LLMs. Access the ready-to-use RESTful APIs to decouple Prompts from business logic. The management interface tracks data, costs, and usage while continuously improving performance.

  • LLM infrastructure - As an internal LLM gateway, accelerating the adoption of GenAI technologies.

  • Explore LLM capabilities - easily practice Prompt engineering and Agent technologies through different LLMs and integrate them with other real-time external knowledge.

Tips: Currently, most services in the service layer are invited-only. The public testing will be opened once the mainnet goes live.

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