This project is an application designed to supports the development of NEAR BOS components, enhanced by AI-generated code suggestions. It features a canvas-based UI that allows users to visualize component relationships
demo.mp4
Launch Demo🌈: nearstack.weminal
- Planned Code Deliverables during the Hackathon
- Project Background
- Problems Nearstack Aims to Solve
- Overview
- Features
- Technical Architecture
- Project Structure
- How does Nearstack work
- Team Information
- License
- Chat Windows.
- Editor Window.
- Reactflow UI
- Code Snippet Generation
Nearstack was created to address the challenges of frontend development in Web3, specifically for the NEAR ecosystem. Traditional tools often fall short in handling blockchain interactions and visualizing complex component relationships. By integrating NEAR BOS components and offering AI-driven code suggestions, Nearstack streamlines dApp development, enhancing productivity and accessibility. Its React flow interface helps developers understand and optimize component interactions.
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Complexity of Web3 Frontend Development
- Traditional frontend tools aren't optimized for blockchain interactions, making Web3 development more challenging and time-consuming.
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Lack of Visual Component Mapping
- Developers struggle to understand how components interact in decentralized applications, leading to inefficient workflows and increased errors.
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Limited AI Assistance in Web3 Coding
- Existing tools lack intelligent code suggestions tailored for Web3, leaving developers without optimized support for blockchain-specific tasks.
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Difficulty in Integrating NEAR Components
- Using NEAR BOS components in frontend development can be complex, slowing down the development process.
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Need for Enhanced Developer Efficiency
- Web3 projects require efficient workflows; Nearstack helps developers work faster and more effectively by simplifying component relationships and code management.
This repository contains nearstack source code, include: frontend, backend, AI and landing page. Nearstack is an innovative platform designed to streamline Web3 frontend development, specifically for applications built on the NEAR Protocol. Leveraging AI-generated code suggestions, Nearstack simplifies the development process and boosts productivity. The platform includes a React flow interface, allowing developers to visualize and understand the relationships between components, making it easier to manage complex frontend architectures.
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AI-Powered Code Suggestions
Provides intelligent code suggestions to speed up development and reduce errors. Tailored AI recommendations based on NEAR and Web3 development patterns.
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NEAR BOS Component Integration
Allows seamless integration and management of NEAR BOS components within frontend projects. Simplifies access to blockchain components, enhancing the Web3 development experience.
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React Flow Visualization
Features a React flow interface to map out component relationships visually. Makes it easy to understand how components connect, interact, and influence one another.
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Intuitive Component Interaction Mapping
Easily links components (e.g., Component A to Component B) for a clear, organized development workflow. Improves code maintainability and clarity, especially for larger projects.
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Efficient Frontend Development
Streamlines frontend code management, allowing developers to focus on functionality rather than setup. Combines visual mapping with NEAR components to optimize the dApp-building process.
├── landing-page
├── frontend
├── backend
├── AI
└── README.md
- User Input: The user provides a text prompt or description of the components.
- AI Processing & Code Generation:
- Generate a node and visualize on Reactflow UI:
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Lê Khắc Thanh Tùng
Role: Fullstack Developer
Github: tung-lee
Email: -
Đỗ Phạm Phúc Tính
Role: AI Developer
Github: dpptinh
Email: -
Hoàng Phú Lộc
Role: Frontend developer
Github: lochoang174
Email: -
Võ Nguyên Phú Quí
Role: Blockchain Developer
Github: phuquivo03
Email: [email protected] -
Anh Quân
Role: AI Developer
Github: AnhQuan2004
Email:
This project is licensed under the MIT License - see the LICENSE file for details.