Team 27 ArbitrumAgent: Empowering Decentralized Governance and Development with AI

Archive GovHack Brussels
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Title: ArbitrumAgent: Empowering Decentralized Governance and Development with AI

Track: AI, Gov, Tech

Group: 27

Challenges in the Current Grant Approval Process

Inconsistent Approvals: The unpredictable nature of grant approvals creates uncertainty and hampers community progress.

Resource Drain: Manual approval processes consume significant team resources and energy, leading to reduced productivity.

Missed Opportunities: The current system’s inefficiencies result in missed opportunities for valuable contributions to the ecosystem.

Loom Video: Empowering Decentralized Governance with AI in DAOs | Loom

Objective:
Develop an intelligent agent, ArbitrumAgent, that automates the approval of micro-grants, provides specialized AI-driven assistance within the Arbitrum ecosystem, and enhances developer support and community engagement.

Project Description:
ArbitrumAgent is designed to revolutionize the way the Arbitrum ecosystem operates by leveraging AI and automation. The project has three main components:

  1. Automated Approval of Micro-Grants:

    • Automate the approval of micro-grants for specific types of proposals defined by the DAO. This includes grants for organizing local developer events, contributing to GitHub repositories, writing articles or blogs, and other community-building activities.
    • Implement a smart contract that evaluates and approves these grants based on predefined criteria, ensuring transparency and efficiency.

  2. Custom Trained Arbitrum LLM:

    • Develop a custom-trained Large Language Model (LLM) specifically tailored to the Arbitrum ecosystem. This AI model will be fine-tuned using all available resources, including forums, websites, smart contracts, and other relevant data.
    • Phase 1: Fine-tune an existing LLM with current Arbitrum data.
    • Phase 2: Create a comprehensive dataset and train a custom LLM from scratch to better understand and respond to Arbitrum-specific queries.

  3. Query Handling and Developer Support:

    • Implement an LLM-based agent to handle queries related to the Arbitrum ecosystem, including smart contracts, project information, and troubleshooting.
    • This agent will act as a Stack Overflow-like support system for Arbitrum, providing accurate and context-specific answers to developers and users, thereby enhancing the overall developer experience.

Key Features:

  1. Automated Micro-Grant Approval:

    • Smart contract-based approval for micro-grants.
    • Criteria-based evaluation to ensure fairness and transparency.

  2. Arbitrum-Specific LLM:

    • AI model fine-tuned with Arbitrum ecosystem data.
    • Customized training for more accurate and relevant responses.

  3. Comprehensive Query Handling:

Technical Approach:

  • Smart Contracts: Develop smart contracts for automated micro-grant approvals using Solidity.
  • LLM Fine-Tuning: Use existing LLMs like GPT-4 and fine-tune them with Arbitrum-specific data.
  • Custom LLM Training: Create datasets and train a custom LLM using frameworks like Hugging Face Transformers and TensorFlow.
  • Query Handling System: Build an AI-driven query handling system using natural language processing (NLP) techniques.

Milestones:

  1. Milestone 1: Develop and deploy the smart contract for micro-grant approvals (Month 1-2)
  2. Milestone 2: Fine-tune an existing LLM with Arbitrum data (Month 3-4)
  3. Milestone 3: Develop the query handling system (Month 5-6)
  4. Milestone 4: Create datasets for custom LLM training (Month 7-8)
  5. Milestone 5: Train and deploy the custom LLM (Month 9-10)
  6. Milestone 6: Integrate all components and conduct testing (Month 11-12)

Funding Request:

  • Total: $80,000
    • Development: $20,000
    • AI Model Training: $30,000
    • Infrastructure: $20,000
    • Miscellaneous: $10,000

Impact:
ArbitrumAgent will streamline the micro-grant approval process, provide AI-driven support to developers, and enhance community engagement within the Arbitrum ecosystem. By automating routine tasks and offering specialized AI assistance, ArbitrumAgent will foster innovation and collaboration, driving the ecosystem forward.

Team Members:

  • Lead Developer and AI Specialist: Sagar
  • Technical Project Manager: Umesh.S
  • Social Marketing and AI Research: Ayush

Thank you for reading this proposal until the end, and please give us your honest and harshest feedback. We know we need it, and we truly welcome it! :innocent:

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