Hemera Doc
  • 👋Welcome
    • Introduction
    • Quick Start
    • Account Centric Indexing Protocol
      • What is Account-Centric Indexing?
      • Why "account-centric" indexing?
      • The advantages of Account-Centric Indexing
      • What's next for account-centric indexing?
      • Why create a new protocol here?
      • The Hemera Network
        • Network Roles
        • Indexers
        • Validators
        • Proprietary models & knowledge
        • Proprietary data and labels
        • Smart Contracts
        • Key roadmap items
        • Supported blockchains
      • Example Hemera use cases
        • SocialScan Explorers
        • Anti-sybil UML algorithm
        • Ethereum long term DA
        • EVM chain history preservation
        • Ecosystem AI Agents
        • User-defined AI Agents
  • 👩‍💻Developer Resources
    • Smart Contract Developers
    • EVM-compatible chains
      • Blockchain explorers
      • SocialScan explorer API doc
      • Ecosystem AI Agents
    • Dapp developers
    • User-defined Agent creators
    • AVS Operator
  • 🖥️Hemera Indexer
    • Introduction
    • Installation
      • Prerequisites
      • Install & Run
      • Export Result
    • Configurations
    • Benchmark
    • Data Class
      • Raw Data Tables
        • Blocks
        • Transactions
        • Logs
        • Traces
      • Generated Tables
        • Contract Internal Transactions
        • ERC20 Token Transfers
        • Tokens
        • ERC20 Token Holders
        • ERC721 Token Transfers
        • ERC721 Token Holders
        • ERC1155 Token Transfers
        • ERC1155 Token Holders
        • Address Coin Balances
        • Address Token Balances
        • Address Current Token Balances
        • Daily Wallet Address Stats
        • Contracts
      • Other Tables
        • Inscriptions
        • Bridges
          • L1 to L2 Transactions
          • L2 to L1 Transactions
          • Optimistic Rollup Data Availability Batches
          • Optimistic Rollup State Batches
    • Use Cases
      • UniSwap V3
        • Data Class
        • Trigger and Function
        • Run & Query
      • ENS
        • Data Class
        • Trigger and Function
        • Run & Query
      • OpenSea
        • Data Class
        • Trigger and Function
        • Run & Query
      • Deposit to L2
        • Data Class
        • Trigger and Function
        • Run & Query
      • User Profile
  • UDFs - User Defined Functions
    • Introduction
    • Components of UDFs
    • Building User Defined Functions(UDF)
    • Testing and Running UDF
    • Troubleshooting and Support
    • Supported UDFs
    • FAQs
  • 😄About us
    • The story behind building Hemera
    • Partners & Backers
    • Partnership inquiries
    • Hemera Powered Explorers
    • Active Developer Hackathons
    • Developer Contribution
  • Documentation feedback
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  1. Developer Resources

User-defined Agent creators

PreviousDapp developersNextAVS Operator

This application is under active development. We expect to have our early access testnet launch in Q3, 2024. In the meantime, you can read about the application design below.

To stay updated for early access, please follow our official twitter account for the latest announcements:

Hemera Protocol:

  1. Creating an AI Agent

To create a user-defined AI agent on Hemera, creators can follow these steps:

  • Accessing the Platform: Creators can sign up for an account on Hemera and log in to access the platform.

  • Setting up a New AI Agent Project: Upon logging in, creators can initiate a new AI agent project and define its objectives, parameters, and customization options.

  • Defining Objectives and Parameters: Creators specify the tasks and functions their AI agent will perform, along with any configurable parameters and settings.

  1. Customization Interface

Hemera provides an intuitive customization interface for creators to tailor their AI agents:

  • Drag-and-Drop Interface: Creators can use a user-friendly drag-and-drop interface to configure the behavior and logic of their AI agents.

  • Configuration Wizards:

  1. Data Indexing

Creators can seamlessly integrate data sources into their AI agents on Hemera:

  • Connecting to Hemera Indexing Network: Hemera supports agent integration with our open indexing protocol, allowing creators to access blockchain data directly within their AI agents.

  • Importing External Data? Creators can import data from external sources, such as APIs, databases, or Web3 data feeds, to enrich the capabilities of their AI agents.

  1. Algorithm Selection

Hemera offers a range of options for selecting and implementing algorithms within AI agents:

  • Pre-built Algorithm Libraries: Creators can choose from a library of pre-built algorithms optimized for common tasks and use cases.

  • Custom Algorithm Development: For advanced users, Hemera provides tools for developing custom algorithms tailored to specific requirements and objectives.

  1. Testing and Validation

Creators can test and validate their AI agents on Hemera to ensure optimal performance:

  • Simulation and Evaluation: Creators can simulate different scenarios and evaluate the performance of their AI agents using predefined metrics and benchmarks.

  • Iterative Improvement? Hemera supports an iterative development process, allowing creators to iterate on their designs based on testing and validation results.

👩‍💻
https://x.com/HemeraProtocol